Optimal static load balancing in distributed computer systems
Journal of the ACM (JACM)
Computer networks
An Algorithm for Optimal Static Load Balancing in Distributed Computer Systems
IEEE Transactions on Computers
Computer Communications Network Design and Analysis
Computer Communications Network Design and Analysis
Mathematical Optimization and Economic Theory
Mathematical Optimization and Economic Theory
A General Model for Optimal Static Load Balancing in Star Network Configurations
Performance '84 Proceedings of the Tenth International Symposium on Computer Performance Modelling, Measurement and Evaluation
Load Balancing Problems for Multiclass Jobs in Distributed/Parallel Computer Systems
IEEE Transactions on Computers
Load Balancing in Distributed Systems: An Approach Using Cooperative Games
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Cooperative load balancing for a network of heterogeneous computers
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Game-theoretic static load balancing for distributed systems
Journal of Parallel and Distributed Computing
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
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We study the static load balancing problem in a distributed computer system with thetree hierarchy configuration. It is formulated as a nonlinear optimization problem. Afterstudying the conditions that the solution to the optimization problem of the tree hierarchynetwork satisfies, we demonstrate that the special structure of the optimization problemleads to an interesting decomposition technique. A new effective decomposition algorithm to solve the optimization problem is presented. The proposed algorithm Is compared with two other well known algorithms: the Flow Deviation (FD) algorithm and the Dafermos-Sparrow (D-S) algorithm. It is shown that the amounts of the storage required for the proposed algorithm and the FD algorithm are O(n) for load balancing of an n-node system. However, the amount of the storage required for the D-S algorithm is O(n log(n)). By using numerical experiments, we show that both the proposed algorithm and the D-S algorithm have much faster convergence in terms of central processing unit(CPU) time than the FD algorithm.