Using dual approximation algorithms for scheduling problems theoretical and practical results
Journal of the ACM (JACM)
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)
Improved approximation schemes for scheduling unrelated parallel machines
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
A PTAS for the multiple knapsack problem
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Path-independent load balancing with unreliable machines
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
ICA3PP'10 Proceedings of the 10th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
On the value of job migration in online makespan minimization
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
Recent advances for a classical scheduling problem
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part II
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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 the makespan, which is the load on the heaviest loaded processor. Since in most real world scenarios the load is a dynamic measure, the initial assignment may not remain optimal over 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 the weighted version of this problem where there is an arbitrary cost associated with each job's relocation. The problem is NP-hard and hence, we focus on approximation algorithms. We construct an algorithm which achieves a 1.5-approximation, with near linear running time. We also show that the problem has a PTAS, thereby resolving the complexity issue. Finally, we investigate the approximability of several extensions of the load rebalancing model.