<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Recently, distributed computing system have been gaining much attention due to a growing demand for various kinds of effective computations in both industry and academia. In this paper, we focus on Peer-to-Peer (P2P) computing systems, also called public-resource computing systems or global computing systems. P2P computing systems, contrary to grids, use personal computers and other relatively simple electronic equipment (e.g., the PlayStation console) to process sophisticated computational projects. A significant example of the P2P computing idea is the BOINC (Berkeley Open Infrastructure for Network Computing) project. To improve the performance of the computing system, we propose to use the P2P approach to distribute results of computational projects, i.e., results are transmitted in the system like in P2P file sharing systems (e.g., BitTorrent). In this work, we concentrate on offline optimization of the P2P computing system including two elements: scheduling of computations and data distribution. The objective is to minimize the system OPEX cost related to data processing and data transmission. We formulate an Integer Linear Problem (ILP) to model the system and apply this formulation to obtain optimal results using the CPLEX solver. Next, we propose two heuristic algorithms that provide results very</p></abstract>

Recently, distributed computing system have been gaining much attention due to a growing demand for various kinds of effective computations in both industry and academia. In this paper, we focus on Peer-to-Peer (P2P) computing systems, also called public-resource computing systems or global computing systems. P2P computing systems, contrary to grids, use personal computers and other relatively simple electronic equipment (e.g., the PlayStation console) to process sophisticated computational projects. A significant example of the P2P computing idea is the BOINC (Berkeley Open Infrastructure for Network Computing) project. To improve the performance of the computing system, we propose to use the P2P approach to distribute results of computational projects, i.e., results are transmitted in the system like in P2P file sharing systems (e.g., BitTorrent). In this work, we concentrate on offline optimization of the P2P computing system including two elements: scheduling of computations and data distribution. The objective is to minimize the system OPEX cost related to data processing and data transmission. We formulate an Integer Linear Problem (ILP) to model the system and apply this formulation to obtain optimal results using the CPLEX solver. Next, we propose two heuristic algorithms that provide results very

Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems

Department of Systems and Computer Networks, Faculty of Electronics Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Recently, distributed computing system have been gaining much attention due to a growing demand for various kinds of effective computations in both industry...

Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems

Published Online: Sep 28, 2012

Page range: 733 - 748

DOI: https://doi.org/10.2478/v10006-012-0055-0

Keywords
P2P computing system, distributed computing, optimization, heuristics, evolutionary algorithms

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems

Published Online: Sep 28, 2012

Page range: 733 - 748

DOI: https://doi.org/10.2478/v10006-012-0055-0

KeywordsP2P computing system, distributed computing, optimization, heuristics, evolutionary algorithms

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
P2P computing system, distributed computing, optimization, heuristics, evolutionary algorithms