Application of the Diffusion Approximation to Queueing Networks I: Equilibrium Queue Distributions
Journal of the ACM (JACM)
Ethernet: distributed packet switching for local computer networks
Communications of the ACM
Operating Systems Theory
A Comparative Study of Some Two-Processor Organizations
IEEE Transactions on Computers
Assignment of Tasks in a Distributed Processor System with Limited Memory
IEEE Transactions on Computers
Models for Dynamic Load Balancing in a Heterogeneous Multiple Processor System
IEEE Transactions on Computers
Multiprocessor Scheduling with the Aid of Network Flow Algorithms
IEEE Transactions on Software Engineering
Adaptive Routing Using a Virtual Waiting Time Technique
IEEE Transactions on Software Engineering
Load Balancing in Distributed Systems
IEEE Transactions on Software Engineering
Critical Load Factors in Two-Processor Distributed Systems
IEEE Transactions on Software Engineering
Hypercube experiments with Joyce
ACM SIGPLAN Notices
Heuristic methods for dynamic load balancing in a message-passing supercomputer
Proceedings of the 1990 ACM/IEEE conference on Supercomputing
Analytic Models of Adaptive Load Sharing Schemes in Distributed Real-Time Systems
IEEE Transactions on Parallel and Distributed Systems
Design and Evaluation of Effective Load Sharing in Distributed Real-Time Systems
IEEE Transactions on Parallel and Distributed Systems
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In order to be able to take full advantage of a distributed computing facility it is important not only to distribute the hardware but also to distribute the control of these resources. However, distributed control is very different from centralized control since at any time, several processes or several controllers may observe different and inconsistent views of the global system state. The task of scheduling jobs in a distributed system must also be done Without full knowledge of the system state. In this correspondence we define a totally new distributed scheduling algorithm LP (linear predictive). scheduling, which not only implements distributed control of task scheduling but is also able to adapt itself to workload fluctuations. Using a general-purpose distributed system simulator we have shown the performance rnitince advantages of this new algorithm.