Tuesday, April 12, 2016

Entrepreneur

An entrepreneur is one who creates a new business in the face of risk and uncertainty for achieving profit and growth opportunities and assembles the necessary resources to capitalize on those opportunities. While we may not be able to teach entrepreneurship, we can teach the skills of small business management. This is an important distinction to make to students. Noted psychologist David McClelland characterized high achievers/entrepreneurs as possessing these traits:

v Desire for responsibility

v Preference for moderate risk (risk eliminators)

v Confidence in their ability to succeed

v Desire for immediate feedback

v High level of energy

v Future orientation (serial entrepreneurs)

v Skill in organization

v Value of achievement over money

Other characteristics of entrepreneurs include:

v High degree of commitment

v Willingness to accept risk, work hard and take action

v Flexibility

The Benefits of Entrepreneurship

The primary benefits entrepreneurs enjoy include the opportunity to:

v Create their own destiny

v Make a difference

v Reach their full potential

v Generate impressive profits

v Contribute to society and be recognized for their efforts

v Do what they enjoy and have fun at it!

The Potential Drawbacks of Entrepreneurship

With these potential rewards, Entrepreneurship also presents risk and uncertainty. Entrepreneurs may experience:

v Uncertainty of income –”The entrepreneur is the last one to be paid.”

v Risk of losing their entire investment

v Long hours and hard work

v Lower quality of life until the business gets established

v High levels of stress

v Complete responsibility

v Discouragement

The Power of “Small” Business

Because big business is more visible than small business, most people underestimate the role of the small firm in the U.S. economy. The definition of a “Small Business” is: 1. One which is independently owned and operated and not dominant in its field. 2. Eligibility requirements are based on the specific industry.

v Retailing – annual sales/receipts not exceeding $3.5 to $13.5 million.

v Services – annual receipts not exceeding $2.5 to $14.5 million.

v Wholesaling – yearly sales must not be over $9.5 to $22 million.

v Agriculture – annual receipts not exceeding $1.0 to $3.5 million.

v Construction – General construction with annual receipts not exceeding $17 million.

v Special Trade Construction – annual receipts not exceeding $7 million.

v Manufacturing – maximum number of employees may range from 500 to 1,500 depending on the industry. The most commonly used measure of small business is the number of employees on a firm’s payroll. The White House Conference on Small Business definition is: A firm employing 500 people or fewer.

The Committee for Economic Development states that a small business must meet two of four stated criteria:

v Management is independent.

v Capital is supplied and ownership is held by an individual or a small group.

v Area of operation is mainly local; markets need not be local.

v Size is small when compared to the biggest unit in the field

The Ten Deadly Mistakes of Entrepreneurship Studies have indicated that there are common reasons for new business ventures to fail. These causes of small business failure may include:

v Management mistakes

v Lack of experience

v Poor financial control

v Weak marketing efforts

v Failure to develop a strategic plan

v Uncontrolled growth

v Poor location

v Improper inventory control

v Incorrect pricing

v Inability to make the “entrepreneurial transition”

Putting Failure into Perspective

Entrepreneurs don’t fail—the venture fails.

v There are no such things as failures, only results.

v Always look to turn a negative situation into a positive opportunity.

v Have no fear of failure and be sure to have a contingency plan.

v The only people who never fail are those who never do anything or never attempt anything new. The successful entrepreneur understands the meaning of these clichés and knows how to deal with adversity in a proactive and positive manner

How to Avoid the Pitfalls

These same studies have indicated that entrepreneurs can increase their chances for success if they:

v Know their business in depth.

v Develop a solid business plan in writing.

v Manage financial resources.

v Understand financial statements.

v Learn to manage people effectively.

v Keep in tune with who they are.

U.S. takes a positive “negative” approach to trade with Cuban entrepreneurs

In keeping with the Obama Administration's fresh approach to relations with Cuba, on Friday the State Department released its list of goods and services eligible for importation from the nascent but growing Cuban private sector. Americans can now directly support independent Cuban entrepreneurs and cooperatives through commerce, a move policy makers hope will empower them to determine their own economic and political futures.

The Section 515.582 list, characterized as a "living document" that will be updated periodically, further clarifies the path breaking Commerce and Treasury Department regulations released in January. It takes a permissive, "negative" approach that identifies specific prohibited categories of items and allows everything not specifically listed as permissible items for importation to the United States. It lays out a flexible framework and sets the right tone for encouraging trade with the approximately 500,000 registered self-employed workers.

Certain goods like some agricultural products (sugar, tobacco), some textiles (cotton, wool) pharmaceuticals, and base metals (nickel) are, not surprisingly, excluded, since these products are almost exclusively produced by state owned enterprises. Notably, unlike the itemized list of goods, the new regulations authorize importation of all private sector services, which will allow U.S. businesses to access the human capital for which the island is well known. For example, Americans can now hire Cuban entrepreneurs or cooperatives to design software, provide accounting support, or translate documents, as long as they are certified as independent of the state. The negative approach looks like a very positive approach indeed.

The execution of this policy, however, is fraught with challenges stemming from the fifty-plus years of icy relations and the current Cuban context.

v Shipping. Cuba and the United States still do not have direct mail services and the U.S. embargo precludes most global providers (UPS, FedEx, and DHL) from shipping between the two countries. The most workable alternative to standard shipping is unaccompanied baggage transported on the daily charter flights between (primarily) Florida and the island.

v While not well suited to commercial shipping, this arrangement would facilitate initial micro-exchanges, build confidence and work out the kinks.

v Tariffs. Goods imported from Cuban entrepreneurs valued over $800 in total will be subject to Smoot-Hawley level tariffs, as high as 50% in some cases. As a member of the WTO, Cuba enjoys Most Favored Nation status but a national security exception in the U.S. embargo permits these highway robbery level tariffs. At least in the short- to medium-term, importers face cost-prohibitive fees.

v Financial transactions. The January 16 regulatory changes permit the use of debit and credit cards on the island and allow U.S. financial institutions to open correspondent accounts on the island to "facilitate the processing of authorized transactions." However, this will take time to implement and requires that the relevant actors (Visa, Mastercard, Western Union and major U.S.-based banks) be prepared to take the risk given the uncertain regulatory environment in Cuba. Most Cubans deal in cash rather than through the highly overregulated Cuban state banking system, which is smaller now than it was in 1959. Until financial institutions set up the necessary infrastructure, it may still be difficult to issue payment for services rendered or goods sent, outside of cash transactions.

v Categories of entrepreneurs. U.S. importers can only engage in transactions with independent Cuban entrepreneurs demonstrated by documentation such as the entity's self-employment or "cuentapropista" license issued by the Cuban government. At present, the Cuban government has identified only 201 categories of activities authorized for self-employment. Huge swaths of Cuba's human capital are excluded from participating in this emerging sector, primarily highly educated professions like economists, engineers, lawyers, and doctors. It remains to be seen if the Cuban government will expand the number of permissible categories or switch to a negative list, like the State Department imports list.

v Communication. Cuba remains one of the lowest ranked countries in terms of internet access, making it difficult to receive and fill orders, communicate with buyers, or establish call centers. Cuban citizens are eager to modernize and expand their telecommunications infrastructure, but the Cuban government has been very slow in expanding access and will likely be reticent to cede control. The new regulations issued in Janaury allow U.S. telecommunications companies to compete more readily in the Cuban market but it remains to be seen whether Havana is interested.

v The greatest unknown is how the Cuban government will react to these and other elements of the President's new policy of engagement. It is unclear, for example, whether entrepreneurs will even be permitted to export goods and services in the short term. To create a more business friendly environment and attract much-needed investment, Cuba's regulatory framework and judicial system require significant reforms. This is a much longer-term challenge that Cuba must grapple with, but as the international community and incipient Cuban private sector become more active, pressure for deeper and faster reform should grow.

v This policy shift and resulting regulatory changes are complex issues and, by government standards, they have been drafted and implemented swiftly. It will take time for companies to catch up and evaluate whether to take on the risks of engagement. But the benefits are clear: the authorization of imports from Cuban entrepreneurs inserts capital into the non-state sector, builds relationships between Cuban and American citizens, and perhaps even facilitates some much-needed reconciliation between the two countries. Congress would do well to consider the positive impact trade could have on Cuban citizens as it considers the recently introduced bipartisan legislation to end the embargo.

