Optimal static load balancing in distributed computer systems
Journal of the ACM (JACM)
An Algorithm for Optimal Static Load Balancing in Distributed Computer Systems
IEEE Transactions on Computers
Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
Application-layer anycasting: a server selection architecture and use in a replicated Web service
IEEE/ACM Transactions on Networking (TON)
Temporal locality and its impact on Web proxy cache performance
Performance Evaluation - Special issue on internet performance modelling
The state of the art in locally distributed Web-server systems
ACM Computing Surveys (CSUR)
ProWGen: a synthetic workload generation tool for simulation evaluation of web proxy caches
Computer Networks: The International Journal of Computer and Telecommunications Networking
Modeling and analysis of power-tail distributions via classical teletraffic methods
Queueing Systems: Theory and Applications
Content Delivery Networks: Status and Trends
IEEE Internet Computing
Architecting noncooperative networks
IEEE Journal on Selected Areas in Communications
Packet-level traffic measurements from the Sprint IP backbone
IEEE Network: The Magazine of Global Internetworking
On the price of anarchy in unbounded delay networks
GameNets '06 Proceeding from the 2006 workshop on Game theory for communications and networks
Load balancing in processor sharing systems
Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools
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In this paper, we investigate the problem of optimal server selection in “content replication networks,” such as peer-to-peer (P2P) and content delivery networks (CDNs). While a number of server selection policies have been proposed or implemented, understanding of the theoretical performance limits of server selection and the relative performance of existing policies remains limited. In this paper, we introduce a mathematical framework, based on the M/G/1 Processor Sharing queueing model, and derive closed-form expressions for the optimal server access probabilities and the optimal average delay. We also analyze the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, that characterize a wide range of existing algorithms. We prove that the average delay achieved by these policies can theoretically be as much as N times larger than the optimal delay, where N is the total number of servers in the system. Furthermore, simulation results obtained using our M/G/1-PS workload model and the ProWGen Web workload generator show that the optimal policy can reduce the average delay of requests by as much as 30% as compared to EQ_LOAD and EQ_DELAY, in realistic scenarios. They also show that the optimal policy compares favorably to the other policies in terms of fairness and sensitivity to traffic parameters.