Survey on anonymity in unstructured peer-to-peer systems
Journal of Computer Science and Technology
Optimal Power Management for Server Farm to Support Green Computing
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Dynamic resource selection heuristics for a non-reserved bidding-based Grid environment
Future Generation Computer Systems
An integrated security-aware job scheduling strategy for large-scale computational grids
Future Generation Computer Systems
An auction method for resource allocation in computational grids
Future Generation Computer Systems
Resource Selection in Large-Scale Distributed System Using Dynamic Task Sharing
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
Proceedings of the 20th international conference companion on World wide web
Resource scheduling methods for query optimization in data grid systems
ADBIS'11 Proceedings of the 15th international conference on Advances in databases and information systems
Reputation-based resource allocation in market-oriented distributed systems
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part I
International Journal of Computer Applications in Technology
Grid resource scheduling algorithm based on dynamic price-adjusting strategy
International Journal of Information and Communication Technology
Economy Based Resource Allocation in IaaS Cloud
International Journal of Cloud Applications and Computing
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A sustainable, market-like computational grid has two characteristics: it must allow resource providers and resource consumers to make autonomous scheduling decisions; and both parties of providers and consumers must have sufficient incentives to stay and play in the market. In this paper, we formulate this intuition of optimizing incentives for both parties as a dual-objective scheduling problem. The two objectives identified are to maximize the success rate of job execution, and to minimize fairness deviation among resources. The challenge is to develop a grid scheduling scheme that enables individual participants to make autonomous decisions while produces a desirable emergent property in the grid system, namely, the two objectives are achieved simultaneously. We present an incentive-based scheduling scheme which utilizes a peer-to-peer decentralized scheduling framework, a set of local heuristic algorithms, and three market instruments of job announcement, price, competition degree. The performance of this scheme is evaluated via extensive simulation using synthetic and real workloads. The results show that our approach outperforms other scheduling schemes in optimizing incentives for both consumers and providers, leading to highly successful job execution and fair profit allocation.