Information policies for load balancing on heterogeneous systems

Beltrán, Marta; Bosque, José Luis

doi:10.1109/ccgrid.2005.1558666

Cited by 7 publications

(9 citation statements)

References 21 publications

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“…Table VII and Figure 6 summarizes the information efficiency observed by SLB, RLB, HSRLB, HLBWSR, MELISA and LBA for the resource Set I and II with number of jobs fixed to 1000 and 3000 respectively. As can be seen, MELISA and LBA are outperforming their peers for all the cases for small scale system indicating that periodic information policies works best for small scale system (in this case seven resources) as pointed out in [20]. It is to be noted that the communication complexity of MELISA and LBA in terms of messages communicated is quadratic being O(V 2 ) while that of RIE being linear with O(V).…”

Section: Simulation Studymentioning

confidence: 53%

“…The problem related to redistribution of load of the system among its nodes is defined in [4,6,[10][11][12][13][14][15] describing the load-distributing algorithms based on SLB, RLB and diffusion-based approaches. It has been stated in [4,6,20] that dynamic load balancing algorithms can be decomposed in three rules. It has been stated in [4,6,20] that dynamic load balancing algorithms can be decomposed in three rules.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, number of messages exchanged is also dependent on the periodic time T s [20]. It is evidently clear that as the number of nodes in the system increases, number of messages broadcasted also increases.…”

Section: Random Information Exchangementioning

confidence: 99%

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An adaptive threshold based hybrid load balancing scheme with sender and receiver initiated approach using random information exchange

Alam

Raza

2016

Concurrency and Computation

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The primary objective of load balancing for distributed systems is to minimize the job execution time while maximizing the resource utilization. Load balancing on decentralized systems need effective information exchange policy so that with minimum amount of communication the nodes have up to date information about other nodes in the system. Periodic, event-based and on-demand information exchange are some important policies used for the same. All these approaches involve a lot of overhead and even sometime leading toward obsolete data with the nodes if there is a delay in the updation. This work presents an adaptive threshold-based hybrid load balancing scheme with sender and receiver initiated approach (HLBWSR) using random information exchange (RIE). RIE ensures that the information is exchanged in such a way that each node in the system has up-to-date state of the other nodes with much reduced communication overhead. Further, the adaptive threshold ensures that almost an average numbers of jobs are executed by all the nodes in the system. The study of the effect of the use of RIE on sender initiated, receiver initiated and hybrid of sender and receiver initiated load balancing approach establishes the superior performance of HLBWSR among its RIE-based peers. A comparative analysis of HLBWSR, with periodic information exchange strategy, modified estimated load information scheduling algorithm and load balancing on arrival reveals its effectiveness under various test conditions. allocation and execution by transferring tasks from the heavily loaded to the lightly loaded nodes with the aim of improving the performance of the system. A typical load balancing algorithm is defined by three inherent policies [4-6]: Information policyIt deals with the amount of load information that is required by the job placement decision-makers for efficient job transfer. Transfer policyThe current load of the host and the size of the job under consideration determine the conditions under which the job should be transferred from heavily loaded node to lightly loaded node. Placement policyThe processing element with the least number of jobs and closest to the sender node is the best recipient. The affinity for processing element to receive job is the deciding factor during job placement.Load balancing algorithms are broadly characterized as static and dynamic. Static algorithms make use of prior information for load balancing while dynamic load balancing algorithms use runtime system-state information to make load balancing decisions. Dynamic algorithms have the potential to outperform static algorithms as they make use of system-state information during the runtime to enhance the quality of their decisions. However, dynamic algorithms incur more overhead than their static counterparts as they have to collect, store, and analyze state information. This overhead can be overcome if reduction in the response time incurred because of the redistribution outperforms the overhead [3,4,6].According to the degree of centralization, load sch...

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Section: Simulation Studymentioning

confidence: 53%

Section: Related Workmentioning

confidence: 99%

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An adaptive threshold based hybrid load balancing scheme with sender and receiver initiated approach using random information exchange

Alam

Raza

2016

Concurrency and Computation

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“…Thus, obtaining real-time global information from sites is costly (Patel and Darlington, 2006). Information exchange methods can be classified into three categories: periodic, on demand, and event-driven (Beltran and Bosque, 2005). In the first category, information is available to scheduler every specified time intervals.…”

Section: Introductionmentioning

confidence: 99%

Communication cost effective scheduling policies of nonclairvoyant jobs with load balancing in a grid

Zikos

Karatza

2009

Journal of Systems and Software

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“…In Beltran and Bosque [13], information exchange methods are classified into three categories: periodic, on demand, and event-driven. In the first category, each node periodically broadcasts its state information throughout the system.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Load Balancing and Pricing in Grid Computing with Communication Delay

2008

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Due to the emergence of Grid computing over the Internet, there is presently a need for dynamic load balancing algorithms which take into account the characteristics of Grid computing environments. In this paper, we consider a Grid architecture where computers belong to dispersed administrative domains or groups which are connected with heterogeneous communication bandwidths. We address the problem of determining which group an arriving job should be allocated to and how its load can be distributed among computers in the group to optimize the performance. We propose algorithms which guarantee finding a load distribution over computers in a group that leads to the minimum response time or computational cost. We then study the effect of pricing on load distribution by considering a simple pricing function. We develop three fully distributed algorithms to decide which group the load should be allocated to, taking into account the communication cost among groups. These algorithms use different information exchange methods and a resource estimation technique to improve the accuracy of load balancing. We conducted extensive simulations to evaluate the performance of the proposed algorithms and strategies.

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Information policies for load balancing on heterogeneous systems

Cited by 7 publications

References 21 publications

An adaptive threshold based hybrid load balancing scheme with sender and receiver initiated approach using random information exchange

An adaptive threshold based hybrid load balancing scheme with sender and receiver initiated approach using random information exchange

Communication cost effective scheduling policies of nonclairvoyant jobs with load balancing in a grid

Dynamic Load Balancing and Pricing in Grid Computing with Communication Delay

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