Abstract
As wireless sensor networks (WSNs) are increasingly being deployed in some important applications, it becomes imperative that we consider application requirements in in-network processes. We intend to use a WSN to aid information querying and navigation within a dynamic and real-time environment. We propose a novel method that relies on the heat diffusion equation to finish the navigation process conveniently and easily. From the perspective of theoretical analysis, our proposed work holds the lower constraint condition. We use multiple scales to reach the goal of accurate navigation. We present a multi-scale gradient descent method to satisfy users’ requirements in WSNs. Formula derivations and simulations show that the method is accurately and efficiently able to solve typical sensor network configuration information navigation problems. Simultaneously, the structure of heat diffusion equation allows more flexibility and adaptability in searching algorithm designs.
Highlights
After the past decade of active research and field trials, wireless sensor networks (WSNs) have started penetrating into many areas of science, engineering, and our daily life
We have proposed a brand new heat diffusion equation to finish the navigation process conveniently and
Partitioned scales are used to reach the goal of the accurate navigation
Summary
After the past decade of active research and field trials, WSNs have started penetrating into many areas of science, engineering, and our daily life. We work on the information potential of using a sensor network to aid information querying and navigation through a dynamic and real-time environment. The construction and maintenance costs of these information potentials vary according to the high-frequency of queries to the data sources Most of these gradient-based methods [9,10,11,12] utilize the natural gradients of physical phenomena, since the spatial distribution of many physical quantities, such as temperature measurements for heat, follows a natural diffusion law. The information potential sets up a smooth ‘hill area’ (information potential field hill) with several local ‘peaks’; almost all nodes on this area are likely to have several ascending neighbors, and greater capacity to reach the different definitions.
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