The distributed program reliability analysis on star topologies

Abstract

A distributed computing system consists of processing elements, communication links, memory units, data files, and programs. These resources are interconnected via a communication network and controlled by a distributed operating system. The distributed program reliability in a distributed computing system is the probability that a program which runs on multiple processing elements and needs to retrieve data files from other processing elements will be executed successfully. This reliability varies according to (1) the topology of the distributed computing system, (2) the reliability of the communication edges, (3) the data files and programs distribution among processing elements, and (4) the data files required to execute a program. In this paper, we show that computing the distributed program reliability on the star distributed computing systems is NP-hard. We also develop an efficiently solvable case to compute distributed program reliability when some additional file distribution is restricted on the star topology. Scope and purpose Recent advances in VLSI circuitry have a tremendous impact on the price-performance revolution in microelectronics. This development has led to an increased use of workstations connected in the form of a powerful distributed computing system. Potential benefits offered by such distributed computing systems include better cost performance, enhanced fault tolerance, increased system throughput, and efficient sharing of resources. Distributed program reliability is an important measure that should be examined for designing a high fault-tolerance distributed computing system. This reliability varies according to (1) the topology of the distributed computing system, (2) the reliability of the communication edges, (3) the data files and programs distribution among processing elements, and (4) the data files required to execute a program. This article is concerned with the analysis of distributed program reliability on star distributed computing systems.