One measure of the usefulness of a general-purpose distributed computing system is the system's ability to provide a level of performance commensurate to the degree of multiplicity of resources present in the system. A taxonomy of approaches to the resource management problem is presented in an attempt to provide a common terminology and classification mechanism necessary in addressing this problem. The taxonomy, while presented and discussed in terms of distributed scheduling, is also applicable to most types of resource management. >

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A taxonomy of scheduling in general-purpose distributed computing systems

The term “peer-to-peer” (P2P) refers to a class of systems and applications that employ distributed resources to perform a critical function in a decentralized manner. With the pervasive deployment of computers, P2P is increasingly receiving attention in research, product development, and investment circles. This interest ranges from enthusiasm, through hype, to disbelief in its potential. Some of the benefits of a P2P approach include: improving scalability by avoiding dependency on centralized points; eliminating the need for costly infrastructure by enabling direct communication among clients; and enabling resource aggregation. This survey reviews the field of P2P systems and applications by summarizing the key concepts and giving an overview of the most important systems. Design and implementation issues of P2P systems are analyzed in general, and then revisited for each of the case studies described in Section 6. This survey will help people understand the potential benefits of P2P in the research community and industry. For people unfamiliar with the field it provides a general overview, as well as detailed case studies. It is also intended for users, developers, and information technologies maintaining systems, in particular comparison of P2P solutions with alternative architectures and

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Peer-to-Peer Computing

Technical report series

Dynamic load balancing strategies for minimizing the execution time of single applications running in parallel on multicomputer systems are discussed. Dynamic load balancing (DLB) is essential for the efficient use of highly parallel systems when solving non-uniform problems with unpredictable load estimates. With the evolution of more highly parallel systems, centralized DLB approaches which make use of a high degree of knowledge become less feasible due to the load balancing communication overhead. Five DLB strategies are presented which illustrate the tradeoff between 1) knowledge - the accuracy of each balancing decision, and 2) overhead - the amount of added processing and communication incurred by the balancing process. All five strategies have been implemented on an Inter iPSC/2 hypercube. >

Strategies for dynamic load balancing on highly parallel computers

Process migration is the act of transferring a process between two machines. It enables dynamic load distribution, fault resilience, eased system administration, and data access locality. Despite these goals and ongoing research efforts, migration has not achieved widespread use. With the increasing deployment of distributed systems in general, and distributed operating systems in particular, process migration is again receiving more attention in both research and product development. As high-performance facilities shift from supercomputers to networks of workstations, and with the ever-increasing role of the World Wide Web, we expect migration to play a more important role and eventually to be widely adopted.This survey reviews the field of process migration by summarizing the key concepts and giving an overview of the most important implementations. Design and implementation issues of process migration are analyzed in general, and then revisited for each of the case studies described: MOSIX, Sprite, Mach, and Load Sharing Facility. The benefits and drawbacks of process migration depend on the details of implementation and, therefore, this paper focuses on practical matters. This survey will help in understanding the potentials of process migration and why it has not caught on.

Process migration

An important part of a distributed system design is the choice of a load sharing or global scheduling strategy. A comprehensive literature survey on this topic is presented. We propose a taxonomy of load sharing algorithms that draws a basic dichotomy between source-initiative and server-initiative approaches. The taxonomy enables ten representative algorithms to be selected for performance evaluation. A performance metric called the Q-factor (quality of load sharing) is defined which summarizes both overall efficiency and fairness of an algorithm and allows algorithms to be ranked by performance. We then evaluate the algorithms using both mathematical and simulation techniques. The results of the study show that: i) the choice of load sharing algorithm is a critical design decision; ii) for the same level of scheduling information exchange, server-initiative has the potential of outperforming source-initiative algorithms (whether this potential is realized depends on factors such as communication overhead); iii) the Q-factor is a useful yardstick; iv) some algorithms, which have previously received little attention, e.g., multiserver cyclic service, may provide effective solutions.

Yung-Terng Wang

Papers

Load Sharing in Distributed Systems