Reputation-based dependable scheduling of workflow applications in Peer-to-Peer Grids

  • Authors:
  • Mustafizur Rahman;Rajiv Ranjan;Rajkumar Buyya

  • Affiliations:
  • Cloud Computing and Distributed Systems (CLOUDS) Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia;Service Oriented Computing (SOC) Research Group, School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia;Cloud Computing and Distributed Systems (CLOUDS) Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2010

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Abstract

Grids facilitate creation of wide-area collaborative environment for sharing computing or storage resources and various applications. Inter-connecting distributed Grid sites through peer-to-peer routing and information dissemination structure (also known as Peer-to-Peer Grids) is essential to avoid the problems of scheduling efficiency bottleneck and single point of failure in the centralized or hierarchical scheduling approaches. On the other hand, uncertainty and unreliability are facts in distributed infrastructures such as Peer-to-Peer Grids, which are triggered by multiple factors including scale, dynamism, failures, and incomplete global knowledge. In this paper, a reputation-based Grid workflow scheduling technique is proposed to counter the effect of inherent unreliability and temporal characteristics of computing resources in large scale, decentralized Peer-to-Peer Grid environments. The proposed approach builds upon structured peer-to-peer indexing and networking techniques to create a scalable wide-area overlay of Grid sites for supporting dependable scheduling of applications. The scheduling algorithm considers reliability of a Grid resource as a statistical property, which is globally computed in the decentralized Grid overlay based on dynamic feedbacks or reputation scores assigned by individual service consumers mediated via Grid resource brokers. The proposed algorithm dynamically adapts to changing resource conditions and offers significant performance gains as compared to traditional approaches in the event of unsuccessful job execution or resource failure. The results evaluated through an extensive trace driven simulation show that our scheduling technique can reduce the makespan up to 50% and successfully isolate the failure-prone resources from the system.