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The Journal of Supercomputing
Published in: The Journal of Supercomputing 10/2019

05-06-2019

SLA-RALBA: cost-efficient and resource-aware load balancing algorithm for cloud computing

Authors: Altaf Hussain, Muhammad Aleem, Muhammad Azhar Iqbal, Muhammad Arshad Islam

Published in: The Journal of Supercomputing | Issue 10/2019

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Abstract

Recently, Service-level agreement (SLA) is deemed to be an integral aspect for on-demand provisioning of scalable resources on Cloud. SLA defines important constraints for instance guaranteed quality of service (QoS), pricing, fault-tolerant availability, security, and period of service. Currently, there is a dire need of SLA-based scheduling that improves resources utilization on Cloud. Scheduling with reduced execution time and cost may adversely affect resource utilization. To overcome this issue, we present a cost-efficient SLA-based load balancing scheduler, namely SLA-RALBA, for heterogeneous Cloud infrastructures. The proposed technique supports three levels of SLA opted by the Cloud users. The proposed novel technique incorporates the execution cost for the successful execution of users’ services to elevate the resource utilization on Cloud. The SLA-RALBA is simulated for performance analysis using the benchmark GoCJ and HCSP datasets. The performance results of the SLA-RALBA are compared with the existing schedulers, namely Execution-MCT, Profit-MCT, SLA-MCT, Execution-Min-Min, Profit-Min-Min, and SLA-Min-Min in terms of average resource utilization, execution time, and cost of the Cloud services. The obtained results reveal that SLA-RALBA provides an even trade-off between execution time and cost of the services by guaranteeing a drastic improvement in resource utilization on Cloud than existing algorithms.
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Literature
1.
Beloglazov A, Buyya R (2013) Managing overloaded hosts for dynamic consolidation of virtual machines in cloud data centers under quality of service constraints. IEEE Trans Parallel Distrib Syst 24(7):1366–1379CrossRef
2.
Yeo CS, Buyya R (2005) Service level agreement based allocation of cluster resources : handling penalty to enhance utility. In: Proceedings of the 7th IEEE International Conference on Cluster Computing
3.
Durao F, Fernando J, Carvalho S, Fonseka A (2014) A systematic review on cloud computing. J Supercomput 68(3):1321–1346CrossRef
4.
Groot S (2013) Research on efficient resource utilization in data intensive distributed systems. The University of Tokyo, Tokyo
5.
Yadwadkar NJ, Gonzalez JE, Katz R (2016) Multi-task learning for straggler avoiding predictive job scheduling. J Mach Learn Res 17:1–37MathSciNetMATH
6.
Ananthanarayanan G, Ghodsi A, Shenker S, Stoica I (2013) Effective straggler mitigation : attack of the clones. In: 10th USENIX Symposium on Networked Systems Design and Implementation, 2013, pp 185–198
7.
Hussain A, Aleem M, Islam MA, Iqbal MA (2018) A rigorous evaluation of state-of-the-art scheduling algorithms for cloud computing. IEEE Access 6:1–15CrossRef
8.
Kavulya S, Tany J, Gandhi R, Narasimhan P (2010) An analysis of traces from a production MapReduce cluster. In: 11th IEEE/ACM International Conference on Grid Computing (CCGrid), 2010, pp 94–103
9.
Isard M, Birrell A, Fetterly D (2007) Dryad: distributed data-parallel programs from sequential building blocks. In: 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems, 2007, pp 59–72
10.
Zaharia M et al (2012) Resilient distributed datasets : a fault-tolerant abstraction for in-memory cluster computing. In: 9th USENIX Conference on Networked Systems Design and Implementation
11.
Son S, Jung G, Chan S (2013) An SLA-based cloud computing that facilitates resource allocation in the distributed data centers of a cloud provider An SLA-based cloud computing that facilitates resource allocation in the distributed data centers of a cloud. J Supercomput 64(2):606–637CrossRef
