Operating systems: design and implementation
Operating systems: design and implementation
A survey of process migration mechanisms
ACM SIGOPS Operating Systems Review
GAMMON: A Load Balancing Strategy for Local Computer Systems with Multiaccess Networks
IEEE Transactions on Computers
PVM: a framework for parallel distributed computing
Concurrency: Practice and Experience
Semi-Distributed Load Balancing for Massively Parallel Multicomputer Systems
IEEE Transactions on Software Engineering
Estimating Capacity for Sharing in a Privately Owned Workstation Environment
IEEE Transactions on Software Engineering
Network-based concurrent computing on the PVM system
Concurrency: Practice and Experience
Portable Programs for Parallel Processors
Portable Programs for Parallel Processors
Adaptive load migration systems for PVM
Proceedings of the 1994 ACM/IEEE conference on Supercomputing
Scalable, Adaptive Load Sharing for Distributed Systems
IEEE Parallel & Distributed Technology: Systems & Technology
Efficient Task Migration Algorithm for Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Strategies for Dynamic Load Balancing on Highly Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
A taxonomy of scheduling in general-purpose distributed computing systems
IEEE Transactions on Software Engineering
MPVM: A Migration Transparent Version of PVM
MPVM: A Migration Transparent Version of PVM
QoS guided min-min heuristic for grid task scheduling
Journal of Computer Science and Technology - Grid computing
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The wide availability of workstation networks and the rapid evolution of workstation technology is a motivation for investigating methods of harnessing the full power of such systems. Individual workstations are not usually effectively utilized by their owners. Owners may be willing to lend the processing power of their workstations if used in an unobtrusive way. The ability to effectively borrow the idle cycles of the workstations in a network and efficiently schedule parallel application programs concurrently onto those idle workstations is the topic of this paper. In this paper, we present a distributed scheduling algorithm that will track the available workstations, i.e. workstations not used by their owners, in networks and act upon those workstations by scheduling processes of parallel applications onto them. Our scheduling objectives are minimizing the average Turn Around Time (TAT) of the scheduled applications and maintaining fairness among scheduled applications by granting each application all the resources it requires. Moreover, scheduling solutions are narrowed to those that produce a responsive and scalable scheduling algorithm.