Abstract
We study online resource allocation in a cloud computing platform through posted pricing: The cloud provider publishes a unit price for each resource type, which may vary over time; upon arrival at the cloud system, a cloud user either takes the current prices, renting resources to execute its job, or refuses the prices without running its job there. We design pricing functions based on current resource utilization ratios, in a wide array of demand-supply relationships and resource occupation durations, and prove worst-case competitive ratios in social welfare. In the basic case of a single-type, non-recycled resource (allocated resources are not later released for reuse), we prove that our pricing function design is optimal, in that it achieves the smallest competitive ratio among all possible pricing functions. Insights obtained from the basic case are then used to generalize the pricing functions to more realistic cloud systems with multiple types of resources, where a job occupies allocated resources for a number of time slots till completion, upon which time the resources are returned to the cloud resource pool.
- 2017. Amazon EC2 Spot Instances Pricing. https://aws.amazon.com/ec2/spot/pricing/. (2017).Google Scholar
- 2017. Spot Instance Interruptions. https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/spot interruptions.html. (2017).Google Scholar
- Orna Agmon Ben-Yehuda, Muli Ben-Yehuda, Assaf Schuster, and Dan Tsafrir. 2013. Deconstructing amazon ec2 spot instance pricing. ACM Transactions on Economics and Computation 1, 3 (2013), 16. Google ScholarDigital Library
- May Al-Roomi, Shaikha Al-Ebrahim, Sabika Buqrais, and Imtiaz Ahmad. 2013. Cloud computing pricing models: a survey. International Journal of Grid and Distributed Computing 6, 5 (2013), 93--106.Google ScholarCross Ref
- Bo An, Victor Lesser, David Irwin, and Michael Zink. 2010. Automated negotiation with decommitment for dynamic resource allocation in cloud computing. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1-Volume 1. International Foundation for Autonomous Agents and Multiagent Systems, 981--988. Google ScholarDigital Library
- Niv Buchbinder and Joseph Naor. 2005. Online primal-dual algorithms for covering and packing problems. In European Symposium on Algorithms. Springer, 689--701. Google ScholarDigital Library
- Niv Buchbinder and Joseph Naor. 2006. Improved bounds for online routing and packing via a primal-dual approach. In 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06. IEEE. Google ScholarDigital Library
- Niv Buchbinder and Joseph Naor. 2009. The design of competitive online algorithms via a primal: dual approach. Foundations and Trends® in Theoretical Computer Science 3, 2--3 (2009), 93--263. Google ScholarDigital Library
- Rajkumar Buyya, Chee Shin Yeo, Srikumar Venugopal, James Broberg, and Ivona Brandic. 2009. Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation computer systems 25, 6 (2009), 599--616. Google ScholarDigital Library
- Yang Cai, Constantinos Daskalakis, and S Matthew Weinberg. 2013. Reducing revenue to welfare maximization: Approximation algorithms and other generalizations. In Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms. SIAM, 578--595. Google ScholarDigital Library
- Deeparnab Chakrabarty, Yunhong Zhou, and Rajan Lukose. 2008. Online knapsack problems. In Workshop on internet and network economics (WINE).Google Scholar
- Saurabh Kumar Garg, Steve Versteeg, and Rajkumar Buyya. 2013. A framework for ranking of cloud computing services. Future Generation Computer Systems 29, 4 (2013), 1012--1023. Google ScholarDigital Library
- Sijia Gu, Zongpeng Li, Chuan Wu, and Chuanhe Huang. 2016. An Efficient Auction Mechanism for Service Chains in The NFV Market. In Computer Communications, IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on. IEEE.Google ScholarCross Ref
- Hao Li, Jianhui Liu, and Guo Tang. 2011. A pricing algorithm for cloud computing resources. In Network Computing and Information Security (NCIS), 2011 International Conference on, Vol. 1. IEEE, 69--73. Google ScholarDigital Library
- Wei-Yu Lin, Guan-Yu Lin, and Hung-Yu Wei. 2010. Dynamic auction mechanism for cloud resource allocation. In Cluster, Cloud and Grid Computing (CCGrid), 2010 10th IEEE/ACM International Conference on. IEEE, 591--592. Google ScholarDigital Library
- RT Ma, Dah Ming Chiu, John CS Lui, Vishal Misra, and Dan Rubenstein. 2010. On resource management for cloud users: A generalized kelly mechanism approach. Electrical Engineering, Tech. Rep (2010).Google Scholar
