Search

We use a great deal of wireless sensor nodes to detect target signal that is more accurate than the traditional single radar detection method. Each local sensor detects the target signal in the region of interests and collects relevant data, and then it sends the respective data to the data fusion center (DFC) for aggregation processing and judgment making whether the target signal exists or not. However, the current judgment fusion rules such as Counting Rule (CR) and Clustering-Counting Rule (C-CR) have the characteristics on high energy consumption and low detection precision. Consequently, this paper proposes a novel Weight-based Clustering Decision Fusion Algorithm (W-CDFA) to detect target signal in wireless sensor network. It first introduces the clustering method based on tree structure to establish the precursor-successor relationships among the clusters in the region of interests and then fuses the decision data along the direction from the precursor clusters to the successor clusters gradually, and DFC (i.e., tree root) makes final determination by overall judgment values from subclusters and ordinary nodes. Simulation experiments show that the fusion rule can obtain more satisfactory system level performance at the environment of low signal to noise compared with CR and C-CR methods. [ABSTRACT FROM AUTHOR]

As an important constituent of wireless network planning, location area planning (LAP) directly affects the stability, security, and performance of wireless network. This work proposes a novel evolutionary algorithm(EA) to solve the LAP problem. The difference between the proposed algorithm and the previous EA is mainly how to encode. The new coding method is inspired by the famous four-color theorem in graph theory. Only four numbers are needed to encode all chromosomes by this method. The encoding and decoding process is fast and easy to implement. What is more, illegal solutions can be processed easily in the process of decoding. The design of effective and efficient genetic operators can also benefit from this coding method. The modified evolutionary algorithm with this coding method is especially effective for LAP problem. The use of the principle of fuzzy clustering in initialization can effectively compress the search space in this new algorithm. The computer simulation has been conducted, and the quality of proposed algorithm is confirmed by comparing the results of proposed algorithm with EA and simulated annealing (SA). [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSNET) can support various types of queries. The energy resource of sensors constrains the total number of query responses, called query capacity, received by the sink. There are four problems in the existing approaches for energy-efficient query processing in WSNETs: 1. the fact that sensors near the sink drain their energy much faster than distant sensors has been overlooked, 2. routing trees (RT) are rooted at the sink, and therefore, aggregative queries are less energy-efficient, 3. data reception cost has been ignored, and 4. flooding is used in query distribution or RT construction. In this paper, we propose a Broadcasting-Based query Scheme (BBS) to address the above problems. BBS reduces the energy depletion rate of sensors near the sink, builds different localized RTs for different query types, and eliminates the flooding cost of query distribution. Compared to the existing approaches, simulation studies show that BBS produces significant improvement in the query capacity for non-holistic queries (10%-100% capacity improvement) and holistic queries (up to an order of magnitude of capacity improvement). [ABSTRACT FROM AUTHOR]