Characteristic of Entrepreneurship

Entrepreneur

v Desire for responsibility

v Preference for moderate risk (risk eliminators)

v Confidence in their ability to succeed

v Desire for immediate feedback

v High level of energy

v Future orientation (serial entrepreneurs)

v Skill in organization

v Value of achievement over money

Other characteristics of entrepreneurs include:

v High degree of commitment

v Willingness to accept risk, work hard and take action

v Flexibility

The Benefits of Entrepreneurship

The primary benefits entrepreneurs enjoy include the opportunity to:

v Create their own destiny

v Make a difference

v Reach their full potential

v Generate impressive profits

v Contribute to society and be recognized for their efforts

v Do what they enjoy and have fun at it!

Characteristics of Successful Entrepreneurs:

Passion & Motivation

The one word that describes the basic requirement for an entrepreneurship venture is “Passion.”

v Is there something that you can work on over and over again, without getting bored?

v Is there something that keeps you awake because you have not finished it yet?

v Is there something that you have built and want to continue to improve upon, again and again?

v Is there something that you enjoy the most and want to continue doing for the rest of your life?

Your demonstration of passion and motivation will determine your success in any entrepreneurial venture. From building and implementing a prototype, to pitching your idea to venture capitalists, success is a function of passion and determination.

You'll find that with these have a much easier finally, it's impossible to be a successful entrepreneur if you aren't passionate about your work. Passion can be defined subjectively, but what's important is that you're excited to come to work every day. You may not like every task you have to perform or every person you have to work with, but at the end of the day, you must be both satisfied and exhilarated to be the leader of your own enterprise.

Without passion, your productivity will suffer, but more importantly, you'll never be happy with where you are. Only when you're truly passionate about your work will you be able to find the success you yearn for.

Self-motivated

Successful entrepreneurs do not need someone who holds them accountable or forces them to be efficient and productive. Unfortunately, without a manager, many people cannot take their business past the planning stages. It takes hard work to create your own business; most people need someone who forces them to keep working. Moreover, when people do not have someone to hold them accountable, they may let their work’s quality suffer. For example, many freelance writers set their own hours and choose their workload. However, for this same reason, many freelance writers do not work how they ought to work.

Creative

When creating a business idea, many entrepreneurs have to be very creative. There is a good chance that someone else has already established himself as the authority for the niche that a new entrepreneur chooses. However, with a little creative twist, new entrepreneurs can take old ideas or business models and revolutionize them, making them attractive to potential clients or customers.

Creativity allows for ideas and innovation. Ideas and innovation often lead to money and success. Sergey Brin and Larry Page founded Google in their colossal quest to master the Internet search engine. Steve Jobs and Apple revolutionized the gadget industry with iPods, Macbooks, and the iPhone. In many cases, a single creative idea can makes its inventor billions.

The desire to be an expert
Entrepreneurs like a challenge. If they didn't, they'd probably have chosen another line of work. But as exciting as it is to consider a new field, high-achieving entrepreneurs know the benefits of staying in the same industry for a while are immense. When you spend years in the same industry, you learn its history. Knowing what's been done before can help you identify how it can and should move forward. In the meantime, you'll build a network of relationships to support you in future endeavors, especially when times are lean. Those relationships are invaluable.

A forward-looking approach.
Successful entrepreneurs are always thinking ahead. They may stray from their roadmap, and that's okay, but they have one in mind. Having a clearly established set of goals will keep you from getting stuck. Your goals may be constantly evolving, but if you don't know where you want to go, chances are, you won't get anywhere.

Risk Taking and Rewards

Entrepreneurs are risk takers ready to dive deep into a future of uncertainty. But not all risk takers are successful entrepreneurs. Successful entrepreneurs are will to risk time and money on unknowns, but they also keep resources, plans and bandwidth for dealing with "unknown" in reserve. When evaluating risk, a successful entrepreneur will ask herself, is this risk worth the cost of my career, time and money? And, what will I do if this venture doesn't pay off?

Entrepreneurship requires risk. The measurement of this risk equates to the amount of time and money you invest into your business. However, this risk also tends to relate directly to the rewards involved. An entrepreneur who invests in a franchise pays for someone else's business plan and receives a respectable income, while an entrepreneur who undertakes groundbreaking innovations risks everything on an assumption that something revolutionary will work in the market. If such a revolutionary is wrong, she can lose everything. However, if she is right, she can suddenly become extremely wealthy.

Self-belief, Hard work & Disciplined Dedication

Entrepreneurs enjoy what they do. They believe in themselves and are confident and dedicated to their project. Occasionally, they may show stubbornness in their intense focus on and faith in their idea. But the flip side is their demonstrated discipline and dedication.

Adaptability & Flexibility

It’s good to be passionate or even stubborn about what you do. But being inflexible about client or market needs will lead to failure. Remember, an entrepreneurial venture is not simply about doing what you believe is good, but also making successful business out of it. Market needs are dynamic: changes are a recurring phenomenon. Successful entrepreneurs welcome all suggestions for optimization or customization that enhances their offering and satisfies client and market needs. A product you develop for yourself alone may qualify as a hobby, but a product for the market should satisfy market needs.

Understand Your Offering – And Its Market

Entrepreneurs know their product offering inside and out. They also know the marketplace and its dynamics inside and out. Remaining unaware of changing market needs, competitor moves and other external factors can bring even great products to failure (for example, Blockbuster).

Money Management

It takes time to get to profitability for any entrepreneurial venture. Till then, capital is limited and needs to be utilized wisely. Successful entrepreneurs realize this mandatory money management requirement and plan for present and future financial obligations (with some additional buffer). Even after securing funding or going fully operational, a successful businessman keeps a complete handle on cash flows, as it is the most important aspect of any business.

Planning (But not Over-planning)

Entrepreneurship is about building a business from scratch while managing limited resources (including time, money and personal relationships). It is a long-term commitment, and attempting to plan as much as possible at the beginning is a noble impulse. In reality, however, planning for everything and having a ready solution for all possible risks may prevent you from even taking the first step. Successful entrepreneurs do keep some dry powder in reserve, but more importantly they maintain a mindset and temperament to capable of dealing with unforeseen possibilities.

Do a feasibility analysis; identify time and capital thresholds; take the deep dive with your limited resources. If your thresholds are crossed, look for alternatives and be prepared to take the next exit.

Networking Abilities

Many people seek comfort in commiseration: friends, colleagues and neighbors are happy to complain with you about "the global slowdown,” poor demand, or unfair competition; but that won't improve the bottom line. What do successful entrepreneurs do? They reach out to mentors with more experience and extensive networks to seek valuable advice. Having such networking abilities, including more experienced mentors, is a key characteristics of successful entrepreneurs.

Being Prepared to Take the Exit

Not every attempt will result in success. The failure rate of entrepreneurial ventures is very high. At times, it is absolutely fine to take the “practical” exit route and try something new, instead of continuing to make sunk cost investments in the same venture. Many famous entrepreneurs weren't successful the first time around. But they had the serenity and foresight to know when to cut their losses.

The Bottom Line

Personal qualities and their correct demonstration with the right stakeholders are the determining factors for success or failure as an entrepreneur. A realistic self-assessment checklist against these suggested guidelines will ensure you take the right steps in the right direction to success.

