The load rebalancing problem

Aggarwal, Gagan; Motwani, Rajeev; An, Zhijie

doi:10.1016/j.jalgor.2004.10.002

Cited by 33 publications

(31 citation statements)

References 14 publications

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“…It is commonly agreed that reallocation imposes extra communication cost in the network, and so, it should be kept to a reasonable amount. For using reallocation to balance a single criterion, Aggrawal et al gave an O(N log N )-time algorithm for minimizing the maximum load in a set of homogeneous (identical) servers with the allowance to reallocate at most k objects [1]. The worst case ratio is bounded by 1.5, but the high time complexity makes it run as an offline algorithm.…”

Section: A Related Workmentioning

confidence: 99%

Rotating Escalators upon Deletions for Improving Online Bicriteria Load Balancing

Tse

2012

2012 12th International Symposium on Pervasive Systems, Algorithms and Networks

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We study the online load balancing problem for two independent criteria upon deletion in this paper. For convenience, we choose a system of distributed homogeneous file servers located in a cluster as the scenario, and propose a solution for balancing their loads and required storage spaces for any sequence of document placements and deletions. The upper bounds of load and storage space are extremely close to the best existing online result for sole placements which do not allow reallocation and replication.Upon deleting a document from a server, other servers experience relative increases in both criteria. However, our upper bound result can tolerate a certain number of deletions. Based on this buffer, for each criterion, we construct an escalator to model the numbers of deletions that the servers can withstand before violating the upper bound. The escalator moves down upon deletion, and the servers of the lowest group, which have the least tolerance, will go through reallocation and rotate back to the highest point. As long as the escalators are valid, the upper bounds are intact.

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Section: A Related Workmentioning

confidence: 99%

Rotating Escalators upon Deletions for Improving Online Bicriteria Load Balancing

Tse

2012

2012 12th International Symposium on Pervasive Systems, Algorithms and Networks

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“…Aggarwal et al [15] first addressed the problem of makespan minimization with job migration. Given an assignment of a schedule, then migrate the jobs within a budget (at most k jobs) to minimize the makespan.…”

Section: A Related Workmentioning

confidence: 99%

Online Scheduling with Migration Cost

Yang

2012

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops &Amp; PhD Forum

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In this paper, we consider a new variation of the classical online scheduling problem. In our model, an online scheduler is allowed to migrate the assigned jobs to different machines. Live migration is a powerful tool for load balancing. However, migration will incur additional cost in the destination machines. In this paper, we study the scheduling problem with migration cost model. Suppose that a job with processing time p which is already scheduled on the machine A is removed and transferred to the machine B, the load of the machine A will decrease p, but the load of the machine B will increase (1 + r)p, where 0 ≤ r ≤ 1 is a constant and it is called the migration factor.First, we propose an approximation algorithm for arbitrary machines. Then we give an improved algorithm for the case of two machines. Both algorithms are better than list scheduling algorithm [2] if the migration factor is smaller than a certain value. Finally, we implement our algorithms both in real data and random data. The experimental results indicate that the performances of algorithms are very close to the optimal algorithm.

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“…1 However, in many systems, however, tasks cannot be fragmented, or if they can, there is a cost for fragmenting them. Previous algorithmic approaches for task scheduling across machines [4], [6]- [8], for provisioning server loads in [9], and for traffic engineering using interior gateway routing protocols [10] do not consider fragmentation costs in their models. The optimization approaches in [11]- [13] and the performance study in [14] also differ from our work in this same fundamental aspect.…”

Section: Related Workmentioning

confidence: 99%

Impact of Load Sharing on Provisioning Services with Consistency Requirements

Villela

Misra

Rubenstein

et al. 2006

Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications

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Providers of services such as online auctions must provision servers to respond quickly to users' requests. Assigning each service to its own set of servers can result in some servers being overloaded while others remain underloaded. In contrast, load sharing spreads all services across the sets of servers, allowing each request to each be serviced from a choice of multiple servers, relieving the busiest servers. Sharing arbitrarily across servers, however, can be costly because of the need to maintain consistency of the service across these servers. In this work we model servicing systems with consistency requirements and analyze the impact of load sharing. Our analysis of greedy algorithms provides upper bounds of the response times, and shows that greedy algorithms can reduce the busiest server's intensity to be very close to the average service intensity -a near-optimal result. We also reveal a surprising result that, when servers' average loads are equal but fluctuate over time, the average response time can be reduced by sharing load.

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The load rebalancing problem

Cited by 33 publications

References 14 publications

Rotating Escalators upon Deletions for Improving Online Bicriteria Load Balancing

Rotating Escalators upon Deletions for Improving Online Bicriteria Load Balancing

Online Scheduling with Migration Cost

Impact of Load Sharing on Provisioning Services with Consistency Requirements

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