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Response Threshold Model-Based Device Assignment for Cooperative Resource Sharing in a WSAN

机译:WSAN中基于响应阈值模型的协作资源共享的设备分配

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Many researchers have been attracted by a wireless sensor and actuator network (WSAN) for its wide range of applications. In a WSAN, embedded sensors detect and conjecture environmental and personal conditions and actuators provide users with information services and environmental control which are suited for time, place, occasion, and people. Since it apparently is wasteful and redundant to deploy an independent WSAN for each of envisioned applications, building a multi-purpose WSAN consisting of heterogeneous sensors and actuators and sharing them among applications are considered promising. However, we need a mechanism to effectively share available resources among concurrent applications while taking into account application requirements and resources. Although there are several proposals on centralized or deterministic device assignment mechanisms, they suffer from difficulty in designing an appropriate set of rules with fine-tuned parameters. In this paper, we propose a fully distributed and self-organizing device assignment mechanism by adopting a response threshold model, which imitates division of labors in a colony of social insects. Our proposal does not require deterministic and complicated rules and appropriate device assignment emerges as a consequence of autonomous decision of individual nodes. Through simulation experiments, we confirmed the our proposal accomplishes as effective device assignment as an existing deterministic mechanism and our proposal is less sensitive to parameter setting errors.
机译:无线传感器和执行器网络(WSAN)因其广泛的应用而吸引了许多研究人员。在WSAN中,嵌入式传感器检测并推测环境和个人状况,执行器为用户提供适合时间,地点,场合和人员的信息服务和环境控制。由于为每个预想的应用程序部署独立的WSAN显然是浪费和冗余的,因此,构建由异构传感器和执行器组成的多功能WSAN并在应用程序之间共享它们被认为是有希望的。但是,我们需要一种机制来在并发应用程序之间有效共享可用资源,同时考虑到应用程序需求和资源。尽管有一些关于集中式或确定性设备分配机制的建议,但它们在设计带有微调参数的适当规则集时遇到困难。在本文中,我们通过采用响应阈值模型来模拟社交昆虫群落中的分工,提出了一种完全分布式且自组织的设备分配机制。我们的建议不需要确定性和复杂的规则,并且由于各个节点的自主决策而出现了适当的设备分配。通过仿真实验,我们确认了我们的建议能够像现有的确定性机制一样实现有效的设备分配,并且我们的建议对参数设置错误不那么敏感。

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