A Model for Reducing Power Consumption in Peer-to-Peer Systems

Information systems based on the cloud computing model and peer-to-peer (P2P) model are now getting popular. In the cloud computing model, a cloud of servers support thin clients with various types of service like Web pages and databases. On the other hand, every computer is peer and there is no centralized coordinator in the P2P model. It is getting more significant to discuss how to reduce the total electric power consumption of computers in information systems to realize eco-society. In this paper, we consider a Web type of application on P2P overlay networks. First, we discuss a model for showing how much each server peer consumes electric power to perform Web requests from client peers. Then, we discuss algorithms for a client peer to select a server peer in a collection of server peers so that the total power consumption can be reduced while some constraint like deadline one is satisfied. Lastly, we evaluate the algorithms in terms of the total power consumption and throughput compared with traditional round robin algorithms.

[1]  Nancy A. Lynch,et al.  Impossibility of distributed consensus with one faulty process , 1985, JACM.

[2]  Ricardo Bianchini,et al.  Analytical and experimental evaluation of cluster-based network servers , 2000, World Wide Web.

[3]  Ian F. Akyildiz,et al.  Wireless Sensor and Actor Networks , 2010 .

[4]  Willy Zwaenepoel,et al.  Cluster reserves: a mechanism for resource management in cluster-based network servers , 2000, SIGMETRICS '00.

[5]  Tomoya Enokido,et al.  Consistency Based Approach for Agreement Achievement among Peers , 2009, 2009 International Conference on Network-Based Information Systems.

[6]  Ricardo Bianchini,et al.  Energy conservation in heterogeneous server clusters , 2005, PPoPP.

[7]  Robert L. Grossman,et al.  The Case for Cloud Computing , 2009, IT Professional.

[8]  Ricardo Bianchini,et al.  Self-Configuring Heterogeneous Server Clusters , 2006 .

[9]  Alessandro Bevilacqua A Dynamic Load Balancing Method On A Heterogeneous Cluster Of Workstations , 1999, Informatica.

[10]  Ian F. Akyildiz,et al.  Wireless sensor and actor networks: research challenges , 2004, Ad Hoc Networks.

[11]  Ricardo Bianchini,et al.  Power and energy management for server systems , 2004, Computer.

[12]  Tomoya Enokido,et al.  Models for P2P Multi-Source Streaming , 2009, 2009 International Conference on Complex, Intelligent and Software Intensive Systems.

[13]  Karthick Rajamani,et al.  On evaluating request-distribution schemes for saving energy in server clusters , 2003, 2003 IEEE International Symposium on Performance Analysis of Systems and Software. ISPASS 2003..

[14]  Liang-Jie Zhang,et al.  CCOA: Cloud Computing Open Architecture , 2009, 2009 IEEE International Conference on Web Services.

[15]  Tomoya Enokido,et al.  Energy-Efficient Computation Models for Distributed Systems , 2009, 2009 International Conference on Network-Based Information Systems.

[16]  Alberto Montresor,et al.  A robust protocol for building superpeer overlay topologies , 2004, Proceedings. Fourth International Conference on Peer-to-Peer Computing, 2004. Proceedings..

[17]  Philip S. Yu,et al.  Dynamic load balancing in geographically distributed heterogeneous Web servers , 1998, Proceedings. 18th International Conference on Distributed Computing Systems (Cat. No.98CB36183).

[18]  GhemawatSanjay,et al.  The Google file system , 2003 .

[19]  Naixue Xiong,et al.  Minimizing Power Consumption with Performance Efficiency Constraint in Web Server Clusters , 2009, 2009 International Conference on Network-Based Information Systems.