CloudBay: Enabling an Online Resource Market Place for Open Clouds

This paper presents Cloud Bay, an online resource trading and leasing platform for multi-party resource sharing. Following a market-oriented design principle, Cloud Bay provides an abstraction of a shared virtual resource space across multiple administration domains, and features enhanced functionalities for scalable and automatic resource management and efficient service provisioning. Cloud Bay distinguishes itself from existing research and contributes in a number of aspects. First, it leverages scalable network virtualization and self-configurable virtual appliances to facilitate resource federation and parallel application deployment. Second, Cloud Bay adopts an eBay-style transaction model that supports differentiated services with different levels of job priorities. For cost-sensitive users, Cloud Bay implements an efficient matchmaking algorithm based on auction theory and enables opportunistic resource access through preemptive service scheduling. The proposed Cloud Bay platform stands between HPC service sellers and buyers, and offers a comprehensive solution for resource advertising and stitching, transaction management, and application-to-infrastructure mapping. In this paper, we present the design details of Cloud Bay, and discuss lessons and challenges encountered in the implementation process. The proof-of-concept prototype of Cloud Bay is justified through experiments across multiple sites and simulations.

[1]  Arkady Kanevsky,et al.  Enabling a marketplace of clouds: VMware's vCloud director , 2010, OPSR.

[2]  Richard Wolski,et al.  G-commerce: market formulations controlling resource allocation on the computational grid , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

[3]  Evgenia Smirni,et al.  Multiple-queue backfilling scheduling with priorities and reservations for parallel systems , 2002, PERV.

[4]  Randy H. Katz,et al.  Improving MapReduce Performance in Heterogeneous Environments , 2008, OSDI.

[5]  David Abramson,et al.  Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid , 2000, Proceedings Fourth International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region.

[6]  Cynthia Bailey Lee,et al.  Are User Runtime Estimates Inherently Inaccurate? , 2004, JSSPP.

[7]  Carrie Grimes,et al.  Using a market economy to provision compute resources across planet-wide clusters , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

[8]  Li Zhang,et al.  Tycoon: An implementation of a distributed, market-based resource allocation system , 2004, Multiagent Grid Syst..

[9]  Nazareno Andrade,et al.  Labs of the World, Unite!!! , 2006, Journal of Grid Computing.

[10]  Mohamed Jemni,et al.  BonjourGrid: Orchestration of multi-instances of grid middlewares on institutional Desktop Grids , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

[11]  Lawrence M. Ausubel An Efficient Ascending-Bid Auction for Multiple Objects , 2004 .

[12]  David Wolinsky,et al.  Experiences with self-organizing, decentralized grids using the grid appliance , 2011, HPDC '11.

[13]  S. Krishnan myHadoop-Hadoop-on-Demand on Traditional HPC Resources , 2004 .

[14]  Paul Marshall,et al.  Improving Utilization of Infrastructure Clouds , 2011, 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

[15]  Pierre St. Juste,et al.  On the design of scalable, self-configuring virtual networks , 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

[16]  N. Nisan,et al.  The POPCORN market—an online market for computational resources , 1998, ICE '98.

[17]  P. Oscar Boykin,et al.  IP over P2P: enabling self-configuring virtual IP networks for grid computing , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[18]  Lior Amar,et al.  The Effects of Untruthful Bids on User Utilities and Stability in Computing Markets , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.