On-line routing of virtual circuits with applications to load balancing and machine scheduling
Journal of the ACM (JACM)
The MOSIX multicomputer operating system for high performance cluster computing
Future Generation Computer Systems - Special issue on HPCN '97
Competitive routing of virtual circuits with unknown duration
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Developments from a June 1996 seminar on Online algorithms: the state of the art
Load Balancing for Response Time
ESA '95 Proceedings of the Third Annual European Symposium on Algorithms
Performance comparisons of load balancing algorithms for I/O-intensive workloads on clusters
Journal of Network and Computer Applications
Dynamic load balancing for I/O-intensive applications on clusters
ACM Transactions on Storage (TOS)
Initiating load balancing operations
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
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Abstract: Most implementations of a Computing Cluster (CC) use greedy-based heuristics to perform load balancing. In some cases, this is in contrast to theoretical results about the performance of on-line load balancing algorithms. In this paper we define the home model in order to better reflect the architecture of a CC. In this new theoretical model, we assume a realistic cluster structure in which every job has a "home" machine which it prefers to be executed on, e.g. due to I/O considerations or because it was created there. We develop several on-line algorithms for load balancing in this model. We first provide a theoretical worst-case analysis, showing that our algorithms achieve better competitive ratios and perform less reassignments than algorithms for the unrelated machines model, which is the best existing theoretical model to describe such clusters. We then present an empirical average-case performance analysis by means of simulations. We show that the performance of our algorithms is consistently better than that of several existing load balancing methods, e.g. the greedy and the opportunity cost methods, especially in a dynamic and changing CC environment.