Agility.

Agile entrepreneurs are able to treat every problem they encounter quickly and adeptly, without taking too long to address them. This agility allows entrepreneurs to remain proactive and vigilant, preventing small problems from becoming major ones.

On a larger scale, this ability also allows entrepreneurs to constantly change, and therefore improve, their businesses. With new technologies, new resources, and new trends emerging daily, the most successful businesses are ones who are able to adapt and grow with the times. Remaining agile in a position of leadership enables this course of growth.

Patience.

Too many entrepreneurs get started with a business based on dreams of becoming an overnight millionaire. Several leaders in the tech sector with some great new idea have been able to seemingly rise to success out of nowhere, but the reality is this level of success can only come after years of hard, committed effort. Successful entrepreneurs realize that all great things take time, and aren't impeded when their great ideas don't take off immediately.

Patience also goes a long way when building the infrastructure of your company. Great entrepreneurs want to build the best team, not one pieced together with the first candidates that cross their paths. They're also willing to make mistakes and go through temporary hardships if it's en route to a more stable, successful long-term vision.

Trust

Mutual trust is a necessity when working in a position of leadership, especially in the context of a small team that typically defines startups. For example, entrepreneurs need to trust their team leaders to accomplish their primary objectives without interference. If that trust isn't there, team leaders will not be able to execute their work effectively. It's also a symptom of a hire that isn't the best fit for the organization.

Of course, workers, partners, and investors all need to trust you as an entrepreneur as well. You can cultivate this trust by maintaining constant, transparent lines of communication, which will also facilitate greater productivity and a tighter sense of collaboration within the team.

Interest and Vision

The first factor for entrepreneurial success is interest. Since entrepreneurship pays off according to performance rather than time spent on a particular effort, an entrepreneur must work in an area that interests her. Otherwise, she will not be able to maintain a high level of work ethic, and she will most likely fail. This interest must also translate into a vision for the company's growth. Even if the day-to-day activities of a business are interesting to an entrepreneur, this is not enough for success unless she can turn this interest into a vision of growth and expansion. This vision must be strong enough that she can communicate it to investors and employees.

Skill

All of the interest and vision cannot make up for a total lack of applicable skill. As the head of a company, whether he has employees or not, an entrepreneur must be able to wear many hats and do so effectively. For instance, if he wants to start a business that creates mobile games, he should have specialized knowledge in mobile technology, the gaming industry, game design, mobile app marketing or programming.

Investment

An entrepreneur must invest in her company. This investment may be something less tangible, such as the time she spends or the skills or reputation she brings with her, but it also tends to involve a significant investment of assets with a clear value, whether they be cash, real estate or intellectual property. An entrepreneur who will not or cannot invest in her company cannot expect others to do so and cannot expect it to succeed.

Organization and Delegation

While many new businesses start as a one-man show, successful entrepreneurship is characterized by quick and stable growth. This means hiring other people to do specialized jobs. For this reason, entrepreneurship requires extensive organization and delegation of tasks. It is important for entrepreneurs to pay close attention to everything that goes on in their companies, but if they want their companies to succeed, they must learn to hire the right people for the right jobs and let them do their jobs with minimal interference from management

Tuesday, August 18, 2015

RAID(Redundant Arrays of Inexpensive Disks)

RAID

(Redundant Arrays of Inexpensive Disks)

In 1987, Patterson, Gibson and Katz at the University of California Berkeley, published a paper entitled “A Case for Redundant Array of Inexpensive Disks (RAID)”.Described the various types of Disk Arrays, referred to as the acronym RAID. The basic idea of RAID was to combine multiple, small inexpensive disks drive into an array of disk drives which yields performance exceeding that of a Single, Large Expensive Drive(SLED).Additionally this array of drives appear to the computer as a single logical storage unit or drive. In a SLED Reliabity becomes a big problem as the data in an entire disk may be lost. As the number of disks per component increases, the probability of failure also increases .Suppose a (reliable) disk fails every 100,000 hrs. Reliabity of a disk in an array of N disks = Reliability of 1 disk/ N 100000hrs / 100 = 1000 hrs. = 41.66 days. RAID can improve availability and throughput (although actually reliability – whether anything is broken – suffers because of the larger number of disks).Data is stored on several disks instead of a single disk. It’s a technology that enables greater levels of performance, reliability and/or large volumes when dealing with data. Disks are small (physically) and cheap, so it’s easy to put lots of disks (10s to 100s) in one box for increased storage, performance, and availability. Data plus some redundant information is striped across the disks in some way. Standard way of organizing disks and classifying the reliability of multi-disk systems. General methods: data duplication, parity, and error-correcting codes (ECC).

RAID idea: use redundancy to improve performance and reliability. Redundant array of cheap disks as one storage unit. Fast: simultaneous read and write disks in the array

Reliable: use parity to detect and correct errors

RAID can have different redundancy levels, achieving different performance and reliability. Seven different RAID levels (0-6). Basic idea is to connect multiple disks together to provide large storage capacity faster access to reading data redundant data. Many different levels of RAID systems differing levels of redundancy, error checking, capacity, and cost.

Where can I use RAID?

v LANs/WANs

v SANs

v Clustering environments

v Mission critical installations

v News centers

v Internet News Servers

v Enterprise Servers

v Performance Desktop

v Systems

v PC Workstations

v Workgroup/File Servers

v E-Mail Servers

v Intranet/Web Servers

v Application Servers

RAID Applications

Ø Transfer Rate Intensive Applications: (Typically RAID 0 environments) RAID

Ø Striping is ideal for transfer rate-intensive environments

Ø A transfer rate-intensive environment consists of :

Ø Applications that require a large amount of data to be processed in a fixed amount of time.

Ø Video playback and video editing are typical transfer rate intensive environments

Ø Photo processing, manipulation and rendering

Ø Request Rate Intensive Applications: (Typically RAID 5 environments)

Ø RAID is used in highly multi-tasking, request rate-intensive environments

Ø A request rate-intensive environment consists of:

Ø Data bases, file/web servers: -- high number of random smaller requests.

Ø A RAID drive can be configured to process each request within a stripe, allowing multiple requests to be processed in parallel.

Improvement of Reliability via Redundancy

It has two parts

1. Mirroring

2. Data Striping.

Mirroring:

Ø It performs following tasks:

Ø Duplicate every disk

Ø Logical disk consists of two physical disks.

Ø Every write is carried out on both disks.

Ø If one of the disk fails, data read from the other

Ø Data permanently lost only if the second disk fails before the first failed disk is replaced.

Example of mirroring in raid

Suppose mean time to repair is 10 hrs. The mean time to data loss of a mirrored disk system is

100,000 ^ 2 / (2 * 10) hrs. ~ 57,000 years.

Parallel Disk Systems

• We cannot improve the disk performance significantly as a single drive

- But many applications require high performance storage systems?

Solutions:

- Parallel Disk Systems

- Higher Reliability and Higher data-transfer rate.

DATA STRIPING

Ø It performs following tasks:

Ø Fundamental to RAID

v A method of concatenating multiple drives into one logical storage unit.

Ø Splitting the bits of each byte across multiple disks: bit – level striping

Ø E.g. an array of eight disks, write bit i of each byte to disk I

Ø Sectors are eight times the normal size

Ø Eight times the access rate

Ø Similarly for blocks of file, block-level striping

AI RAID LEVELS

The RAPID level defines how the disk are organized, reliability and performance will be improved.

v Data are distributed across the array of disk drives

v Redundant disk capacity is used to store parity information, which

v Guarantees data recoverability in case of a disk failure

v Levels decided according to schemes to provide redundancy at lower cost by using striping and “parity” bits.

