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An online greedy allocation of VMs with non-increasing reservations in clouds

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Abstract

Dynamic VMs allocation plays an important role in resource allocation of cloud computing. In general, a cloud provider needs both to maximize the efficiency of resource and to improve the satisfaction of in-house users simultaneously. However, industrial experience has often shown only maximizing the efficiency of resources and providing poor or little service guarantee for users. In this paper, we propose a novel model-free virtual machine allocation, which is characterized by an online greedy algorithm with reservation of virtual machines, and is named OGAWR. We couple the greedy allocation algorithm with non-increasing reserving algorithms to deal with flexible jobs and inflexible jobs. With the OGAWR, users are incentivized to be truthful not only about their valuations, but also about their arrival, departure and the characters of jobs (flexible or inflexible). We simulated the proposed OGAWR using data from RICC. The results show that OGAWR can lead to high social welfare and high percentage of served users, compared with another mechanism that adopts the same method of allocation and reservation for all jobs. The results also prove that the OGAWR is an appropriate market-based model for VMs allocation because it works better for allocation efficiency and served users.

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References

  1. Abramson D, Buyya R, Giddy J (2002) A computational economy for grid computing and its implementation in the nimrod-g resource broker. Future Gener Computer Syst 18(8):1061–1074

    Article  MATH  Google Scholar 

  2. Agmon Ben-Yehuda O, Ben-Yehuda M, Schuster A, Tsafrir D (2013) Deconstructing amazon ec2 spot instance pricing. ACM Trans Econ Comput 1(3):16

    Article  Google Scholar 

  3. Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I et al (2010) A view of cloud computing. Commun ACM 53(4):50–58

    Article  Google Scholar 

  4. Constantin F, Feldman J, Muthukrishnan S, Pál M (2009) An online mechanism for ad slot reservations with cancellations. In: Proceedings of the twentieth annual ACM-SIAM symposium on discrete algorithms, pp 1265–1274. Society for Industrial and Applied Mathematics

  5. Danak A, Mannor S (2010) Resource allocation with supply adjustment in distributed computing systems. In: IEEE 30th international conference on distributed computing systems (ICDCS), 2010, pp 498-506. IEEE

  6. Dash RK, Vytelingum P, Rogers A, David E, Jennings NR (2007) Market-based task allocation mechanisms for limited-capacity suppliers. IEEE Trans Syst Man Cybern Part A Syst Humans 37(3):391–405

    Article  Google Scholar 

  7. Feitelson DG (2015) Parallel workloads archives: logs. http://www.cs.huji.ac.il/labs/parallel/workload/logs.html

  8. Friedman EJ, Parkes DC (2003) Pricing wifi at starbucks: issues in online mechanism design. In: Proceedings of the 4th ACM conference on electronic commerce, pp 240–241. ACM

  9. Garg SK, Venugopal S, Broberg J, Buyya R (2013) Double auction-inspired meta-scheduling of parallel applications on global grids. J Parallel Distrib Comput 73(4):450–464

    Article  Google Scholar 

  10. Gerding EH, Robu V, Stein S, Parkes DC, Rogers A, Jennings NR (2011) Online mechanism design for electric vehicle charging. In: The 10th international conference on autonomous agents and multiagent systems, vol 2, pp 811–818. International Foundation for Autonomous Agents and Multiagent Systems

  11. Gershkov A, Moldovanu B (2010) Efficient sequential assignment with incomplete information. Games Econ Behav 68(1):144–154

    Article  MathSciNet  MATH  Google Scholar 

  12. Hajiaghayi MT (2005) Online auctions with re-usable goods. In: Proceedings of the 6th ACM conference on electronic commerce, pp 165–174. ACM

  13. Hao F, Kodialam M, Lakshman T, Mukherjee S (2014) Online allocation of virtual machines in a distributed cloud. In: INFOCOM, 2014 proceedings IEEE, pp 10–18. IEEE

  14. Hsu CH, Slagter KD, Chen SC, Chung YC (2014) Optimizing energy consumption with task consolidation in clouds. Inf Sci 258:452–462

    Article  Google Scholar 

  15. Jain N, Menache I, Naor JS, Yaniv J (2014) A truthful mechanism for value-based scheduling in cloud computing. Theory Comput Syst 54(3):388–406

    Article  MathSciNet  Google Scholar 

  16. Lavi R, Nisan N (2000) Competitive analysis of incentive compatible on-line auctions. In: Proceedings of the 2nd ACM conference on electronic commerce, pp 233–241. ACM

  17. Lizhe W, Hao G, Peng L, Ke L, Joanna K, Rajiv R, Y ZA (2015) Particle swarm optimization based dictionary learning for remote sensing big data. J Knowl Based Syst 79:43–50

    Article  Google Scholar 

  18. Lizhe W, Jie T, Rajiv R, Holger M, Achim S, Jingying C, Dan C (2013) G-hadoop: Mapreduce across distributed data centers for data-intensive computing. J Future Gener Compter Syst 29(3):739–750

    Article  Google Scholar 

  19. Lizhe W, Samee UK, Dan C, Joanna K, Rajiv R, Cheng-Zhong X, Y ZA (2013) Energy-aware parallel task scheduling in a cluster. J Future Gener Compter Syst 29(7):1661–1670