- Sunilkumar S Manvi and Gopal Krishna Shyam. 2014. Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey. Journal of Network and Computer Applications 41 (2014), 424--440.Google ScholarCross Ref
- Ishai Menache, Asuman Ozdaglar, and Nahum Shimkin. 2011. Socially optimal pricing of cloud computing resources. In Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), 322--331. Google ScholarDigital Library
- Marian Mihailescu and Yong Meng Teo. 2010. Dynamic resource pricing on federated clouds. In Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing. IEEE Computer Society, 513--517. Google ScholarDigital Library
- Mahyar Movahed Nejad, Lena Mashayekhy, and Daniel Grosu. 2015. Truthful greedy mechanisms for dynamic virtual machine provisioning and allocation in clouds. IEEE transactions on parallel and distributed systems 26, 2 (2015), 594--603.Google Scholar
- Weijie Shi, Chuan Wu, and Zongpeng Li. 2014. RSMOA: A revenue and social welfare maximizing online auction for dynamic cloud resource provisioning. In 2014 IEEE 22nd International Symposium of Quality of Service (IWQoS). IEEE, 41--50.Google ScholarCross Ref
- Weijie Shi, Chuan Wu, and Zongpeng Li. 2016. An online mechanism for dynamic virtual cluster provisioning in geo-distributed clouds. In Computer Communications, IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on. IEEE.Google ScholarCross Ref
- Weijie Shi, Linquan Zhang, Chuan Wu, Zongpeng Li, and Francis Lau. 2014. An online auction framework for dynamic resource provisioning in cloud computing. ACM SIGMETRICS Performance Evaluation Review 42, 1 (2014), 71--83. Google ScholarDigital Library
- Adel Nadjaran Toosi, Rodrigo N Calheiros, and Rajkumar Buyya. 2014. Interconnected cloud computing environments: Challenges, taxonomy, and survey. ACM Computing Surveys (CSUR) 47, 1 (2014), 7. Google ScholarDigital Library
- Wei Wang, Ben Liang, and Baochun Li. 2013. Revenue maximization with dynamic auctions in IaaS cloud markets. In Quality of Service (IWQoS), 2013 IEEE/ACM 21st International Symposium on. IEEE, 1--6.Google ScholarCross Ref
- Hong Xu and Baochun Li. 2013. Dynamic cloud pricing for revenue maximization. IEEE Transactions on Cloud Computing 1, 2 (2013), 158--171. Google ScholarDigital Library
- Sharrukh Zaman and Daniel Grosu. 2013. Combinatorial auction-based allocation of virtual machine instances in clouds. J. Parallel and Distrib. Comput. 73, 4 (2013), 495--508. Google ScholarDigital Library
- Qi Zhang, Quanyan Zhu, Mohamed Faten Zhani, Raouf Boutaba, and Joseph L Hellerstein. 2013. Dynamic service placement in geographically distributed clouds. IEEE Journal on Selected Areas in Communications 31, 12 (2013), 762--772.Google ScholarCross Ref
- Xiaoxi Zhang, Zhiyi Huang, Chuan Wu, Zongpeng Li, and Francis Lau. 2015. Online auctions in IaaS clouds: welfare and profit maximization with server costs. In ACM SIGMETRICS Performance Evaluation Review, Vol. 43. ACM, 3--15. Google ScholarDigital Library
- Ruiting Zhou, Zongpeng Li, Chuan Wu, and Zhiyi Huang. 2016. An Efficient Cloud Market Mechanism for Computing Jobs With Soft Deadlines. IEEE/ACM Transactions on Networking (2016). Google ScholarDigital Library
- Yunhong Zhou, Deeparnab Chakrabarty, and Rajan Lukose. 2008. Budget constrained bidding in keyword auctions and online knapsack problems. In International Workshop on Internet and Network Economics. Springer, 566--576 Google ScholarDigital Library
Index Terms
- Optimal Posted Prices for Online Cloud Resource Allocation
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An online auction framework for dynamic resource provisioning in cloud computing
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Optimal Posted Prices for Online Cloud Resource Allocation
SIGMETRICS '17 Abstracts: Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer SystemsWe study online resource allocation in a cloud computing platform, through a posted pricing mechanism: The cloud provider publishes a unit price for each resource type, which may vary over time; upon arrival at the cloud system, a cloud user either ...
Optimal Posted Prices for Online Cloud Resource Allocation
Performance evaluation reviewWe study online resource allocation in a cloud computing platform, through a posted pricing mechanism: The cloud provider publishes a unit price for each resource type, which may vary over time; upon arrival at the cloud system, a cloud user either ...
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