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Implementing a Trust and Reputation Model for Robotic Sensor Networks

机译:为机器人传感器网络实现信任和信誉模型

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摘要

Robotic sensor networks (RSNs) can be described as networks of devices equipped with communication, sensing and actuation capabilities. Successful implementations of RSNs require tackling challenging problems lying at the intersection of robotics, communication and perception. In addition, RSNs resemble human societies and emerging intelligent multi-agent systems in some respects. In these collaborative distributed systems, each node decides which to interact with and forms a network with other nodes in order to improve the quality of the decisions. In order to achieve this goal, trust and reputation models are of practical use. In this paper, a trust and reputation model for RNSs is proposed. Also, performance evaluations of the model in comparison with well-known models in the literature are given to prove its effectiveness. The results of the performance evaluations prove that the proposed model is successful in RSNs comprising of a large number of sensor nodes. In addition, the processing and memory requirements of the proposed model are moderate and the system runs effectively in systems with low processing power and limited main memory.
机译:机器人传感器网络(RSN)可以描述为配备有通信,传感和致动功能的设备网络。 RSN的成功实施需要解决机器人技术,通信技术和感知技术交汇处的挑战性问题。此外,RSN在某些方面类似于人类社会和新兴的智能多代理系统。在这些协作分布式系统中,每个节点决定与其他节点进行交互并与其他节点形成网络,以提高决策质量。为了实现这个目标,信任和声誉模型是实际使用的。本文提出了RNS的信任和信誉模型。此外,与文献中的已知模型相比,对该模型的性能进行了评估,以证明其有效性。性能评估的结果证明,所提出的模型在包含大量传感器节点的RSN中是成功的。此外,所提出模型的处理和内存要求适中,并且系统在处理能力低且主内存有限的系统中有效运行。

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