B.3. Communication/Networking and Information Technology
Ali Abdi Seyedkolaei
Abstract
Deploying multiple sinks instead of a single sink is one possible solution to improve the lifetime and durability of wireless sensor networks. Using multiple sinks leads to the definition of a problem known as the sink placement problem. In this context, the goal is to determine the optimal locations ...
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Deploying multiple sinks instead of a single sink is one possible solution to improve the lifetime and durability of wireless sensor networks. Using multiple sinks leads to the definition of a problem known as the sink placement problem. In this context, the goal is to determine the optimal locations and number of sink nodes in the network to maximize the network's lifetime. In this paper, we propose a dynamic sensor assignment algorithm to address the sink placement problem and evaluate its performance against existing solution methods on a diverse set of instances. We conducted experiments in two stages. In the first stage, based on random instances and compared to the exact computational method using the CPLEX solver, and in the second stage, based on real-world instances compared to MC-JMSP (Model-Based Clustering- Joint Multiple Sink Placement) method. The results obtained in the first stage of the experiments indicate the superiority of the dynamic sensor assignment algorithm in runtime for all instances. Furthermore, the solution obtained by the dynamic sensor assignment algorithm is very close to the solution obtained by the CPLEX solver. In particular, the percentage error of the solution found by the proposed method compared to CPLEX in all experimented instances is less than 0.15%, indicating the effectiveness of the proposed method in finding the appropriate solution for assigning sensors to sinks. Also, the results of the second stage experiments show the superiority of the proposed method in both execution time and energy efficiency compared to the MC-JMSP method.
Seyed Mojtaba Hosseinirad; S.K. Basu
Abstract
In this paper, we study WSN design, as a multi-objective optimization problem using GA technique. We study the effects of GA parameters including population size, selection and crossover method and mutation probability on the design. Choosing suitable parameters is a trade-off between different network ...
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In this paper, we study WSN design, as a multi-objective optimization problem using GA technique. We study the effects of GA parameters including population size, selection and crossover method and mutation probability on the design. Choosing suitable parameters is a trade-off between different network criteria and characteristics. Type of deployment, effect of network size, radio communication radius, density of sensors in an application area, and location of base station are the WSN’s characteristics investigated here. The simulation results of this study indicate that the value of radio communication radius has direct effect on radio interference, cluster-overlapping, sensor node distribution uniformity, communication energy. The optimal value of radio communication radius is not dependent on network size and type of deployment but on the density of network deployment. Location of the base station affects radio communication energy, cluster-overlapping and average number of communication per cluster head. BS located outside the application domain is preferred over that located inside. In all the network situations, random deployment has better performance compared with grid deployment.