Levels 0

This level offers no redundancy – no extra data is kept. The performance is the best of any level. Throughput is increased by striping data across several disks. It splits data among two or more disks. It provides good performance. It has lack of data redundancy means there is no fail over support with this configuration. In the diagram to the right, the odd blocks are written to disk 0 and the even blocks to disk 1 such that A1, A2, A3, A4, would be the order of blocks read if read sequentially from the beginning. Used I read only NFS systems and gaming systems.

RAID Level 0: Striping

The first RAID level is actually not a RAID level at all, in that there is no redundancy. However, RAID level 0, or striping as it is better known, serves as an excellent upper-bound on performance and capacity and thus is worth understanding. The simplest form of striping will stripe blocks across the disks of the system as follows (assume here a 4-disk array):

Disk 0 Disk 1 Disk 2 Disk 3

0 1 2 3

4 5 6 7

8 9 10 11

12 13 14 15

Table 38.1: RAID-0: Simple Striping

From Table 38.1, you get the basic idea: spread the blocks of the array across the disks in a round-robin fashion. This approach is designed to extract the most parallelism from the array when requests are made for contiguous chunks of the array (as in a large, sequential read, for example).We call the blocks in the same row a stripe; thus, blocks 0, 1, 2, and 3 are in the same stripe above. In the example, we have made the simplifying assumption that only 1 block (each of say size 4KB) is placed on each disk before moving on to the next. However, this arrangement need not be the case. For example, we could arrange the blocks across disks as in Table 38.2:

Disk 0 Disk 1 Disk 2 Disk 3

0 2 4 6 chunk size:

1 3 5 7 2 blocks

8 10 12 14

9 11 13 15

Table 38.2: Striping with a Bigger Chunk Size

In this example, we place two 4KB blocks on each disk before moving on to the next disk. Thus, the chunk size of this RAID array is 8KB, and a stripe thus consists of 4 chunks or 32KB of data.

ASIDE: THE RAID MAPPING PROBLEM

Before studying the capacity, reliability, and performance characteristics of the RAID, we first present an aside on what we call the mapping problem. This problem arises in all RAID arrays; simply put, given a logical block to read or write, how does the RAID know exactly which physical disk and offset to access? For these simple RAID levels, we do not need much sophistication in order to correctly map logical blocks onto their physical locations. Take the first striping example above (chunk size = 1 block = 4KB). In this case, given a logical block address A, the RAID can easily compute the desired disk and offset with two simple equations:

Disk = A % number_of_disks

Offset = A / number_of_disks

Note that these are all integer operations (e.g., 4 / 3 = 1 not 1.33333...).Let’s see how these equations work for a simple example. Imagine in the first RAID above that a request arrives for block 14. Given that there are 4 disks, this would mean that the disk we are interested in is (14 % 4 = 2): disk 2. The exact block is calculated as (14 / 4 = 3): block 3. Thus, block 14 should be found on the fourth block (block 3, starting at 0) of the third disk (disk 2, starting at 0), which is exactly where it is.You can think about how these equations would be modified to support different chunk sizes. Try it! It’s not too hard.

Chunk Sizes

Chunk size mostly affects performance of the array. For example, a small chunk size implies that many files will get striped across many disks, thus increasing the parallelism of reads and writes to a single file; however, the positioning time to access blocks across multiple disks increases, because the positioning time for the entire request is determined by themaximu of the positioning times of the requests across all drives. A big chunk size, on the other hand, reduces such intra-file parallelism, and thus relies on multiple concurrent requests to achieve high throughput. However, large chunk sizes reduce positioning time; if, for example, a single file fits within a chunk and thus is placed on a single disk, the positioning time incurred while accessing it will just be the positioning time of a single disk. Thus, determining the “best” chunk size is hard to do, as it requires a great deal of knowledge about the workload presented to the disk system [CL95]. For the rest of this discussion, we will assume that the array uses a chunk size of a single block (4KB). Most arrays use larger chunk sizes (e.g., 64 KB), but for the issues we discuss below, the exact chunk size does not matter; thus we use a single block for the sake of simplicity.

Back To RAID-0 Analysis

Let us now evaluate the capacity, reliability, and performance of striping. From the perspective of capacity, it is perfect: given N disks, striping delivers N disks worth of useful capacity. From the standpoint of reliability, striping is also perfect, but in the bad way: any disk failure will lead to data loss. Finally, performance is excellent: all disks are utilized, often in parallel, to service user I/O requests.

Evaluating RAID Performance

In analyzing RAID performance, one can consider two different performance metrics. The first is single-request latency. Understanding the latency of a single I/O request to a RAID is useful as it reveals how much parallelism can exist during a single logical I/O operation. The second is steady-state throughput of the RAID, i.e., the total bandwidth of many concurrent requests. Because RAIDs are often used in high-performance environments, the steady-state bandwidth is critical, and thus will be the main focus of our analyses. To understand throughput in more detail, we need to put forth some workloads of interest. We will assume, for this discussion, that there are two types of workloads: sequential and random. With a sequential workload, we assume that requests to the array come in large contiguous chunks; for example, a request (or series of requests) that accesses 1 MB of data, starting at block (B) and ending at block (B + 1 MB), would be deemed sequential. Sequential workloads are common in many environments (think of searching through a large file for a keyword), and thus are considered important. For random workloads, we assume that each request is rather small, and that each request is to a different random location on disk. For example, a random stream of requests may first access 4KB at logical address 10, then at logical address 550,000, then at 20,100, and so forth. Some important workloads, such as transactional workloads on a database management system (DBMS), exhibit this type of access pattern, and thus it is considered an important workload. Of course, real workloads are not so simple, and often have a mix of sequential and random-seeming components as well as behaviors in between the two. For simplicity, we just consider these two possibilities. As you can tell, sequential and random workloads will result in widely different performance characteristics from a disk. With sequential access, a disk operates in its most efficient mode, spending little time seeking and waiting for rotation and most of its time transferring data. With random access, just the opposite is true: most time is spent seeking and waiting for rotation and relatively little time is spent transferring data. To capture this difference in our analysis, we will assume that a disk can transfer data at S MB/s under a sequential workload, and R MB/s when under a random workload. In general, S is much greater than Rotor make sure we understand this difference, let’s do a simple exercise. Specifically, let’s calculate S and R given the following disk characteristics. Assume a sequential transfer of size 10 MB on average, and a random transfer of 10 KB on average. Also, assume the following disk

Characteristics:

Average seek time 7 ms. Average rotational delay 3 ms.Transfer rate of disk 50 MB/s. To compute S, we need to first figure out how time is spent in a typical 10 MB transfer. First, we spend 7 ms seeking, and then 3 ms rotating. Finally, transfer begins; 10 MB @ 50 MB/s leads to 1/5th of a second, or 200 ms, spent in transfer. Thus, for each 10 MB request, we spend 210 ms completing the request. To compute S, we just need to divide:

S = Amount of Data

Time to access = 10 MB

210 ms = 47.62 MB/s

As we can see, because of the large time spent transferring data, S is very near the peak bandwidth of the disk (the seek and rotational costs have been amortized).We can compute R similarly. Seek and rotation are the same; we then compute the time spent in transfer, which is 10 KB @ 50 MB/s, or 0.195ms.

R = Amount of Data

Time to access = 10 KB

10.195 ms = 0.981 MB/s

As we can see, R is less than 1 MB/s, and S/R is almost 50.

Back To RAID-0 Analysis, Again

Let’s now evaluate the performance of striping. As we said above, it is generally good. From a latency perspective, for example, the latency of a single-block request should be just about identical to that of a single disk; after all, RAID-0 will simply redirect that request to one of its disks. From the perspective of steady-state throughput, we’d expect to get the full bandwidth of the system. Thus, throughput equals N (the number of disks) multiplied by S (the sequential bandwidth of a single disk). For a large number of random I/Os, we can again use all of the disks, and thus obtain N · R MB/s. As we will see below, these values are both the simplest to calculate and will serve as an upper bound in comparison with other RAID levels.

