Heuristic Algorithms for Optimization of Task Allocation and Result Distribution in Peer-to-Peer Computing Systems

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

Optimization of P2P-based Distributed Systems

Various kinds of distributed systems gain much attention in recent years. One of the most significant example is the Peer-to-Peer (P2P) paradigm widely used in many applications including: file-sharing systems (e.g. BitTorrent), computing systems (e.g. SETI@home), communication systems (e.g. Skype) and many others. In this work we present our latest research related to the problem of P2P-based distributed systems optimization. We consider two following problems: optimization of data distribution P2P systems and optimization of P2P computing systems. For both problems we formulate Integer Programming models. Due to the complexity of these problems, exact methods can be applied only for relatively small instances. Therefore, we propose several heuristic algorithms including tabu search, evolutionary algorithm, constructive heuristic and random approach. Results of extensive numerical experiments show the effectiveness of proposed algorithms in comparison to optimal results yielded by CPLEX solver. The optimization methods presented in this paper can be used for optimization of various P2P systems