Resource Availability Characteristicsand Node Selection in CooperativelyShared Computing Platforms

The focus of our work is on studying the resource availability characteristics of large-scale, cooperatively pooled, shared computing platforms. Our focus is on platforms in which resources at a node are allocated to competing users on fair-share basis, without any reserved resource capacities for any user, and there is no platform-wide resource manager for the placement of users on different nodes. The users independently select nodes for their applications. Our study is focused on the PlanetLab system which exemplifies such platforms. The goal of our study is to develop heuristics based on the observed resource availability characteristics for selecting nodes for deploying applications. Our approach uses the notion of eligibility period, which represents a contiguous duration for which a node satisfies a given resource requirement. We study the characteristics of the eligibility periods of Planetlab nodes for various resource capacity requirements. Based on this study we develop heuristics for identifying nodes that are likely to satisfy a given requirement for long durations. We also develop an online model for predicting the idle resource capacity that is likely to be available on a node over a short term. We evaluate and demonstrate the performance benefits of the node selection techniques and the prediction model using the PlanetLab node utilization data traces collected at different intervals over an extended period of several months.

[1]  Thomas R. Gross,et al.  Design, Implementation, and Evaluation of the Remos Network Monitoring System , 2004, Journal of Grid Computing.

[2]  Richard Wolski,et al.  Dynamically forecasting network performance using the Network Weather Service , 1998, Cluster Computing.

[3]  Jean-Marc Vincent,et al.  Discovering Statistical Models of Availability in Large Distributed Systems: An Empirical Study of SETI@home , 2011, IEEE Transactions on Parallel and Distributed Systems.

[4]  Richard Wolski,et al.  Modeling Machine Availability in Enterprise and Wide-Area Distributed Computing Environments , 2005, Euro-Par.

[5]  Guillaume Pierre,et al.  Autonomous Resource Selection for Decentralized Utility Computing , 2009, 2009 29th IEEE International Conference on Distributed Computing Systems.

[6]  I. Foster,et al.  The grid grows up , 2003, IEEE Internet Computing.

[7]  Wilhelm Hasselbring,et al.  Availability of Globally Distributed Nodes: An Empirical Evaluation , 2008, 2008 Symposium on Reliable Distributed Systems.

[8]  Larry L. Peterson,et al.  Sophia: an Information Plane for networked systems , 2004, Comput. Commun. Rev..

[9]  David E. Culler,et al.  Operating Systems Support for Planetary-Scale Network Services , 2004, NSDI.

[10]  Amin Vahdat,et al.  Design and implementation tradeoffs for wide-area resource discovery , 2005, HPDC-14. Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing, 2005..

[11]  Richard Wolski,et al.  The network weather service: a distributed resource performance forecasting service for metacomputing , 1999, Future Gener. Comput. Syst..

[12]  Miron Livny,et al.  The Available Capacity of a Privately Owned Workstation Environmont , 1991, Perform. Evaluation.

[13]  Peter A. Dinda,et al.  The statistical properties of host load , 1999, Sci. Program..

[14]  Daniel Stutzbach,et al.  Understanding churn in peer-to-peer networks , 2006, IMC '06.

[15]  Richard Wolski,et al.  Predicting the CPU availability of time‐shared Unix systems on the computational grid , 2004, Cluster Computing.

[16]  Abhishek Chandra,et al.  Resource Bundles: Using Aggregation for Statistical Wide-Area Resource Discovery and Allocation , 2008, 2008 The 28th International Conference on Distributed Computing Systems.

[17]  Matt W. Mutka.  Estimating Capacity For Sharing in a Privately Owned Workstation Environment , 1992, IEEE Trans. Software Eng..

[18]  Amin Vahdat,et al.  Service Placement in a Shared Wide-Area Platform , 2006, USENIX Annual Technical Conference, General Track.

[19]  Rudolf Eigenmann,et al.  Resource Availability Prediction in Fine-Grained Cycle Sharing Systems , 2006, 2006 15th IEEE International Conference on High Performance Distributed Computing.

[20]  Xian-He Sun,et al.  Performance Modeling and Prediction of Nondedicated Network Computing , 2002, IEEE Trans. Computers.

[21]  Peter A. Dinda,et al.  An Extensible Toolkit for Resource Prediction In Distributed Systems , 1999 .

[22]  Anand R. Tripathi,et al.  Building Autonomically Scalable Services on Wide-Area Shared Computing Platforms , 2011, 2011 IEEE 10th International Symposium on Network Computing and Applications.

[23]  KyoungSoo Park,et al.  CoMon: a mostly-scalable monitoring system for PlanetLab , 2006, OPSR.

[24]  Andrew A. Chien,et al.  Henri Casanova , 2022 .

[25]  David E. Culler,et al.  The ganglia distributed monitoring system: design, implementation, and experience , 2004, Parallel Comput..

[26]  Gilles Fedak,et al.  Characterizing resource availability in enterprise desktop grids , 2007, Future Gener. Comput. Syst..

[27]  Alexandru Iosup,et al.  On the dynamic resource availability in grids , 2007, 2007 8th IEEE/ACM International Conference on Grid Computing.

[28]  Amin Vahdat,et al.  Design and implementation tradeoffs for wide-area resource discovery , 2005, HPDC.

[29]  Anand R. Tripathi,et al.  Resource-Aware Migratory Services in Wide-Area Shared Computing Environments , 2009, 2009 28th IEEE International Symposium on Reliable Distributed Systems.