12.
Garg SK, Toosi AN, Gopalaiyengar SK, Buyya R (2014) SLA-based virtual machine management for heterogeneous workloads in a cloud datacenter. J Netw Comput Appl 45:108–120CrossRef
13.
14.
Hussain A, Aleem M (2018) GoCJ: Google cloud jobs dataset for distributed and cloud computing infrastructure. MDPI Data 3(4):1–12
15.
16.
Braun TD et al (2001) A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems. J Parallel Distrib Comput 61(6):810–837CrossRef
17.
Calheiros RN, Ranjan R, Beloglazov A, De Rose CAF, Buyya R (2009) CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw Pract Exp 39(7):701–736
18.
Leitner P, Hummer W, Satzger B, Inzinger C, Dustdar S (2012) Cost-efficient and application SLA-aware client side request scheduling in an infrastructure-as-a-service cloud. In: IEEE Fifth International Conference on Cloud Computing, 2012, pp 213–220
19.
Alrokayan M, Dastjerdi AV, Buyya R (2014) SLA-aware provisioning and scheduling of cloud resources for big data analytics. In: IEEE International Conference on Cloud Computing in Emerging Markets (CCEM), 2014, pp 1–8
20.
Sharma U, Shenoy P, Sahu S, Shaikh A (2011) A cost-aware elasticity provisioning system for the cloud. In: IEEE 31st International Conference on Distributed Computing Systems, 2011, pp 559–570
21.
Lenzini L, Mingozzi E, Stea G (2004) Tradeoffs between low complexity, low latency, and fairness with deficit round-robin schedulers. IEEE/ACM Trans Netw 12(4):681–693CrossRef
22.
Aditya A, Chatterjee U, Gupta S (2015) A comparative study of different static and dynamic load balancing algorithm in cloud computing with special emphasis on time factor. Int J Curr Eng Technol 5(3):2277–4106
23.
Hamid S et al (2017) Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment. PLoS ONE 12(5):1–26
24.
Li B, Wu H (2015) Heuristics to allocate high-performance cloudlets for computation offloading in mobile ad hoc clouds. J Supercomput 71(8):3009–3036CrossRef
25.
Muhammed A, Abdullah A, Hussin M (2016) Max-average: an extended max–min scheduling algorithm for grid computing environment. J Telecommun Electron Comput Eng 8(6):43–47
26.
Elzeki OM, Rashad MZ, Elsoud MA (2012) Overview of scheduling tasks in distributed computing systems. Int J Soft Comput Eng 2(3):470–475
27.
Tchernykh A et al (2016) Online Bi-objective scheduling for IaaS clouds ensuring quality of service. J Grid Comput 14(1):5–22CrossRef
28.
Maheswaran M, Ali S, Siegel HJ, Hensgen D, Freund RF (1999) Dynamic mapping of a class of independent tasks onto heterogeneous computing systems. J Parallel Distrib Comput 59(2):107–131CrossRef
29.
Chen H, Wang F, Helian N, Akanmu G (2013) User-priority guided min-min scheduling algorithm for load balancing in cloud computing. In: 2013 National Conference on Parallel Computing Technologies, PARCOMPTECH 2013, pp 1–8
30.
Sharma G, Banga P (2013) Task aware switcher scheduling for batch mode mapping in computational grid environment. Int J Adv Res Comput Sci Softw Eng 3:1292–1299
31.
Panda SK, Jana PK (2017) SLA-based task scheduling algorithms for heterogeneous multi-cloud environment. J Supercomput 73(6):2730–2762CrossRef
32.
Al Shalabi L, Shaaban Z, Kasasbeh B (2006) Data mining: a preprocessing engine data mining. J Comput Sci 2(9):735–739CrossRef
33.
Shao X, Wang Z, Li P, Feng CJ (2005) Integrating data mining and rough set for customer group-based discovery of product configuration rules. Int J Prod Res 44(14):2789–2811CrossRef
Metadata
Title
SLA-RALBA: cost-efficient and resource-aware load balancing algorithm for cloud computing
Authors
Altaf Hussain
Muhammad Aleem
Muhammad Azhar Iqbal
Muhammad Arshad Islam
Publication date
05-06-2019
Publisher
Springer US
Published in
The Journal of Supercomputing / Issue 10/2019
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-019-02916-4

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