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Optimizing security and quality of service in a Real-time database system using Multi-objective genetic algorithm

机译:使用多目标遗传算法优化实时数据库系统中的安全性和服务质量

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摘要

Both network security and quality of service (QoS) consume computational resource of IT system and thus may evidently affect the application services. In the case of limited computational resource, it is important to model the mutual influence between network security and QoS, which can be concurrently optimized in order to provide a better performance under the available computational resource. In this paper, an evaluation model is accordingly presented to describe the mutual influence of network security and QoS, and then a multi-objective genetic algorithm NSGA-II is revised to optimize the multi-objective model. Using the intrinsic information from the target problem, a new crossover approach is designed to further enhance the optimization performance. Simulation results validate that our algorithm can find a set of Pareto-optimal security policies under different network workloads, which can be provided to the potential users as the differentiated security preferences. These obtained Pareto-optimal security policies not only meet the security requirement of the user, but also provide the optimal QoS under the available computational resource. (C) 2016 Elsevier Ltd. All rights reserved.
机译:网络安全性和服务质量(QoS)都消耗IT系统的计算资源,因此显然可能影响应用程序服务。在计算资源有限的情况下,对网络安全性和QoS之间的相互影响建模是很重要的,可以同时优化它们,以便在可用的计算资源下提供更好的性能。本文提出了一种评估模型来描述网络安全性和QoS的相互影响,然后修改了多目标遗传算法NSGA-II以优化多目标模型。利用目标问题的内在信息,设计了一种新的交叉方法来进一步提高优化性能。仿真结果验证了我们的算法能够在不同的网络工作量下找到一组Pareto最优安全策略,这些策略可以作为不同的安全偏好提供给潜在用户。这些获得的帕累托最优安全策略不仅可以满足用户的安全需求,而且可以在可用的计算资源下提供最佳的QoS。 (C)2016 Elsevier Ltd.保留所有权利。

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