Profit-Driven Service Request Scheduling in Clouds
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Modeling resource usage in planetary-scale shared infrastructures: PlanetLab's case study
Computer Networks: The International Journal of Computer and Telecommunications Networking
A node placement heuristic to encourage resource sharing in mobile computing
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part III
Decentralized proactive resource allocation for maximizing throughput of P2P Grid
Journal of Parallel and Distributed Computing
Profit-driven scheduling for cloud services with data access awareness
Journal of Parallel and Distributed Computing
Future Generation Computer Systems
Location-Based sponsored search advertising
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
Sharing hardware resources in heterogeneous computer-supported collaboration scenarios
Integrated Computer-Aided Engineering
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We study the problem of allocating shared resources, such as bandwidth in computer networks and computational resources in shared clusters, among multiple users by the proportional-share market mechanism. Under this mechanism, each user partitions his budget among the multiple resources and receives a fraction of each resource proportional to his bid. We first formulate the resource allocation game under the proportional-share mechanism and study the efficiency and fairness of the equilibrium in this game. We present analytic and simulation results demonstrating that the proportional-share mechanism achieves a reasonable balance of high degrees of efficiency and fairness at the equilibrium.