RAID Level 1

Ø It performs following tasks:

Ø A complete file is stored on a single disk.

Ø A second disk contains an exact copy of the file

Ø Provides complete redundancy of data

Ø Read performance can be improved

Ø file data can be read in parallel

Ø Write performance suffers must write the data out twice

Ø Most expensive RAID implementation

Ø requires twice as much storage space

RAID Level 1: Mirroring

Our first RAID level beyond striping is known as RAID level 1, or mirroring. With a mirrored system, we simply make more than one copy of each block in the system; each copy should be placed on a separate disk, of course. By doing so, we can tolerate disk failures. In a typical mirrored system, we will assume that for each logical block, the RAID keeps two physical copies of it. Here is an example:

Disk 0 Disk 1 Disk 2 Disk 3

0 0 1 1

2 2 3 3

4 4 5 5

6 6 7 7

Table 38.3: Simple RAID-1: Mirroring

In the example, disk 0 and disk 1 have identical contents, and disk 2 and disk 3 do as well; the data is striped across these mirror pairs. In fact, you may have noticed that there are a number of different ways to place block copies across the disks. The arrangement above is a common one and is sometimes called RAID-10 or (RAID 1+0) because it uses mirrored pairs (RAID-1) and then stripes (RAID-0) on top of them; another common arrangement is RAID-01 (or RAID 0+1), which contains two large striping (RAID-0) arrays, and then mirrors (RAID-1) on top of them. For now, we will just talk about mirroring assuming the above layout. When reading a block from a mirrored array, the RAID has a choice: it can read either copy. For example, if a read to logical block 5 is issued to the RAID, it is free to read it from either disk 2 or disk 3. When writing a block, though, no such choice exists: the RAID must update both copies of the data, in order to preserve reliability. Do note, though, that these writes can take place in parallel; for example, a write to logical block 5 could proceed to disks 2 and 3 at the same time.

RAID-1 Analysis

Let us assess RAID-1. From a capacity standpoint, RAID-1 is expensive; with the mirroring level = 2, we only obtain half of our peak useful capacity. Thus, with N disks, the useful capacity of mirroring is N/2. From a reliability standpoint, RAID-1 does well. It can tolerate the failure of any one disk. You may also notice RAID-1 can actually do better than this, with a little luck. Imagine, in the figure above, that disk 0 and disk 2 both failed. In such a situation, there is no data loss! More generally, a mirrored system (with mirroring level of 2) can tolerate 1 disk failure for certain, and up to N/2 failures depending on which disks fail. In practice, we generally don’t like to leave things like this to chance; thus most people consider mirroring to be good for handling a single failure. Finally, we analyze performance. From the perspective of the latency of a single read request, we can see it is the same as the latency on a single disk; all the RAID-1 does is direct the read to one of its copies. A write is a little different: it requires two physical writes to complete before it is done. These two writes happen in parallel, and thus the time will be roughly equivalent to the time of a single write; however, because the logical write must wait for both physical writes to complete, it suffers the worst-case seek and rotational delay of the two requests, and thus (on average) will be slightly higher than a write to a single disk.

ASIDE: THE RAID CONSISTENT-UPDATE PROBLEM

Before analyzing RAID-1, let us first discuss a problem that arises in any multi-disk RAID system, known as the consistent-update problem [DAA05]. The problem occurs on a write to any RAID that has to update multiple disks during a single logical operation. In this case, let us assume we are considering a mirrored disk array. Imagine the write is issued to the RAID, and then the RAID decides that it must be written to two disks, disk 0 and disk 1. The RAID then issues the write to disk 0, but just before the RAID can issue the request to disk 1, a power loss (or system crash) occurs. In this unfortunate case, let us assume that the request to disk 0 completed (but clearly the request to disk 1 did not, as it was never issued).The result of this untimely power loss is that the two copies of the block are now inconsistent; the copy on disk 0 is the new version, and the copy on disk 1 is the old. What we would like to happen is for the state of both disks to change atomically, i.e., either both should end up as the new version or neither. The general way to solve this problem is to use a write-ahead log of some kind to first record what the RAID is about to do (i.e., update two disks with a certain piece of data) before doing it. By taking this approach, we can ensure that in the presence of a crash, the right thing will happen; by running a recovery procedure that replays all pending transactions to the RAID, we can ensure that no two mirrored copies (in the RAID-1 case)are out of sync. One last note: because logging to disk on every write is prohibitively expensive, most RAID hardware includes a small amount of non-volatile RAM (e.g., battery-backed) where it performs this type of logging. Thus, consistent update is provided without the high cost of logging to disk. To analyze steady-state throughput, let us start with the sequential workload. When writing out to disk sequentially, each logical write must result in two physical writes; for example, when we write logical block 0 (in the figure above), the RAID internally would write it to both disk 0 and disk 1. Thus, we can conclude that the maximum bandwidth obtained during sequential writing to a mirrored array is (N2 · S), or half the peak band width. Unfortunately, we obtain the exact same performance during a sequential read. One might think that a sequential read could do better, because it only needs to read one copy of the data, not both. However, let’s use an example to illustrate why this doesn’t help much. Imagine we need to read blocks 0, 1, 2, 3, 4, 5, 6, and 7. Let’s say we issue the read of 0 to disk 0, the read of 1 to disk 2, the read of 2 to disk 1, and the read of 3 to disk 3. We continue by issuing reads to 4, 5, 6, and 7 to disks 0, 2, 1 and 3, respectively. One might naively think that because we are utilizing all disks, we are achieving the full bandwidth of the array. To see that this is not the case, however, consider the requests a single disk receives (say disk 0). First, it gets a request for block 0; then, it gets a request for block 4 (skipping block 2). In fact, each disk receives a request for every other block. While it is rotating over the skipped block, it is not delivering useful bandwidth to the client. Thus, each disk will only deliver half its peak bandwidth. And thus, the sequential read will only obtain a bandwidth of (N2 · S) MB/random reads are the best case for a mirrored RAID. In this case, we can distribute the reads across all the disks, and thus obtain the full possible bandwidth. Thus, for random reads, RAID-1 delivers N · R MB/finally, random writes performs you might expect: N2 ·RMB/s. Each logical write must turn into two physical writes, and thus while all the disks will be in use, the client will only perceive this as half the available bandwidth. Even though a write to logical block X turns into two parallel writes to two different physical disks, the bandwidth of many small requests only achieves half of what we saw with striping. As we will soon see, getting half the available bandwidth is actually pretty good!

RAID Level 2

It performs following tasks

• Uses Hamming (or any other) error-correcting code (ECC)

• Intended for use in drives which do not have built-in error detection

• Central idea is if one of the disks fail the remaining bits of the byte and the associated ECC bits can be used to reconstruct the data

• Not very popular

• Bit-level Striping with Hamming (ECC) codes for error correction

• All 7 disk arms are synchronized and move in unison

• Complicated controller

• Single access at a time

• Tolerates only one error, but with no performance degradation

Memory-Style ECC (RAID Level 2)

Ø Some disks in array are used to hold ECC

Ø Using Hamming codes as the ECC

Ø Correct one bit error in a 4 bits code word requires 3 redundant bits.

http://www.ecs.umass.edu/ece/koren/architecture/Raid/raid2.gif

Raid Level 3

Improves upon RAID 2, known as Bit-Interleaved Parity

• Disk Controllers can detect whether a sector has been read correctly.

