Dynamic load balancing and efficient load estimators for asynchronous iterative algorithms

Bahi, Jacques M.; Contassot-Vivier, Sylvain; Couturier, Raphaël

doi:10.1109/tpds.2005.45

Cited by 45 publications

(29 citation statements)

References 19 publications

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“…Baumgartner and Wah [50] and Casavant and Kuhl [2] propose algorithm related to the problem in load balancing in clusters. Lan et al [3] and Bahi et al [4] propose distributed load balancing policy, in which every node executes this policy autonomously. Moreover, the load balancing policy can be static or dynamic.…”

Section: Related Workmentioning

confidence: 99%

A dynamic file replication based on CPU load and consistency mechanism in a trusted distributed environment

Vardhan

Kushwaha

2017

Teh. vjesn.

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Original scientific paper An effort has been made to propose a CPU load based dynamic, cooperative, trust based, and secure file replication approach based along with consistency among file replicas for distributed environment. Simulation results consisting of 100 requesting nodes, three file servers and file size ranging from 677 KB to 11 MB establishes that, when the CPU load is taken into consideration, the average decrease in file request completion time is about 22,04 ÷ 24,81 % thus optimizing the CPU load and minimizing the file request completion time. The CPU load decreases by 4,25 ÷ 5,58 %. Results show that, the average write latency with proposed mechanism decreases by 6,12 % as compared to Spinnaker writes and the average read latency is 3 times better than Cassandra Quorum Read (CQR). The proposed partial update propagation for maintaining file consistency stands to gain up to 69,67 % in terms of time required to update stale replicas. Thus the integrity of files and behaviour of the requesting nodes and file servers is guaranteed within even lesser time. Finally, a relationship between the formal aspects of simple security model and secure reliable CPU load based file replication model is established through process algebra. Keywords Dinamička replikacija datoteke zasnovana na mehanizmu opterećenosti i konzistencije CPU u pouzdanom distribuiranom okruženjuIzvorni znanstveni članak Pokušalo se predložiti dinamički, kooperativni, pouzdani i sigurni pristup replikaciji datoteke utemeljen na opterećenosti CPU uz konzistenciju među replikama datoteke za distribuirano okruženje. Rezultati simulacije koja se sastoji od 100 potrebnih čvorova, tri servera datoteke i datoteke veličine od 677 KB to 11 MB pokazuju da kada se uzme u obzir opterećenje CPU, prosječno smanjenje vremena potrebnog za popunjavanje datoteke je oko 22,04 ÷ 24,81 %. Tako se optimiziralo opterećenje CPU i smanjilo traženo vrijeme popunjavanja datoteke. Opterećenje CPU smanjuje se za 4,25 ÷ 5,58 %. Rezultati pokazuju da se prosječno kašnjenje upisa (write latency) s predloženim mehanizmom smanjuje za 6,12 % u usporedbi sa Spinnakerovim, a prosječno vrijeme čekanja čitanja (read latency) je 3 puta bolje od Cassandra Quorum Read (CQR). Predložena parcijalna propagacija ažuriranja za održavanje konzistencije datoteke povećava se do 69,67 % u odnosu na vrijeme potrebno za ažuriranje zastarjelih replika. Tako je integritet datoteka i ponašanje zahtijevanih čvorova i servera datoteke zagarantirano za čak manje vremena. Konačno, kroz algebra postupak uspostavljen je odnos između formalnih aspekata jednostavnog modela sigurnosti i sigurnog pouzdanog modela replikacije datoteke zasnovanog na sigurnom pouzdanom opterećenju datoteke.

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Section: Related Workmentioning

confidence: 99%

A dynamic file replication based on CPU load and consistency mechanism in a trusted distributed environment

Vardhan

Kushwaha

2017

Teh. vjesn.

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“…Many load-balancing policies have been proposed, aiming at different optimizations, spanning from equalizing processor load [37] to managing memory pools [13,32], to specific optimizations for iterative algorithms [4]. Often load-balancing policies consider web server systems as a target [11,26], where one of the most important result is to bound the maximum response time that the clients are exposed to [19].…”

Section: Related Workmentioning

confidence: 99%

Control-theoretical load-balancing for cloud applications with brownout

Dürango

Dellkrantz

Maggio

et al. 2014

53rd IEEE Conference on Decision and Control

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Abstract-Cloud applications are often subject to unexpected events like flash crowds and hardware failures. Without a predictable behaviour, users may abandon an unresponsive application. This problem has been partially solved on two separate fronts: first, by adding a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience, and, second, by introducing replicas -copies of the applications having the same functionalities -for redundancy and adding a load-balancer to direct incoming traffic.However, existing load-balancing strategies interfere with brownout self-adaptivity. Load-balancers are often based on response times, that are already controlled by the self-adaptive features of the application, hence they are not a good indicator of how well a replica is performing.In this paper, we present novel load-balancing strategies, specifically designed to support brownout applications. They base their decision not on response time, but on user experience degradation. We implemented our strategies in a selfadaptive application simulator, together with some state-of-theart solutions. Results obtained in multiple scenarios show that the proposed strategies bring significant improvements when compared to the state-of-the-art ones.

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“…These strategies are restricted to applications with pre-determined workload and cannot be applied to such iterative routines as adaptive mesh refinement [7], for which the amount of computation data grows unpredictably. Dynamic algorithms [8,9,10,11,12] do not require a priori information and can be used with a wider class of parallel applications. In addition, dynamic algorithms can be deployed on non-dedicated platforms.…”

Section: Related Workmentioning

confidence: 99%

“…In non-centralised algorithms [11,12], load is migrated locally between neighbouring processors, while in centralised ones [4,5,6,8,9,10], load is distributed based on global load information. Non-centralized algorithms are slower to converge.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Load Balancing of Parallel Computational Iterative Routines on Platforms with Memory Heterogeneity

Clarke

Lastovetsky

Рычков

2011

Euro-Par 2010 Parallel Processing Workshops

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Abstract. Traditional load balancing algorithms for data-intensive iterative routines can successfully load balance relatively small problems. We demonstrate that they may fail for large problem sizes on computational clusters with memory heterogeneity. Traditional algorithms use too simplistic models of processors' performance which cannot reflect many aspects of heterogeneity. This paper presents a new dynamic load balancing algorithm based on the advanced functional performance model. The model consists of speed functions of problem size, which are built adaptively from a history of load measurements. Experimental results demonstrate that our algorithm can successfully balance data-intensive iterative routines on parallel platforms with memory heterogeneity.

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Dynamic load balancing and efficient load estimators for asynchronous iterative algorithms

Cited by 45 publications

References 19 publications

A dynamic file replication based on CPU load and consistency mechanism in a trusted distributed environment

A dynamic file replication based on CPU load and consistency mechanism in a trusted distributed environment

Control-theoretical load-balancing for cloud applications with brownout

Dynamic Load Balancing of Parallel Computational Iterative Routines on Platforms with Memory Heterogeneity

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