Decentralizing the cloud: How can small data centers cooperate?

Cloud computing has become pervasive due to attractive features such as on-demand resource provisioning and elasticity. Most cloud providers are centralized entities that employ massive data centers. However, in recent times, due to increasing concerns about privacy and data control, many small data centers (SDCs) established by different providers are emerging in an attempt to meet demand locally. However, SDCs can suffer from resource in-elasticity due to their relatively scarce resources, resulting in a loss of performance and revenue. In this paper we propose a decentralized cloud model in which a group of SDCs can cooperate with each other to improve performance. Moreover, we design a general strategy function for the SDCs to evaluate the performance of cooperation based on different dimensions of resource sharing. Through extensive simulations using a realistic data center model, we show that the strategies based on reciprocity are more effective than other involved strategies, e.g., those using prediction on historical data. Our results show that the reciprocity-based strategy can thrive in a heterogeneous environment with competing strategies.

[1]  Rossitza Goleva,et al.  EVALUATION OF PARETO/D/1/K QUEUE BY SIMULATION , 2008 .

[2]  A. Rapoport,et al.  Prisoner's Dilemma: A Study in Conflict and Co-operation , 1970 .

[3]  Muli Ben-Yehuda,et al.  The Reservoir model and architecture for open federated cloud computing , 2009, IBM J. Res. Dev..

[4]  Hector Garcia-Molina,et al.  The Eigentrust algorithm for reputation management in P2P networks , 2003, WWW '03.

[5]  Randy H. Katz,et al.  A view of cloud computing , 2010, CACM.

[6]  Feng Wang,et al.  Measurement and utilization of customer-provided resources for cloud computing , 2012, 2012 Proceedings IEEE INFOCOM.

[7]  Baochun Li,et al.  Dynamic Cloud Resource Reservation via Cloud Brokerage , 2013, 2013 IEEE 33rd International Conference on Distributed Computing Systems.

[8]  Stefan Schmid,et al.  Robust live media streaming in swarms , 2009, NOSSDAV '09.

[9]  Özalp Babaoglu,et al.  Design and implementation of a P2P Cloud system , 2012, SAC '12.

[10]  Chen-Nee Chuah,et al.  BASS: BitTorrent Assisted Streaming System for Video-on-Demand , 2005, 2005 IEEE 7th Workshop on Multimedia Signal Processing.

[11]  Stuart E. Madnick,et al.  Why Not One Big Database? Principles for Data Ownership , 1995, Decis. Support Syst..

[12]  Manish Parashar,et al.  Exploring Models and Mechanisms for Exchanging Resources in a Federated Cloud , 2014, 2014 IEEE International Conference on Cloud Engineering.

[13]  Primavera De Filippi,et al.  Cloud Computing: Legal Issues in Centralized Architectures , 2011 .

[14]  Rajkumar Buyya,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011, Softw. Pract. Exp..

[15]  Michal Feldman,et al.  Overcoming free-riding behavior in peer-to-peer systems , 2005, SECO.

[16]  Nancy Samaan,et al.  A Novel Economic Sharing Model in a Federation of Selfish Cloud Providers , 2014, IEEE Transactions on Parallel and Distributed Systems.

[17]  Michael Muskulus,et al.  Modeling Job Arrivals in a Data-Intensive Grid , 2006, JSSPP.

[18]  Emin Gün Sirer,et al.  KARMA : A Secure Economic Framework for Peer-to-Peer Resource Sharing , 2003 .

[19]  W. Hamilton,et al.  The Evolution of Cooperation , 1984 .

[20]  Abhishek Chandra,et al.  Decentralized Edge Clouds , 2013, IEEE Internet Computing.

[21]  David Hales,et al.  Design space analysis for modeling incentives in distributed systems , 2011, SIGCOMM.