Load sharing in soft real-time distributed computer systems
IEEE Transactions on Computers - Special Issue on Real-Time Systems
The limited performance benefits of migrating active processes for load sharing
SIGMETRICS '88 Proceedings of the 1988 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Analysis of task migration in shared-memory multiprocessor scheduling
SIGMETRICS '91 Proceedings of the 1991 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Evaluation of Load Sharing in HARTS with Consideration of Its Communication Activities
IEEE Transactions on Parallel and Distributed Systems
A simple dynamic load balancing algorithm for homogeneous distributed systems
CSC '88 Proceedings of the 1988 ACM sixteenth annual conference on Computer science
Analytic Models of Adaptive Load Sharing Schemes in Distributed Real-Time Systems
IEEE Transactions on Parallel and Distributed Systems
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Load balancing policies in distributed systems divide jobs into two classes; those processed at their of origination (local jobs) and those processed at some other site in the system after being transfered through a communication network (remote jobs). This paper considers a class of decentralized load balancing policies that use a threshold on the local job queue length at each host in making decisions for remote processing. They differ from each other according to how they assign priorities to each of these job classes, ranging from one providing favorable treatment to local jobs to one providing favorable treatment to remote jobs. Under each policy, the optimal load balancing problem is formulated as an optimization problem with respect to the threshold parameter. The optimal threshold is obtained numerically using matrix-geometric formulation and an iteration method. Last, we consider the effects that the job arrival process can have on performance. One expects that load balancing for systems operating in an environment of bursty job arrivals should be more beneficial than for an environment with random job arrivals. This fact is observed through numerical examples.