Asynchronous neighborhood task synchronization

Faults are likely to occur in distributed systems. The motivation for designing self-stabilizing system is to be able to automatically recover from a faulty state. As per Dijkstra\u27s definition, a system is self-stabilizing if it converges to a desired state from an arbitrary state in a finite number of steps. The paradigm of self-stabilization is considered to be the most unified approach to designing fault-tolerant systems. Any type of faults, e.g., transient, process crashes and restart, link failures and recoveries, and byzantine faults, can be handled by a self-stabilizing system; Many applications in distributed systems involve multiple phases. Solving these applications require some degree of synchronization of phases. In this thesis research, we introduce a new problem, called asynchronous neighborhood task synchronization ( NTS ). In this problem, processes execute infinite instances of tasks, where a task consists of a set of steps. There are several requirements for this problem. Simultaneous execution of steps by the neighbors is allowed only if the steps are different. Every neighborhood is synchronized in the sense that all neighboring processes execute the same instance of a task. Although the NTS problem is applicable in nonfaulty environments, it is more challenging to solve this problem considering various types of faults. In this research, we will present a self-stabilizing solution to the NTS problem. The proposed solution is space optimal, fault containing, fully localized, and fully distributed. One of the most desirable properties of our algorithm is that it works under any (including unfair) daemon. We will discuss various applications of the NTS problem

Self-Stabilization in the Distributed Systems of Finite State Machines

The notion of self-stabilization was first proposed by Dijkstra in 1974 in his classic paper. The paper defines a system as self-stabilizing if, starting at any, possibly illegitimate, state the system can automatically adjust itself to eventually converge to a legitimate state in finite amount of time and once in a legitimate state it will remain so unless it incurs a subsequent transient fault. Dijkstra limited his attention to a ring of finite-state machines and provided its solution for self-stabilization. In the years following his introduction, very few papers were published in this area. Once his proposal was recognized as a milestone in work on fault tolerance, the notion propagated among the researchers rapidly and many researchers in the distributed systems diverted their attention to it. The investigation and use of self-stabilization as an approach to fault-tolerant behavior under a model of transient failures for distributed systems is now undergoing a renaissance. A good number of works pertaining to self-stabilization in the distributed systems were proposed in the yesteryears most of which are very recent. This report surveys all previous works available in the literature of self-stabilizing systems

Self-stabilizing inter-domain policy routing

As the complexity of the networked systems increases, the likelihood of experiencing unanticipated faults grows. Self-stabilization is the most general technique to design fault tolerant systems. This paradigm was introduced by Dijkstra in 1974. A self-stabilizing system guarantees that starting from an arbitrary state, the system converges to a legal state in a finite number of steps and remains in a legal state until another fault occurs. Such a system after any unexpected perturbation eventually recovers without any outside intervention; The goal of this thesis research is to design a self-stabilizing Inter Domain Policy Routing Algorithm in order to make the policy routing procedure resistant to failures. We propose two algorithms. Our first algorithm sets up a path from a source to a destination, where the source and destination belong to different autonomous systems. It uses the Path Control Protocol (PCP). This algorithm can handle path failures, but cannot cope with message losses. Our second solution takes care of this problem by using the Control Message Transport Protocol (CMTP). (Abstract shortened by UMI.)

Self-stabilizing wormhole routing in hypercubes

Wormhole routing is an efficient technique used to communicate message packets between processors when they are not completely connected. To the best of our knowledge, this is the first attempt at designing a self-stabilizing wormhole routing algorithm for hypercubes. Our first algorithm handles all types of faults except for node/link failures. This algorithm achieves optimality in terms of routing path length by following only the preferred dimensions. In an n-dimensional hypercube, those dimensions in which source and destination address bits differ are called preferred dimensions. Our second algorithm handles topological changes. We propose an efficient scheme of rerouting flits in case of node/link failures. Similar to the first algorithm, this algorithm also tries to follow preferred dimensions if they are nonfaulty at the time of transmitting the flits. However, due to topological faults it is necessary to take non-preferred dimensions resulting in suboptimality of path selection. Formal proof of correctness for both solutions is given. (Abstract shortened by UMI.)

Self-Stabilization by Window Washing

A useful way to design simple and robust protocols is to make them self-stabilizing. We describe a new general technique for self-stabilization called window washing. We apply this technique to generalized sliding window protocols that work on a number of topologies. This results in simple, efficient, and self-stabilizing protocols. As far as we know, both windowwashingand generalized sliding window protocols are new ideas. Our protocols can be used for data links, reliable broadcast, and flow control