• DocumentCode
    245738
  • Title

    Agent Based Resource Discovery for Peak Request Periods in Peer-to-Peer Grid Infrastructures

  • Author

    Olaifa, Moses ; Van Der Merwe, Ronell ; Mapayi, Temitope

  • Author_Institution
    Sch. of Comput., Univ. of South Africa, Johannesburg, South Africa
  • fYear
    2014
  • fDate
    19-21 Dec. 2014
  • Firstpage
    1000
  • Lastpage
    1005
  • Abstract
    One of the fundamentally required services in the grid environment is resource discovery. The discovery involves the search for appropriate resources that match user requirements. An efficient mechanism for this service still remains a crucial problem especially within a dynamic and scalable environment such as the grid. Majority of the proposed solutions based on centralized and hierarchical approaches suffer from shortcomings ranging from single point of failure to network congestion. In this paper, we propose a resource discovery mechanism that relies on the activities of an agent during peak request hours in a peer-to-peer (P2P) based grid system. The agent searches and learns the paths to requested resources with associated maximum rewards. These paths are managed by the super-node for subsequent resource discovery requests. We evaluated the performance of the proposed approach against some resource discovery approaches. The results show an improved performance in the proposed algorithm over the Time To Live (TTL) and and Adjacency List and Ant Colony Algorithm (GAA).
  • Keywords
    ant colony optimisation; grid computing; hierarchical systems; learning (artificial intelligence); peer-to-peer computing; GAA; TTL; adjacency list; agent based resource discovery; ant colony algorithm; centralized approach; hierarchical approach; peak request periods; peer-to-peer grid infrastructures; time to live; Educational institutions; Equations; History; Learning (artificial intelligence); Markov processes; Mathematical model; Peer-to-peer computing; Markov Decision Problem; Peer-to-peer; grid; reinforcement learning; resource discovery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-7980-6
  • Type

    conf

  • DOI
    10.1109/CSE.2014.199
  • Filename
    7023709