Enhanced resource discovery mechanisms for unstructured peer-to-peer network environments

This study explores novel methods for resource discovery in unstructured peer to-peer (P2P) networks. The objective of this study is to develop a lightweight resource discovery mechanism suitable to be used in unstructured P2P networks. Resource discovery techniques are examined and implemented in a...

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Bibliographic Details
Main Author: Azrul Amri Jamal (Author)
Format: Thesis Book
Language:English
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008 170115s2016 enk eng
040 |a UniSZA 
050 0 0 |a TK5105.525 
090 0 0 |a TK5105.525   |b .A97 2016 
100 0 |a Azrul Amri Jamal   |e author  
245 1 0 |a Enhanced resource discovery mechanisms for unstructured peer-to-peer network environments   |c Azrul Amri bin Jamal. 
264 0 |c 2016. 
300 |a xix, 147 leaves:   |b ill. (some col.);   |c 30 cm. 
336 |a text  |2 rdacontent 
337 |a unmediated  |2 rdamedia 
338 |a volume  |2 rdacarrier 
502 |a Thesis (Degree of Doctor of Philosophy) - Bangor University, 2016 
504 |a Includes bibliographical references (leaves 118-130) 
505 0 |a 1. Introduction -- 2. Literature review -- 3. Implementation of resource discovery mechanisms on Peer-to-Peer simulator -- 4. Unstructured P2P Network topology simulation -- 5. Alpha breadth first search 6. Lightweight blackboard resource discovery mechanism -- 7. Discussion & conclusions 
520 |a This study explores novel methods for resource discovery in unstructured peer to-peer (P2P) networks. The objective of this study is to develop a lightweight resource discovery mechanism suitable to be used in unstructured P2P networks. Resource discovery techniques are examined and implemented in a simulator with high scalability in order to imitate real-life P2P environments. Simulated topology generator models are reviewed and compared, the most suitable topology generator model is then chosen to test the novel resource discovery techniques. Resource discovery techniques in unstructured P2P networks usually rely on forwarding as many query messages as possible onto the network. Even though this approach was able to return many resources, the flooding of the network with query messages have an adverse effect on the network. Flooding the network has undesirable consequences such as degenerative performance of the network, waste of network resources, and network downtime. This study has developed alpha multipliers, a method of controlling query message forwarding to deal with the flooding effect of most resource discovery techniques in unstructured P2P networks. The combination of alpha multipliers and breadth-first search (BFS), a-BFS, was able to avoid the flooding effect that usually occurs with BFS. The a-BFS technique also increases the combined query efficiency compared to the original BFS. Aside from improving a uninformed search technique such as the BFS, this study also examines the network communication cost of several informed resource discovery techniques. Several issues that arise in informed resource discovery techniques, such as false positive errors, and high network communication costs for queries to update search results are discussed. This detailed analysis forms the basis of a lightweight resource discovery mechanism (LBRDM) that reduces the network communication cost by reducing the number of backward updates inside the network when utilising the blackboard resource discovery mechanism (BRDM). Simulations of BRDM and LBRDM show that the lightweight version can also return an almost identical combined query efficiency than the BRDM. The solution to control query message forwarding in a-BFS, and the removal of unnecessary exchange of information in LBRDM open a new perspective on simplifying resource discovery techniques. These approaches can be implemented on other techniques to improve the performance of resource discovery. 
610 2 0 |a Bangor University --   |x Dissertations  
650 0 |a Network computers  
650 0 |a Peer-to-peer architecture (Computer networks)  
710 2 |a Bangor University  
999 |a 1000167600  |b Thesis  |c Reference  |e Tembila Thesis Collection