Maximizing Reliability of Heterogeneous Distributed System Using an Adapted Discrete Flower Pollination Algorithm for Task Allocation Problem

2018 21st Saudi Computer Society National Computer Conference (NCC) Pub Date : 2018-04-01 DOI:10.1109/NCG.2018.8593117

Farid Abbache, Hamoudi Kalla

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Abstract

Finding task allocation that maximizes reliability of a heterogeneous distributed system is an NP-hard problem. For that, meta-heuristic is used to get a sub optimal solution in reasonable time. The Flower Pollination algorithm is new meta-heuristic used successfully for solving different problems in different fields. The original Flower Pollination algorithm is designed to deal with continuous problem. Thus, applying this algorithm to discrete problems in its original form seems to be very hard or useless. In this paper, we propose an adapted discrete version of the Flower Pollination algorithm to deal with the problem of maximizing reliability of a heterogeneous distributed system under task allocation problem. This algorithm is called Adapted Discrete Flower Pollination algorithm (ADFP). To confirm the effectiveness of our algorithm, we have tested and compared its results with that of Hybrid Particle Swarm optimization (HPSO). The Experiments results show the effectiveness and superiority of ADFP over HPSO in all tested cases.

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基于自适应离散授粉算法的异构分布式系统可靠性最大化任务分配问题

如何使异构分布式系统的可靠性最大化是一个np难题。为此，采用元启发式算法在合理的时间内得到次优解。花授粉算法是一种新的元启发式算法，成功地解决了不同领域的不同问题。原始的传粉算法是为了处理连续问题而设计的。因此，将该算法以其原始形式应用于离散问题似乎非常困难或无用。在本文中，我们提出了一种离散版本的花授粉算法来处理任务分配问题下异构分布式系统的可靠性最大化问题。该算法被称为自适应离散花授粉算法(ADFP)。为了验证该算法的有效性，我们将其结果与混合粒子群算法(Hybrid Particle Swarm optimization, HPSO)进行了测试和比较。实验结果表明，在所有测试案例中，ADFP都优于HPSO。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2018 21st Saudi Computer Society National Computer Conference (NCC)

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