    Article  Google Scholar 

  20. Ma W, Zheng B, Qin T, Tang P, Liu T (2014) Online mechanism design for cloud computing. arXiv:1403.1896

  21. Nisan N, Roughgarden T, Tardos E, Vazirani VV (2007) Algorithmic game theory, vol 1. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  22. Niu D, Feng C, Li B (2012) Pricing cloud bandwidth reservations under demand uncertainty. In: ACM SIGMETRICS performance evaluation review, vol 40, pp 151–162. ACM

  23. Parkes DC, Duong Q (2007) An ironing-based approach to adaptive online mechanism design in single-valued domains. In: AAAI, vol 7, pp 94–101

  24. Parkes DC, Singh SP (2003) An mdp-based approach to online mechanism design. In: Advances in neural information processing systems

  25. Porter R (2004) Mechanism design for online real-time scheduling. In: Proceedings of the 5th ACM conference on electronic commerce, pp 61–70. ACM

  26. Robu V, Stein S, Gerding EH, Parkes DC, Rogers A, Jennings NR(2012) An online mechanism for multi-speed electric vehicle charging. In: Auctions, market mechanisms, and their applications, pp 100–112. Springer, New York

  27. Shi W, Zhang L, Wu C, Li Z, Lau F (2014) An online auction framework for dynamic resource provisioning in cloud computing. In: The 2014 ACM international conference on measurement and modeling of computer systems, pp 71–83. ACM

  28. Wang Q, Ren K, Meng X (2012) When cloud meets ebay: towards effective pricing for cloud computing. In: INFOCOM, 2012 proceedings IEEE, pp 936–944. IEEE

  29. Weijing S, Lizhe W, Rajiv R, Joanna K, Dan C (2015) Towards modeling large-scale data flows in a multidatacenter computing system with petri net. IEEE Syst J 9(2):416–426

    Article  Google Scholar 

  30. Wolski R, Plank JS, Brevik J, Bryan T (2001) Analyzing market-based resource allocation strategies for the computational grid. Int J High Perfor Comput Appl 15(3):258–281

    Article  Google Scholar 

  31. Wu C, Li Z, Qiu X, Lau F (2012) Auction-based p2p vod streaming: incentives and optimal scheduling. ACM Trans Multim Comput Commun Appl (TOMCCAP) 8(1S):14

    Google Scholar 

  32. Wu X, Gu Y, Li G, Ma X, Tao J (2014) Online mechanism design for vms allocation in private cloud. In: The 11th IFIP international conference on network and parallel computing (NPC’14), pp 234–246

  33. Xu Y, Li K, Hu J, Li K (2014) A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues. Inf Sci 270:255–287

    Article  MathSciNet  Google Scholar 

  34. Zaman S, Grosu D (2012) An online mechanism for dynamic vm provisioning and allocation in clouds. In: IEEE 5th international conference on cloud computing (CLOUD), 2012, pp 253–260. IEEE

  35. Zaman S, Grosu D (2013) Combinatorial auction-based allocation of virtual machine instances in clouds. J Parallel Distrib Comput 73(4):495–508

    Article  Google Scholar 

  36. Zhang H, Li B, Jiang H, Liu F, Vasilakos AV, Liu J (2013) A framework for truthful online auctions in cloud computing with heterogeneous user demands. In: INFOCOM, 2013 Proceedings IEEE, pp 1510–1518. IEEE

  37. Zhang Q, Zhu Q, Boutaba R (2011) Dynamic resource allocation for spot markets in cloud computing environments. In: 2011 Fourth IEEE international conference on utility and cloud computing (UCC), pp 178–185. IEEE

  38. Zhao J, Li H, Wu C, Li Z, Zhang Z, Lau F (2014) Dynamic pricing and profit maximization for the cloud with geo-distributed data centers. In: INFOCOM, 2014 Proceedings IEEE, pp 118–126. IEEE

  39. Zhu Y, Li B, Li Z (2012) Truthful spectrum auction design for secondary networks. In: INFOCOM, 2012 Proceedings IEEE, pp 873–881. IEEE

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Acknowledgments

The workload log from the RICC cluster was graciously provided by Motoyoshi Kurokawa. This work has been supported by the National Natural Science Foundation of China (No. 61170029, 61472240, 61373032 and 71271126), Doctoral Fund of Ministry of Education of China under Grant No. 20120078110002, and Zhejiang Provincial Science and Technology Plan of China under Grant No. 2013C31097.

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Authors and Affiliations

  1. Shanghai University of Finance and Economics, Shanghai, China

    Xiaohong Wu & Jingti Han

  2. Huzhou University, Huzhou, China

    Xiaohong Wu, Yonggen Gu & Jie Tao

  3. Shanghai Jiao Tong University, Shanghai, China

    Guoqiang Li

  4. RMIT Universtiy, Melbourne, VIC, 3000, Australia

    Prem Prakash Jayaraman

  5. NICTA, Sydney, Australia

    Daniel Sun

  6. Newcastle University, Tyne and Wear NE1 7RU, United Kingdom

    Rajiv Ranjan

  7. The University of Sydney, New South Wales 2006, Australia

    Albert Zomaya

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  1. Xiaohong Wu
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Correspondence to Guoqiang Li.

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Wu, X., Gu, Y., Tao, J. et al. An online greedy allocation of VMs with non-increasing reservations in clouds. J Supercomput 72, 371–390 (2016). https://doi.org/10.1007/s11227-015-1567-9

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