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A novel fuzzy programming approach for piece selection problem in P2P content distribution network.

M Anandaraj¹, P Ganeshkumar², S Naganandhini³

¹Department of Information Technology, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India.

Peerj. Computer Science

|January 10, 2024

Summary

This study introduces a novel fuzzy programming approach to optimize piece selection in dynamic peer-to-peer (P2P) networks. The method enhances download efficiency by considering multiple objectives like minimizing cost and time while maximizing speed and data transfer.

Keywords:

Content distribution networks Content management Data communication Fuzzy systems Overlay networks

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Area of Science:

Computer Science
Network Engineering
Artificial Intelligence

Background:

Piece selection is critical in dynamic peer-to-peer (P2P) networks to prevent the 'last piece problem'.
Current methods like BitTorrent's rarest-first policy have limitations due to localized piece rareness views.
The piece selection problem is inherently multi-objective, involving trade-offs between various performance metrics.

Purpose of the Study:

To develop a novel approach for solving the multi-objective piece selection problem in P2P networks.
To address the fuzzy nature of factors influencing piece selection decisions.
To provide an improved decision-making tool for peers in dynamic P2P environments.

Main Methods:

Formulated the piece selection problem as a fuzzy mixed-integer goal programming problem.
Incorporated objectives: minimizing download cost and time, maximizing speed and useful information transmission.
Considered realistic constraints: peer demand, capacity, and network dynamicity.

Main Results:

The proposed fuzzy programming approach effectively handles practical situations within a fuzzy environment.
Simulations demonstrated superior performance compared to existing methods.
Achieved significant improvements in download cost, download time, and the exchange of meaningful information.

Conclusions:

The novel fuzzy programming model offers a superior decision tool for optimal piece selection in dynamic P2P networks.
The approach effectively balances multiple, often fuzzy, objectives.
Outperforms existing strategies in key performance indicators, enhancing overall network efficiency.