Distributed algorithm

About: Distributed algorithm is a research topic. Over the lifetime, 20416 publications have been published within this topic receiving 548109 citations.

Achieving Distributed Termination without Freezing

Abstract: An efficient algorithm for achieving distributed termination without introducing new communicaton channels and without delaying the basic computations ("freezing") is presented. The algorithm is related to the methodology of designing distributed programs where the programmer is relieved from the problem of distributed termination. An informal correctness proof and complexity analysis are included.

Dual coordinate step methods for linear network flow problems

Abstract: We review a class of recently-proposed linear-cost network flow methods which are amenable to parallel implementation. All the methods in the class use the notion of c-complementary slackness, and most do not explicitly manipulate any "global" objects such as paths, trees, or cuts. Interestingly, these methods have also stimulated a large number of new serial computational complexity results. We develop the basic theory of these methods and present two specific methods, the E-relaxation algorithm for the minimum-cost flow problem, and the auction algorithm for assignment problem. We show how to implement these methods with serial complexities of O(N 3 log NC) and O(NA log NC), respectively. We also discuss practical implementation issues and computational experience to date. Finally, we show how to implement e-relaxation in a completely asynchronous, "chaotic" environment in which some processors compute faster than others, some processors communicate faster than others, and there can be arbitrarily large communication delays.

The broadcast comparison model for on-line fault diagnosis in multicomputer systems: theory and implementation

Abstract: This paper describes a new comparison-based model for distributed fault diagnosis in multicomputer systems with a weak reliable broadcast capability. The classical problems of diagnosability and diagnosis are both considered under this broadcast comparison model. A characterization of diagnosable systems is given, which leads to a polynomial-time diagnosability algorithm. A polynomial-time diagnosis algorithm for t-diagnosable systems is also given. A variation of this algorithm, which allows dynamic fault occurrence and incomplete diagnostic information, has been implemented in the COmmon Spaceborne Multicomputer Operating System (COSMOS). Results produced using a simulator for the JPL MAX multicomputer system running COSMOS show that the algorithm diagnoses all fault situations with low latency and very little overhead. These simulations demonstrate the practicality of the proposed diagnosis model and algorithm for multicomputer systems having weak reliable broadcast. This includes systems with fault-tolerant hardware for broadcast, as well as those where reliable broadcast is implemented in software.

Interval consensus: From quantized gossip to voting

Abstract: We design distributed and quantized average consensus algorithms on arbitrary connected networks. By construction, quantized algorithms cannot produce a real, analog average. Instead, our algorithm reaches consensus on the quantized interval that contains the average. We prove that this consensus in reached in finite time almost surely. As a byproduct of this convergence result, we show that the majority voting problem is solvable with only 2 bits of memory per agent.

Cross-Layer Optimization of Correlated Data Gathering in Wireless Sensor Networks

Abstract: We consider the problem of gathering correlated sensor data by a single sink node in a wireless sensor network. We assume that the sensor nodes are energy constrained and design efficient distributed protocols to maximize the network lifetime. Many existing approaches focus on optimizing the routing layer only, but in fact the routing strategy is often coupled with power control in the physical layer and link access in the MAC layer. This paper represents a first effort on network lifetime maximization that jointly considers the three layers. We first assume that link access probabilities are known and consider the joint optimal design of power control and routing. We show that the formulated optimization problem is convex and propose a distributed algorithm, JRPA, for the solution. We also discuss the convergence of JRPA. When the optimal link access probabilities are unknown, as in many practical networks, we generalize the problem formulation to encompass all the three layers of routing, power control, and link-layer random access. In this case, the problem cannot be converted into a convex optimization problem, but there exists a duality gap when the Lagrangian dual method is employed. We propose an efficient heuristic algorithm, JRPRA, to solve the general problem, and show through numerical experiments that it can significantly narrow the gap between the computed and optimal solutions. Moreover, even without a priori knowledge of the best link access probabilities predetermined for JRPA, JRPRA achieves extremely competitive performance with JRPA. Beyond the metric of network lifetime, we also discuss how to solve the problem of correlated data gathering under general utility functions. Numerical results are provided to show the convergence of the algorithms and their advantages over existing solutions.