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Trust-Based Service Composition and Binding with Multiple Objective Optimization in Service-Oriented Mobile Ad Hoc Networks

机译:面向服务的移动自组织网络中基于信任的服务组合和具有多目标优化的绑定

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With the proliferation of fairly powerful mobile devices and ubiquitous wireless technology, we see a transformation from traditional mobile ad hoc networks (MANETs) into a new era of service-oriented MANETs wherein a node can provide and receive services. Requested services must be decomposed into more abstract services and then bound; we formulate this as a multi-objective optimization (MOO) problem to minimize the service cost, while maximizing the quality of service and quality of information in the service a user receives. The MOO problem is an SP-to-service assignment problem. We propose a multidimensional trust based algorithm to solve the problem. We carry out an extensive suite of simulations to test the relative performance of the proposed trust-based algorithm against a non-trust-based counterpart and an existing single-trust-based beta reputation scheme. Our proposed algorithm effectively filters out malicious nodes exhibiting various attack behaviors by penalizing them with loss of reputation, which ultimately leads to high user satisfaction. Further, our proposed algorithm is efficient with linear runtime complexity while achieving a close-to-optimal solution.
机译:随着功能强大的移动设备和无处不在的无线技术的普及,我们看到了从传统的移动自组织网络(MANET)到面向服务的MANET的新时代的转变,在该时代中,节点可以提供和接收服务。必须将请求的服务分解为更抽象的服务,然后进行绑定;我们将其表述为多目标优化(MOO)问题,以最大程度地降低服务成本,同时最大程度地提高服务质量和用户接收的服务中信息的质量。 MOO问题是SP到服务的分配问题。我们提出了一种基于多维信任的算法来解决该问题。我们进行了广泛的仿真,以测试所提出的基于信任的算法相对于基于非信任的对等方和现有的基于单一信任的Beta信誉方案的相对性能。我们提出的算法通过惩罚信誉受损的恶意节点来有效过滤掉表现出各种攻击行为的恶意节点,最终导致很高的用户满意度。此外,我们提出的算法在线性运行时复杂度方面非常有效,同时实现了接近最佳的解决方案。

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