• Storage overhead is reduced – only 1 parity disk

• Expense of computing and writing parity

• Need to include a dedicated parity hardware

RAID 3: Bit-Interleaved Parity

l Reads and writes go to all disks in a group, with one extra disk to hold the check information in case there is a failure. Parity is simply the sum of the data in all the disks modulo 2. Lost data can be reconstructed by examining the parity. Every access goes to all disks.

l One disk in the array stores parity for the other disks

¡ Enough to correct the error when the disk controller tells which disk fails.

+ More efficient that Levels 1 and 2

- Parity disk doesn’t add bandwidth

http://www.ecs.umass.edu/ece/koren/architecture/Raid/raid3.gif

Raid Level 4

Stripes data at a block level across several drives, with parity stored on one drive - block-interleaved parity

• Allows recovery from the failure of any of the disks

• Performance is very good for reads

• Writes require that parity data be updated each time. Slows small random writes but large writes are fairly fast

RAID Level 4: Saving Space with Parity

We now present a different method of adding redundancy to a disk array known as parity. Parity-based approaches attempt to use less capacity and thus overcome the huge space penalty paid by mirrored systems. They do so at a cost, however: performance. In a five-disk RAID-4 system, we might observe the following layout:

Disk 0 Disk 1 Disk 2 Disk 3 Disk 4

0 1 2 3 P0

4 5 6 7 P1

8 9 10 11 P2

12 13 14 15 P3

As you can see, for each stripe of data, we have added a single parity block that stores the redundant information for that stripe of blocks. For example, parity block P1 has redundant information that it calculated from blocks 4, 5, 6, and 7.To compute parity, we need to use a mathematical function that enables us to withstand the loss of any one block from our stripe. It turns out the simple function XOR does the trick quite nicely. For a given set of bits, the XOR of all of those bits returns a 0 if there are an even number of 1’s in the bits, and a 1 if there are an odd number of 1’s. For example:

C0 C1 C2 C3 P

0 0 1 1 XOR (0, 0,1, 1) = 0

0 1 0 0 XOR (0, 1,0,0) = 1

In the first row (0,0,1,1), there are two 1’s (C2, C3), and thus XOR of all of those values will be 0 (P); similarly, in the second row there is only one 1 (C1), and thus the XOR must be 1 (P). You can remember this in a very simple way: that the number of 1’s in any row must be an even (not odd) number; that is the invariant that the RAID must maintain in order for parity to be correct. From the example above, you might also be able to guess how parity information can be used to recover from a failure. Imagine the column labeled C2 is lost. To figure out what values must have been in the column, we simply have to read in all the other values in that row (including the XOR’d parity bit) and reconstruct the right answer. Specifically, assume the first row’s value in column C2 is lost (it is a 1); by reading the other values in that row (0 fromC0, 0 fromC1, 1 fromC3, and 0 from the parity column P), we get the values 0, 0, 1, and 0. Because we know that XOR keeps an even number of 1’s in each row, we know what the missing data must be: a 1. And that is how reconstruction works in a XOR-based parity scheme! Note also how we compute the reconstructed value: we just XOR the data bits and the parity bits together, in the same way that we calculated the parity in the first place. Now you might be wondering: we are talking about XORing all of these bits, and yet above we know that the RAID places 4KB (or larger) blocks on each disk; how do we apply XOR to a bunch of blocks to compute the parity? It turns out this is easy as well. Simply perform a bitwise XOR across each bit of the data blocks; put the result of each bitwise XOR into the corresponding bit slot in the parity block. For example, if we had blocks of size 4 bits (yes, this is still quite a bit smaller than a 4KB block, but you get the picture), they might look something like this:

Block0 Block1 Block2 Block3 Parity

00 10 11 10 11

10 01 00 01 10

As you can see from the figure, the parity is computed for each bit of each block and the result placed in the parity block.

RAID-4 Analysis

Let us now analyze RAID-4. From a capacity standpoint, RAID-4 uses 1 disk for parity information for every group of disks it is protecting. Thus, our useful capacity for a RAID group is (N-1). Reliability is also quite easy to understand: RAID-4 tolerates 1 disk failure and no more. If more than one disk is lost, there is simply no way to reconstruct the lost data. Finally, there is performance. This time, let us start by analyzing steady state throughput. Sequential read performance can utilize all of the disks except for the parity disk, and thus deliver a peak effective bandwidth of(N − 1) · S MB/s (an easy case).To understand the performance of sequential writes, we must first understand how they are done. When writing a big chunk of data to disk, RAID-4 can perform a simple optimization known as a full-stripe write. For example, imagine the case where the blocks 0, 1, 2, and 3 have been sent to the RAID as part of a write request (Table 38.4).

Disk 0 Disk 1 Disk 2 Disk 3 Disk 4

0 1 2 3 P0

4 5 6 7 P1

8 9 10 11 P2

12 13 14 15 P3

Table 38.4: Full-stripe writes in RAID-4

In this case, the RAID can simply calculate the new value of P0 (by performing an XOR across the blocks 0, 1, 2, and 3) and then write all of the blocks (including the parity block) to the five disks above in parallel (highlighted in gray in the figure). Thus, full-stripe writes are the most efficient way for RAID-4 to write to disk. Once we understand the full-stripe write, calculating the performance of sequential writes on RAID-4 is easy; the effective bandwidth is also (N −1) ·S MB/s. Even though the parity disk is constantly in use during the operation, the client does not gain performance advantage from it.Now let us analyze the performance of random reads. As you can also see from the figure above, a set of 1-block random reads will be spread across the data disks of the system but not the parity disk. Thus, the effective performance is: (N − 1) · R MB/s. Random writes, which we have saved for last, present the most interesting case for RAID-4. Imagine we wish to overwrite block 1 in the example above. We could just go ahead and overwrite it, but that would leave us with a problem: the parity block P0 would no longer accurately reflect the correct parity value for the stripe. Thus, in this example, P0 must also be updated. But how can we update it both correctly and efficiently? It turns out there are two methods. The first, known as additive parity, requires us to do the following. To compute the value of the new parity block, read in all of the other data blocks in the stripe in parallel (in the example, blocks 0, 2, and 3) and XOR those with the new block (1). The result is your new parity block. To complete the write, you can then write the new data and new parity to their respective disks, also in parallel. The problem with this technique is that it scales with the number of disks, and thus in larger RAIDs requires a high number of reads to compute parity. Thus, the subtractive parity method. For example, imagine this string of bits (4 data bits, one parity):

C0 C1 C2 C3 P

0 0 1 1 XOR (0,0,1,1) = 0

Let’s imagine that we wish to overwrite bit C2 with a new value which we will call C2 (new). The subtractive method works in three steps. First, we read in the old data at C2 (C2 (old) = 1) and the old parity (P (old) = 0). Then, we compare the old data and the new data; if they are the same (e.g., C2 (new) = C2 (old)), then we know the parity bit will also remain the same (i.e., P (new) = P (old)). If, however, they are different, then we must flip the old parity bit to the opposite of its current state, that is, if (P(old) == 1), P(new) will be set to 0; if (P(old) == 0), P(new) will be set to 1. We can express this whole mess neatly with XOR as it turns out (if you understand XOR, this will now make sense to you): P (new) = (C (old) XOR C (new)) XOR P (old) Because we are dealing with blocks, not bits, we perform this calculation over all the bits in the block (e.g., 4096 bytes in each block multiplied by 8 bits per byte). Thus, in most cases, the new block will be different than the old block and thus the new parity block will too.You should now be able to figure out when we would use the additive parity calculation and when we would use the subtractive method. Think about how many disks would need to be in the system so that the additive method performs fewer I/Os than the subtractive method; what is the cross-over point? For this performance analysis, let us assume we are using the subtractive method. Thus, for each write, the RAID has to perform 4 physical I/Os (two reads and two writes). Now imagine there are lots of writes submitted to the RAID; how many can RAID-4 perform in parallel? To understand, let us again look at the RAID-4 layout (Figure 38.5).

