A hybrid meta-heuristic algorithm for VM scheduling with load balancing in cloud computing

Neural Computing and Applications

Volumn 26, Issue 6, 2015, Pages 1297-1309

  Cho, Keng Mao ^a   Tsai, Pang Wei ^a   Tsai, Chun Wei ^b   Yang, Chu Sing ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^b NATIONAL ILAN UNIVERSITY   (Taiwan)

Author keywords

Ant colony optimization; Cloud computing; Load balance; Particle swarm optimization; Scheduling

Indexed keywords

ANT COLONY OPTIMIZATION; ARTIFICIAL INTELLIGENCE; CLOUD COMPUTING; HEURISTIC ALGORITHMS; INFRASTRUCTURE AS A SERVICE (IAAS); NETWORK MANAGEMENT; PARALLEL ARCHITECTURES; PARTICLE SWARM OPTIMIZATION (PSO); SCHEDULING ALGORITHMS;

DYNAMIC ENVIRONMENTS; HISTORICAL INFORMATION; HYBRID META-HEURISTIC; LOAD BALANCE; SCHEDULING PROBLEM; SERVICE FRAMEWORK; TASK INFORMATION; VIRTUAL MACHINES;

SCHEDULING;

EID: 84937972396     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-014-1804-9     Document Type: Article

References (55)

