Lecture

Redundancy and Fault Tolerance

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In course

CS-522: Principles of computer systems

This advanced graduate course teaches the key design principles underlying successful computer and communication systems, and shows how to solve real problems with ideas, techniques, and algorithms from operating systems, networks, databases, programming l ...

Description

This lecture delves into the concepts of redundancy and fault tolerance, essential for constructing dependable systems. The instructor explains how redundancy complements modularity to increase dependability, defining terms like fault, error, and failure. The lecture covers various fault tolerance techniques, such as error correction codes and failover mechanisms, emphasizing the importance of fault models in system design. The instructor also discusses the significance of graceful degradation and the use of leases to manage resources effectively. Additionally, the lecture explores the concept of software rejuvenation as a preventive maintenance strategy to reduce the probability of failures. Through examples and theoretical designs, the lecture provides insights into building dependable systems with efficient recovery mechanisms.

Instructor

George Candea

George Candea heads the Dependable Systems Lab, where he develops techniques and abstractions for building efficient and trustworthy computer systems. His current work focuses on making performance and energy programmable, i.e., providing first-class abstractions to capture a system’s performance and energy behavior (as interfaces do for functionality) and to use them dependably to design, code, and operate efficient systems.In the recent past, George also served as CEO and later Chief Scientist of Cyberhav

Official source

Related concepts (8)

Fault tolerance

Fault tolerance is the property that enables a system to continue operating properly in the event of the failure of one or more faults within some of its components. If its operating quality decreases at all, the decrease is proportional to the severity of the failure, as compared to a naively designed system, in which even a small failure can cause total breakdown. Fault tolerance is particularly sought after in high-availability, mission-critical, or even life-critical systems.

Error correction code

In computing, telecommunication, information theory, and coding theory, forward error correction (FEC) or channel coding is a technique used for controlling errors in data transmission over unreliable or noisy communication channels. The central idea is that the sender encodes the message in a redundant way, most often by using an error correction code or error correcting code (ECC). The redundancy allows the receiver not only to detect errors that may occur anywhere in the message, but often to correct a limited number of errors.

Error detection and correction

In information theory and coding theory with applications in computer science and telecommunication, error detection and correction (EDAC) or error control are techniques that enable reliable delivery of digital data over unreliable communication channels. Many communication channels are subject to channel noise, and thus errors may be introduced during transmission from the source to a receiver. Error detection techniques allow detecting such errors, while error correction enables reconstruction of the original data in many cases.

Concatenated error correction code

In coding theory, concatenated codes form a class of error-correcting codes that are derived by combining an inner code and an outer code. They were conceived in 1966 by Dave Forney as a solution to the problem of finding a code that has both exponentially decreasing error probability with increasing block length and polynomial-time decoding complexity. Concatenated codes became widely used in space communications in the 1970s.

Hamming code

In computer science and telecommunication, Hamming codes are a family of linear error-correcting codes. Hamming codes can detect one-bit and two-bit errors, or correct one-bit errors without detection of uncorrected errors. By contrast, the simple parity code cannot correct errors, and can detect only an odd number of bits in error. Hamming codes are perfect codes, that is, they achieve the highest possible rate for codes with their block length and minimum distance of three. Richard W.

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