On neighbor-selection strategy in hybrid peer-to-peer networks

Koo, Simon G. M.; Kannan, Karthik; Lee, C. S. George

doi:10.1016/j.future.2006.02.015

Cited by 46 publications

(28 citation statements)

References 5 publications

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“…Koo et. al [21] introduced a neighbour selection algorithm for improving the efficiency of content transfer with the strategy of grouping peer nodes. Despite the fact that unstructured P2P approaches are more resilient in dynamic environments, the efficiency of these unstructured P2P approaches is still far lower than DHTs.…”

Section: Small World Overlay In Peer-to-peer Networkmentioning

confidence: 99%

Fault-tolerant peer-to-peer search on small-world networks

Liu¹,

Antonopoulos²,

Mackin³

2007

Future Generation Computer Systems

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This paper presents small world architecture for P2P networks (SWAN) for content discovery in multi-group P2P systems. A semi-structured P2P algorithm of SWAN is utilized to create and find long-range shortcuts toward remote peer groups. In SWAN, not every peer node needs to be connected to remote groups, but every peer node can easily find which peer nodes have external connections to a specific peer group. From our analysis and simulation, SWAN has the advantages of both structured and unstructured P2P networks and can achieve good performance in both stable and dynamic environments.Keywords: Peer-to-peer; Small world; Information search IntroductionMost early Internet applications are distributed using client/server architecture that has a series of drawbacks, such as performance bottlenecks and low fault tolerance. On the contrary, peer-to-peer (P2P) architecture does not rely on centralized servers to provide access to services and offers an appealing alternative to the client/server model, especially for large-scale distributed applications. This paper presents small world architecture for P2P networks (SWAN) for resource discovery and discovery in multi-group P2P systems. A semi-structured P2P algorithm of SWAN is used to create and discover long-range shortcuts between different peer groups, which can satisfy the following requirements of design:(1) Not every peer node needs to connect to other peer groups;(2) Each peer node needs to know or can easily find which peer nodes have external connections to which peer groups; 3 (3) External links to other peer groups need to be distributed within the peer group and cannot be centralized in one or a few peer nodes.The rest of paper is organized as follows: Section 2 discusses related work. Section 3 presents the SWAN algorithms. The small-world properties of SWAN are analysed in Section 4. The performance evaluation and simulations are given in Section 5 and Section 6, respectively. We conclude the work in Section 7. Related Work Resource Discovery in Peer-to-Peer NetworksExisting P2P solutions for resource discovery can be generally classified into two categories: structured and unstructured P2P systems. Distributed hash tables (DHTs) have become the dominant methodology for resource discovery in structured P2Pnetworks [5]. The observed problem of most DHTs is that the cost of maintaining a consistent distributed index is too high in dynamic environments [6]. Some structured P2P protocols (e.g. Kademlia [7]) are beginning to seek ways to save the cost of maintaining a consistent index. In contrast, unstructured P2P systems (e.g. Gnutella) do not control data placement and are more resilient in dynamic environments, but current unstructured P2P search techniques tend to either require high search overhead or generate massive network traffic.In contrast, SWAN uses a semi-structured P2P search method combining the techniques of both structured and unstructured search methods. SWAN does not strictly rely on DHTs. It can find the requested data inside and ...

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Section: Small World Overlay In Peer-to-peer Networkmentioning

confidence: 99%

Fault-tolerant peer-to-peer search on small-world networks

Liu¹,

Antonopoulos²,

Mackin³

2007

Future Generation Computer Systems

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“…Kooa et al model the neighborhood selection problem using an undirected graph and attempted to determine the connections between the peers [6]. Given a fixed number of N peers, we use a graph G = (V, E) to denote an overlay network, where the set of vertices V = {v 1 , · · · , v N } represents the N peers and the set of edges E = {e ij ∈ {0, 1}, i, j = 1, · · · , N } represents their connectivities : e ij = 1 if peers i and j are connected, and e ij = 0 otherwise.…”

Section: Neighbor-selection Problem In P2p Networkmentioning

confidence: 99%

“…A common difficulty in the current P2P systems is caused by the dynamic membership of peer hosts. This results in a constant reorganization of the topology [3], [12], [13], [14], [15].…”

Section: Introductionmentioning

confidence: 99%

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A Particle Swarm Optimization Algorithm for Neighbor Selection in Peer-to-Peer Networks

Sun

Abraham

Zhang

et al. 2007

6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07)

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“…Based on existing research [15,16,17,18,19,20], we formulate the neighborselection problem for P2P networks. We introduce first the model of P2P networks, and then discuss metrics for measuring neighbor selection.…”

Section: Neighbor-selection Problem In P2p Networkmentioning

confidence: 99%

Peer-to-Peer Neighbor Selection Using Single and Multi-objective Population-Based Meta-heuristics

Liu

Abraham

Xhafa

Studies in Computational Intelligence

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Summary. Peer-to-peer (P2P) topology has significant influence on the performance, search efficiency and functionality, and scalability of the application. In this Chapter, we introduce the problem of neighbor selection in peer-to-peer networks using two population based meta-heuristics: Particle Swarm Optimization (PSO) algorithms and Genetic Algorithms (GAs). Both a single objective and a multi-objective problem are formulated, and then the P2P neighbor selection problem is defined. We present the neighbor selection strategy based on PSO and GA algorithm. Each particle encodes the upper half of the peer-connection matrix through the undirected graph, which reduces the search space dimension. We also discuss the characteristics of ergodicity during particle swarm searching process. We also illustrate the algorithm performance and trace its feasibility and effectiveness with the help of some examples.

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On neighbor-selection strategy in hybrid peer-to-peer networks

Cited by 46 publications

References 5 publications

Fault-tolerant peer-to-peer search on small-world networks

Fault-tolerant peer-to-peer search on small-world networks

A Particle Swarm Optimization Algorithm for Neighbor Selection in Peer-to-Peer Networks

Peer-to-Peer Neighbor Selection Using Single and Multi-objective Population-Based Meta-heuristics

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