Disk 0 Disk 1 Disk 2 Disk 3 Disk 4

0 1 2 3 P0

4 5 6 7 +P1

8 9 10 11 P2

12 13 14 15 +P3

Table 38.5: Example: Writes To 4, 13, and Respective Parity Blocks

Now imagine there were 2 small writes submitted to the RAID-4 at about the same time, to blocks 4 and 13 (marked with in the diagram).The data for those disks is on disks 0 and 1, and thus the read and write to data could happen in parallel, which is good. The problem that arises is with the parity disk; both the requests have to read the related parity blocks for 4 and 13, parity blocks 1 and 3 (marked with +). Hopefully, the issue is now clear: the parity disk is a bottleneck under this type of workload; we sometimes thus call this the small-write problem for parity based RAIDs. Thus, even though the data disks could be accessed in parallel, the parity disk prevents any parallelism from materializing; all writes to the system will be serialized because of the parity disk. Because the parity disk has to perform two I/Os (one read, one write) per logical I/O, we can compute the performance of small random writes in RAID-4 by computing the parity disk’s performance on those two I/Os, and thus we achieve (R/2) MB/s. RAID-4 throughput under random small writes is terrible; it does not improve as you add disks to the system. We conclude by analyzing I/O latency in RAID-4. As you now know, a single read (assuming no failure) is just mapped to a single disk, and thus its latency is equivalent to the latency of a single disk request. The latency of a single write requires two reads and then two writes; the reads can happen in parallel, as can the writes, and thus total latency is about twice that of a single disk (with some differences because we have to wait for both reads to complete and thus get the worst-case positioning time, but then the updates don’t incur seek cost and thus may be a better-than average positioning cost).

RAID Level 5: Rotating Parity

To address the small-write problem (at least, partially), Patterson, Gibson, and Katz introduced RAID-5. RAID-5 works almost identically to RAID-4, except that it rotates the parity block across drives (Figure 38.6).

Disk 0 Disk 1 Disk 2 Disk 3 Disk 4

0 1 2 3 P0

5 6 7 P1 4

10 11 P2 8 9

15 P3 12 13 14

P4 16 17 18 19

Table 38.6: RAID-5With Rotated Parity

As you can see, the parity block for each stripe is now rotated across the disks, in order to remove the parity-disk bottleneck for RAID-4.

RAID-5 Analysis

Much of the analysis for RAID-5 is identical to RAID-4. For example, the effective capacity and failure tolerance of the two levels are identical. So are sequential read and write performance. The latency of a single request (whether a read or a write) is also the same as RAID-4.Randomread performance is a little better, because we can utilize all of the disks. Finally, random write performance improves noticeably overRAID-4, as it allows for parallelism across requests. Imagine a write to block 1 and a write to block 10; this will turn into requests to disk 1 and disk 4 (for block 1 and its parity) and requests to disk 0 and disk 2 (for block 10 and its parity). Thus, they can proceed in parallel. In fact, we can generally assume that that given a large number of random requests, we will be able to keep all the disks about evenly busy. If that is the case, then our total bandwidth for small writes will be N4 · R MB/s. The factor of four loss is due to the fact that each RAID-5 write still generates 4 total I/O operations, which is simply the cost of using parity-based RAID.REDUNDANT ARRAYS OF INEXPENSIVE DISKS (RAIDS) 15

RAID-0 RAID-1 RAID-4 RAID-5

Capacity N N/2 N − 1 N − 1

Reliability 0 1(for sure) 1 1

N/2 (if lucky)

Throughput

Sequential Read N · S (N/2) · S (N − 1) · S (N − 1) · S

Sequential Write N · S (N/2) · S (N − 1) · S (N − 1) · S

Random Read N · R N · R (N − 1) · R N · R

Random Write N · R (N/2) · R 1/2· R N/4 R

Latency

Read D D D D

Write D D 2D 2D

Table 38.7: RAID Capacity, Reliability, and Performance

Because RAID-5 is basically identical to RAID-4 except in the few cases where it is better, it has almost completely replaced RAID-4 in them market place. The only place where it has not is in systems that know they will never perform anything other than a large write, thus avoiding the small write problem altogether [HLM94]; in those cases, RAID-4 is sometimes used as it is slightly simpler to build.

Raid level 6

For raid 6 array with n disks,

Ø Data is divided into n-2 strips

Ø Two pieces of parity information are collected over the n-2 strips(using a Reed-Solomon code)

Ø The parity information is collected over the disk

Raid Advantage

Ø RAID provides an environment of highly reliable, fault tolerant disk drive sub-systems

Ø RAID adds life to disk drives as the controller manages the I/O load equally amongst all the drives in the Array reducing the risk of “single point-of-failure”

Ø A “successful” RAID environment includes reliable robust disk drives

Ø Each RAID environment will include multiple disk drives

Ø Mylex PCI RAID controllers can attach as many as 45 drives per RAID controller, up to 16 controllers per system for an astonishing -- 720 disk drives per system configuration

Ø Mylex external RAID controllers can attach as many as 90 drives per storage subsystem and can reside as part of a SAN (Storage Area

Ø Network)

Ø Capacities range from terabytes to petabytes!

REFERENCE:

PPT+BOOK (Redundant Arrays of Inexpensive Disks RAIDs)

Stripes data at a block level across several

• Allows recovery from the failure of any of the disks

• Performance is very good for reads

• Writes require that parity data be updated each time. Slows small

butlarge writes are fairly fast

Stripes data a RAID

(Redundant Arrays of Inexpensive Disks)

RAID idea: use redundancy to improve performance and reliability. Redundant array of cheap disks as one storage unit. Fast: simultaneous read and write disks in the array

Reliable: use parity to detect and correct errors

Where can I use RAID?

v LANs/WANs

v SANs

v Clustering environments

v Mission critical installations

v News centers

v Internet News Servers

v Enterprise Servers

v Performance Desktop

v Systems

v PC Workstations

v Workgroup/File Servers

v E-Mail Servers

v Intranet/Web Servers

v Application Servers

RAID Applications

Ø Transfer Rate Intensive Applications: (Typically RAID 0 environments) RAID

Ø Striping is ideal for transfer rate-intensive environments

Ø A transfer rate-intensive environment consists of :

Ø Applications that require a large amount of data to be processed in a fixed amount of time.

Ø Video playback and video editing are typical transfer rate intensive environments

Ø Photo processing, manipulation and rendering

Ø Request Rate Intensive Applications: (Typically RAID 5 environments)

Ø RAID is used in highly multi-tasking, request rate-intensive environments

Ø A request rate-intensive environment consists of:

Ø Data bases, file/web servers: -- high number of random smaller requests.

Ø A RAID drive can be configured to process each request within a stripe, allowing multiple requests to be processed in parallel.

Improvement of Reliability via Redundancy

It has two parts

1. Mirroring

2. Data Striping.

Mirroring:

Ø It performs following tasks:

Ø Duplicate every disk

Ø Logical disk consists of two physical disks.

Ø Every write is carried out on both disks.

Ø If one of the disk fails, data read from the other

Ø Data permanently lost only if the second disk fails before the first failed disk is replaced.

Example of mirroring in raid

Suppose mean time to repair is 10 hrs. The mean time to data loss of a mirrored disk system is

100,000 ^ 2 / (2 * 10) hrs. ~ 57,000 years.

Parallel Disk Systems

• We cannot improve the disk performance significantly as a single drive

- But many applications require high performance storage systems?

Solutions:

- Parallel Disk Systems

- Higher Reliability and Higher data-transfer rate.

