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
Approximation algorithms for scheduling unrelated parallel machines
Mathematical Programming: Series A and B
A simple load balancing scheme for task allocation in parallel machines
SPAA '91 Proceedings of the third annual ACM symposium on Parallel algorithms and architectures
A brief survey of systems providing process or object migration facilities
ACM SIGOPS Operating Systems Review
An approximation algorithm for the generalized assignment problem
Mathematical Programming: Series A and B
Tight analyses of two local load balancing algorithms
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Exploiting process lifetime distributions for dynamic load balancing
ACM Transactions on Computer Systems (TOCS)
A PTAS for the multiple knapsack problem
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Locality aware dynamic load management for massively multiplayer games
Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming
Load balancing in dynamic structured peer-to-peer systems
Performance Evaluation - P2P computing systems
International Journal of High Performance Computing Applications
The Chameleon architecture for streaming DSP applications
EURASIP Journal on Embedded Systems
Automated dynamic redistribution of virtual operating systems under the Xen virtual machine monitor
PDCN'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: parallel and distributed computing and networks
Caching collaboration and cache allocation in peer-to-peer video systems
Multimedia Tools and Applications
HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
Search spaces for min-perturbation repair
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Regulating user arrivals at a mobile IP home agent
COMSNETS'10 Proceedings of the 2nd international conference on COMmunication systems and NETworks
Dynamic resource allocation of computer clusters with probabilistic workloads
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Applying process migration on a BSP-based LU decomposition application
VECPAR'10 Proceedings of the 9th international conference on High performance computing for computational science
Incremental placement of interactive perception applications
Proceedings of the 20th international symposium on High performance distributed computing
A Practical Architecture for an Anycast CDN
ACM Transactions on the Web (TWEB)
Decentralized proactive resource allocation for maximizing throughput of P2P Grid
Journal of Parallel and Distributed Computing
Improved algorithms for data migration
APPROX'06/RANDOM'06 Proceedings of the 9th international conference on Approximation Algorithms for Combinatorial Optimization Problems, and 10th international conference on Randomization and Computation
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In the classical load balancing or multiprocessor scheduling problem, we are given a sequence of jobs of varying sizes and are asked to assign each job to one of the m empty processors. A typical objective is to minimize makespan, the load on the heaviest loaded processor. Since in most real world scenarios the load is a dynamic measure, the initial assignment may be not remain optimal with time. Motivated by such considerations in a variety of systems, we formulate the problem of load rebalancing --- given a possibly suboptimal assignment of jobs to processors, relocate a set of the jobs so as to decrease the makespan. Specifically, the goal is to achieve the best possible makespan under the constraint that no more than k jobs are relocated. We also consider a generalization of this problem where there is an arbitrary cost function associated with each job relocation. Since the problem is clearly NP-hard, we focus on approximation algorithms. We construct a sophisticated algorithm which achieves a 1.5-approximation, with near linear running time. We also show that the problem has a PTAS, resolving the complexity issue. Finally, we investigate the approximability of several extensions of the rebalancing model.