1. Ahn Y, Kim WJ, Chung KS, Kim SH, Kim HS, Han TH (2010) A novel load balancing method for multi-core with non-uniform memory architecture. In: Proceedings of the international SoC design conference, pp 412–415
2. Alford T, Morton G (2009) The economics of cloud computing: addressing the benefits of infrastructure in the cloud. Booz Allen Hamilton, McLean
3. Amazon (2008) Amazon elastic compute cloud. http://aws.amazon.com/ec2
4. Amazon (2008) Amazon simple storage service. http://aws.amazon.com/s3
5. Bai L, Hu YL, Lao S, Zhang WM (2010) Task scheduling with load balancing using multiple ant colonies optimization in grid computing. In: Proceedings of the international conference on natural computation, pp 2715–2719
6. Blum C, Roli A (2003) Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput Surv 35(3):268–308
7. Buyya R, Abramson D, Giddy J (2000) Nimrod/g: an architecture for a resource management and scheduling system in a global computational grid. In: Proceedings of the international conference/exhibition on high performance computing in the Asia-Pacific region, vol 1, pp 283–289
8. Cao J, Spooner D, Jarvis S, Saini S, Nudd GR (2003) Agent-based grid load balancing using performance-driven task scheduling. In: Proceedings of the international parallel and distributed processing symposium, p 49
9. Chen WN, Zhang J (2009) An ant colony optimization approach to a grid workflow scheduling problem with various qos requirements. IEEE Trans Syst Man Cybern C Appl Rev 39(1):29–43
10. Chiang CW, Lee YC, Lee CN, Chou TY (2006) Ant colony optimisation for task matching and scheduling. IEE Proc Comput Digit Tech 153(6):373–380
11. Cho KM, Tsai PW, Tsai CW, Yang CS (2014) An aco-based algorithm for vm scheduling with load balancing in cloud computing. In: Proceedings of the international conference on computing, measurement, control and sensor network, pp 1–10
12. Colorni A, Dorigo M, Maniezzo V, Trubian M (1994) Ant system for job-shop scheduling. J Oper Res Stat Comput Sci 34(1):39–53
13. Croce FD, Tadei R, Volta G (1995) A genetic algorithm for the job shop problem. Comput Oper Res 22(1):15–24
14. Dell’Amico M, Trubian M (1993) Applying tabu search to the job-shop scheduling problem. Ann Oper Res 41(3):231–252
15. Dorigo M, Maniezzo V, Colorni A (1996) Ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern B Cybern 26(1):29–41
16. Elhossini A, Huissman J, Debowski B, Areibi S, Dony R (2010) An efficient scheduling methodology for heterogeneous multi-core processor systems. In: Proceedings of the international conference on microelectronics, pp 475–478
17. Ferrandi F, Lanzi PL, Pilato C, Sciuto D, Tumeo A (2010) Ant colony heuristic for mapping and scheduling tasks and communications on heterogeneous embedded systems. IEEE Trans Comput Aided Des Integr Circuits Syst 29(6):911–924
18. Garcia-Nieto J, Olivera A, Alba E (2013) Optimal cycle program of traffic lights with particle swarm optimization. IEEE Trans Evol Comput 17(6):823–839
19. Graham RL, Lawler EL, Lenstra JK, Kan AHGR (1979) Optimization and approximation in deterministic sequencing and scheduling: a survey. Ann Discrete Math 4:287–326
20. Hahne EL, Gallager RG (1986) Round robin scheduling for fair flow control in data communication networks. In: Proceedings of the IEEE international conference on communication, pp 103–107
21. Hamilton D (2008) Cloud computing seen as next wave for technology investors. Financial Post. http://www.financialpost.com/money/story.html
22. Hao S, Liu Q, Zhang L, Wang J (2010) Processes scheduling on heterogeneous multi-core architecture with hardware support. In: Proceedings of the IEEE international conference on networking, architecture and storage, pp 236–241
23. Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. The University of Michigan press, Ann Arbor
24. Huang KL, Liao CJ (2008) Ant colony optimization combined with taboo search for the job shop scheduling problem. Comput Oper Res 35(4):1030–1046
25. Jeon H, Lee WH, Chung SW (2010) Load unbalancing strategy for multicore embedded processors. IEEE Trans Comput 59(10):1434–1440
26. Jiankang D, Hongbo W, Yangyang L, Shiduan C (2014) Virtual machine scheduling for improving energy efciency in IaaS cloud. China Commun 11(3):1–12
27. Junqiang W, Aijia O (2012) A hybrid algorithm of ACO and delete-cross method for TSP. In: Proceedings of the international conference on industrial control and electronics engineering, pp 1694–1696
28. Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of the IEEE international conference on neural networks, vol 4, pp 1942–1948
29. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680
30. Lin C, Lu S (2011) Scheduling scientific workflows elastically for cloud computing. In: Proceedings of the IEEE international conference on cloud computing, pp 746–747
31. Liu B, Wang L, Jin YH (2007) An effective PSO-based memetic algorithm for flow shop scheduling. IEEE Trans Syst Man Cybern B Cybern 37(1):18–27
32. Lu W, Zhiliang W, Siquan H, Lei L (2013) Ant colony optimization for task allocation in multi-agent systems. China Commun 10(3):125–132
33. Lu X, Gu Z (2011) A load-adapative cloud resource scheduling model based on ant colony algorithm. In: Proceedings of the IEEE international conference on cloud computing and intelligence systems, pp 296–300
34. Moreno-Vozmediano R, Montero R, Llorente I (2013) Key challenges in cloud computing: enabling the future internet of services. IEEE Internet Comput 17(4):18–25
35. Parsopoulos KE, Varhatis MN (2010) Particle swarm optimization and intelligence: advances and applications. Information Science Reference, Hershey
36. Pinedo ML (2008) Scheduling: theory, algorithms, and systems, 3rd edn. Springer, Berlin
37. Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization. Swarm Intell 1(1):33–57
38. Rodammer F, White KPJ (1988) A recent survey of production scheduling. IEEE Trans Syst Man Cybern 18(6):841–851
39. Sadiku M, Musa S, Momoh O (2014) Cloud computing: opportunities and challenges. IEEE Potentials 33(1):34–36
40. Schwiegelshohn U, Yahyapour R (1998) Analysis of first-come-first-serve parallel job scheduling. In: Proceedings of the SIAM symposium on discrete algorithms, pp 629–638
41. Selvarani S, Sadhasivam G (2010) Improved cost-based algorithm for task scheduling in cloud computing. In: Proceedings of the IEEE international conference on computational intelligence and computing research, pp 1–5
42. Sheth R (2009) What we talk about when we talk about cloud computing. Google Enterprise Blog. http://googleenterprise.blogspot.tw/2009/04/what-we-talk-about-when-we-talk-about.html
43. Taillard ED (1994) Parallel taboo search techniques for the job shop scheduling problem. ORSA J Comput 6(2):108–117
44. Tsai CW, Huang KW, Chiang MC, Yang CS (2014) A fast particle swarm optimization for clustering. Soft Comput. doi:10.1007/s00500-014-1255-3
45. Tsai PW, Lai YT, Cheng PW, Luo MY, Yang CS (2013) Design and develop an OpenFlow testbed within virtualized architecture. In: Proceedings of the Asia-Pacific network operations and management symposium, pp 1–3
46. Tsakalozos K, Roussopoulos M, Delis A (2013) Hint-based execution of workloads in clouds with nefeli. IEEE Trans Parallel Distrib Syst 24(7):1331–1340
47. Umale J, Mahajan S (2010) Optimized grid scheduling using two level decision algorithm (TLDA). In: Proceedings of the international conference on parallel distributed and grid computing, pp 78–82
48. Wang J, Duan Q, Jiang Y, Zhu X (2010) A new algorithm for grid independent task schedule: genetic simulated annealing. In: Proceedings of the World Automation Congress, pp 165–171
49. Warneke D, Kao O (2011) Exploiting dynamic resource allocation for efficient parallel data processing in the cloud. IEEE Trans Parallel Distrib Syst 22(6):985–997
50. Wen X, Huang M, Shi J (2012) Study on resources scheduling based on ACO allgorithm and PSO algorithm in cloud computing. In: Proceedings of the international symposium on distributed computing and applications to business, engineering science, pp 219–222
51. West DM (2010) Saving money through cloud computing. Brookings Institution http://www.brookings.edu/research/papers/2010/04/07-cloud-computing-west
52. Xie X, Wu P (2010) Research on the optimal combination of ACO parameters based on PSO. In: Proceedings of the international conference on networking and digital Society, vol 1, pp 94–97
53. Yang X, Jiong Yu B.L, Yu F (2011) Grid schedule algorithm based on load with trust-driven mechanism. In: Proceedings of the chinagrid conference, pp 246–250
54. Zhong M, Pan X (2006) A two-step ACO–PSO approach to optimize flexible jobshop scheduling of air compressor based on petri net model. In: Proceedings of the international technology and innovation conference, pp 295–299
55. Zuo X, Zhang G, Tan W (2014) Self-adaptive learning PSO-based deadline constrained task scheduling for hybrid IaaS cloud. IEEE Trans Autom Sci Eng 11(2):564–573