DATA STRIPING

Ø It performs following tasks:

Ø Fundamental to RAID

v A method of concatenating multiple drives into one logical storage unit.

Ø Splitting the bits of each byte across multiple disks: bit – level striping

Ø E.g. an array of eight disks, write bit i of each byte to disk I

Ø Sectors are eight times the normal size

Ø Eight times the access rate

Ø Similarly for blocks of file, block-level striping

AI RAID LEVELS

The RAPID level defines how the disk are organized, reliability and performance will be improved.

v Data are distributed across the array of disk drives

v Redundant disk capacity is used to store parity information, which

v Guarantees data recoverability in case of a disk failure

v Levels decided according to schemes to provide redundancy at lower cost by using striping and “parity” bits.

Levels 0

RAID Level 0: Striping

Disk 0 Disk 1 Disk 2 Disk 3

0 1 2 3

4 5 6 7

8 9 10 11

12 13 14 15

Table 38.1: RAID-0: Simple Striping

Disk 0 Disk 1 Disk 2 Disk 3

0 2 4 6 chunk size:

1 3 5 7 2 blocks

8 10 12 14

9 11 13 15

Table 38.2: Striping with a Bigger Chunk Size

In this example, we place two 4KB blocks on each disk before moving on to the next disk. Thus, the chunk size of this RAID array is 8KB, and a stripe thus consists of 4 chunks or 32KB of data.

ASIDE: THE RAID MAPPING PROBLEM

Disk = A % number_of_disks

Offset = A / number_of_disks

Chunk Sizes

Back To RAID-0 Analysis

Evaluating RAID Performance

Characteristics:

S = Amount of Data

Time to access = 10 MB

210 ms = 47.62 MB/s

R = Amount of Data

Time to access = 10 KB

10.195 ms = 0.981 MB/s

As we can see, R is less than 1 MB/s, and S/R is almost 50.

Back To RAID-0 Analysis, Again

RAID Level 1

Ø It performs following tasks:

Ø A complete file is stored on a single disk.

Ø A second disk contains an exact copy of the file

Ø Provides complete redundancy of data

Ø Read performance can be improved

Ø file data can be read in parallel

Ø Write performance suffers must write the data out twice

Ø Most expensive RAID implementation

Ø requires twice as much storage space

RAID Level 1: Mirroring

Disk 0 Disk 1 Disk 2 Disk 3

0 0 1 1

2 2 3 3

4 4 5 5

6 6 7 7

Table 38.3: Simple RAID-1: Mirroring

RAID-1 Analysis

ASIDE: THE RAID CONSISTENT-UPDATE PROBLEM

RAID Level 2

It performs following tasks

• Uses Hamming (or any other) error-correcting code (ECC)

• Intended for use in drives which do not have built-in error detection

• Central idea is if one of the disks fail the remaining bits of the byte and the associated ECC bits can be used to reconstruct the data

• Not very popular

• Bit-level Striping with Hamming (ECC) codes for error correction

• All 7 disk arms are synchronized and move in unison

• Complicated controller

• Single access at a time

• Tolerates only one error, but with no performance degradation

Memory-Style ECC (RAID Level 2)

Ø Some disks in array are used to hold ECC

Ø Using Hamming codes as the ECC

Ø Correct one bit error in a 4 bits code word requires 3 redundant bits.

Raid Level 3

Improves upon RAID 2, known as Bit-Interleaved Parity

• Disk Controllers can detect whether a sector has been read correctly.

• Storage overhead is reduced – only 1 parity disk

• Expense of computing and writing parity

• Need to include a dedicated parity hardware

RAID 3: Bit-Interleaved Parity

l One disk in the array stores parity for the other disks

¡ Enough to correct the error when the disk controller tells which disk fails.

+ More efficient that Levels 1 and 2

- Parity disk doesn’t add bandwidth

Raid Level 4

Stripes data at a block level across several drives, with parity stored on one drive - block-interleaved parity

• Allows recovery from the failure of any of the disks

• Performance is very good for reads

• Writes require that parity data be updated each time. Slows small random writes but large writes are fairly fast

RAID Level 4: Saving Space with Parity

Disk 0 Disk 1 Disk 2 Disk 3 Disk 4

0 1 2 3 P0

4 5 6 7 P1

8 9 10 11 P2

12 13 14 15 P3

C0 C1 C2 C3 P

0 0 1 1 XOR (0, 0,1, 1) = 0

0 1 0 0 XOR (0, 1,0,0) = 1

Block0 Block1 Block2 Block3 Parity

00 10 11 10 11

10 01 00 01 10

As you can see from the figure, the parity is computed for each bit of each block and the result placed in the parity block.

RAID-4 Analysis

Disk 0 Disk 1 Disk 2 Disk 3 Disk 4

0 1 2 3 P0

4 5 6 7 P1

8 9 10 11 P2

12 13 14 15 P3

Table 38.4: Full-stripe writes in RAID-4

C0 C1 C2 C3 P

0 0 1 1 XOR (0,0,1,1) = 0

Disk 0 Disk 1 Disk 2 Disk 3 Disk 4

0 1 2 3 P0

4 5 6 7 +P1

8 9 10 11 P2

12 13 14 15 +P3

Table 38.5: Example: Writes To 4, 13, and Respective Parity Blocks

RAID Level 5: Rotating Parity

Disk 0 Disk 1 Disk 2 Disk 3 Disk 4

0 1 2 3 P0

5 6 7 P1 4

10 11 P2 8 9

15 P3 12 13 14

P4 16 17 18 19

Table 38.6: RAID-5With Rotated Parity

As you can see, the parity block for each stripe is now rotated across the disks, in order to remove the parity-disk bottleneck for RAID-4.

RAID-5 Analysis

RAID-0 RAID-1 RAID-4 RAID-5

Capacity N N/2 N − 1 N − 1

Reliability 0 1(for sure) 1 1

N/2 (if lucky)

Throughput

Sequential Read N · S (N/2) · S (N − 1) · S (N − 1) · S

Sequential Write N · S (N/2) · S (N − 1) · S (N − 1) · S

Random Read N · R N · R (N − 1) · R N · R

Random Write N · R (N/2) · R 1/2· R N/4 R

Latency

Read D D D D

Write D D 2D 2D

Table 38.7: RAID Capacity, Reliability, and Performance

Raid level 6

For raid 6 array with n disks,

Ø Data is divided into n-2 strips

Ø Two pieces of parity information are collected over the n-2 strips(using a Reed-Solomon code)

Ø The parity information is collected over the disk

Raid Advantage

Ø RAID provides an environment of highly reliable, fault tolerant disk drive sub-systems

Ø RAID adds life to disk drives as the controller manages the I/O load equally amongst all the drives in the Array reducing the risk of “single point-of-failure”

Ø A “successful” RAID environment includes reliable robust disk drives

Ø Each RAID environment will include multiple disk drives

Ø Mylex PCI RAID controllers can attach as many as 45 drives per RAID controller, up to 16 controllers per system for an astonishing -- 720 disk drives per system configuration

Ø Mylex external RAID controllers can attach as many as 90 drives per storage subsystem and can reside as part of a SAN (Storage Area

Ø Network)

Ø Capacities range from terabytes to petabytes!

REFERENCE:

PPT+BOOK (Redundant Arrays of Inexpensive Disks RAIDs)

Stripes data at a block level across several

• Allows recovery from the failure of any of the disks

• Performance is very good for reads

• Writes require that parity data be updated each time. Slows small

butlarge writes are fairly fast

Stripes data at a block level across several drives, with parity

1 parity disk

• Expense of computing and writing parity

• Need to include a dedicated parity hardware

Gibson and Katz at the Ut a block level across several drives, with parity

1 parity disk

• Expense of computing and writing parity

• Need to include a dedicated parity hardware

Gibson and Katz at the U