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Wireless Network has become the critical part of the communication infrastructure in our environment. Nowadays, the using of mobile computing devices such as laptops and Wi-Fi enabled phones in the workplace is increasing. The design of wireless networks for enterprise environments remains a challenging task due to the problem of topological design. In this paper, we discuss the computational aspects of the task of calculation the various criteria of efficiency wireless networks' topology. These criteria determine the different characteristics of wireless networks - the access level of populations to network services, the level of the distributed signal and the level of signal accepted in the city. We use brute force algorithm for comparing the different criteria of efficiency the topology of wireless networks. The brute force algorithm has high computational complexity therefore in our experiments we use parallel computing to solve the problem. For illustration the results we use the task of optimization the Wireless network topology for fragment of Myanmar territory.
The paper discusses utilisation of the brute force methods for the task of towers distribution in wireless communication systems. The proposed algorithm allows to find an optimal allocation of a tower between the settlements. A simple wireless communication has been used as an example to investigate the functionality of the algorithm's software.
Wireless sensor networks are widely used in a variety of fields including industrial environments. In case of a clustered network the location of cluster head affects the reliability of the network operation. Finding of the optimum location of the cluster head, therefore, is critical for the design of a network. This paper discusses the optimisation approach, based on the brute force algorithm, in the context of topology optimisation of a cluster structure centralised wireless sensor network. Two examples are given to verify the approach that demonstrate the implementation of the brute force algorithm to find an optimum location of the cluster head.