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

Grzegorz Chmaj; Krzysztof Walkowiak; Michał Tarnawski; Michał Kucharzak

International Journal of Applied Mathematics and Computer Science (2012)

- Volume: 22, Issue: 3, page 733-748
- ISSN: 1641-876X

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topGrzegorz Chmaj, et al. "Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems." International Journal of Applied Mathematics and Computer Science 22.3 (2012): 733-748. <http://eudml.org/doc/244054>.

@article{GrzegorzChmaj2012,

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 close to an optimum and can be used for larger problem instances than those solvable by CPLEX or other ILP solvers.},

author = {Grzegorz Chmaj, Krzysztof Walkowiak, Michał Tarnawski, Michał Kucharzak},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {P2P computing system; distributed computing; optimization; heuristics; evolutionary algorithms},

language = {eng},

number = {3},

pages = {733-748},

title = {Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems},

url = {http://eudml.org/doc/244054},

volume = {22},

year = {2012},

}

TY - JOUR

AU - Grzegorz Chmaj

AU - Krzysztof Walkowiak

AU - Michał Tarnawski

AU - Michał Kucharzak

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

JO - International Journal of Applied Mathematics and Computer Science

PY - 2012

VL - 22

IS - 3

SP - 733

EP - 748

AB - 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 close to an optimum and can be used for larger problem instances than those solvable by CPLEX or other ILP solvers.

LA - eng

KW - P2P computing system; distributed computing; optimization; heuristics; evolutionary algorithms

UR - http://eudml.org/doc/244054

ER -

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