%0 Journal Article
%T A Transmission Power Self-Optimization Technique for Wireless Sensor Networks
%A F. Lavratti
%A A. Ceratti
%A D. Prestes
%A A. R. Pinto
%A L. Bolzani
%A F. Vargas
%A C. Montez
%A F. Hernandez
%A E. Gatti
%A C. Silva
%J ISRN Communications and Networking
%D 2012
%R 10.5402/2012/720286
%X Wireless sensor networks (WSNs) are generally used to monitor hazardous events in inaccessible areas. Thus, on one hand, it is preferable to assure the adoption of the minimum transmission power in order to extend as much as possible the WSNs lifetime. On the other hand, it is crucial to guarantee that the transmitted data is correctly received by the other nodes. Thus, trading off power optimization and reliability insurance has become one of the most important concerns when dealing with modern systems based on WSN. In this context, we present a transmission power self-optimization (TPSO) technique for WSNs. The TPSO technique consists of an algorithm able to guarantee the connectivity as well as an equally high quality of service (QoS), concentrating on the WSNs efficiency (Ef), while optimizing the transmission power necessary for data communication. Thus, the main idea behind the proposed approach is to trade off WSNs Ef against energy consumption in an environment with inherent noise. Experimental results with different types of noise and electromagnetic interference (EMI) have been explored in order to demonstrate the effectiveness of the TPSO technique. 1. Introduction Recent advancements in wireless communication and electronic technology have made possible the development of small, low-cost, low-power, and multifunctional sensor nodes [1, 2]. Wireless sensor networks (WSNs) are composed of communication nodes, which contain sensing, data processing, and communication components as well as power supply, typically a battery. In more detail, these nodes are able to collect different types of data and to communicate with each other. Nowadays, WSNs have been increasingly deployed for both civil and military applications which typically work in harsh environments. Considering sensor nodes, resources like processor, memory, and battery are generally restricted, since their replacement is considered prohibitive due to the hazardous and inaccessible places where they are supposed to operate [3]. In this scenario, where nodes are likely to operate on limited battery life, power conservation can be considered one of the most important issues [4]. Transmitting at unnecessary high power not only reduces the lifetime of the WSNs nodes but also introduces excessive interference. Thus, transmitting at the lowest possible power while preserving the network connectivity and reliability has become crucial points related to WSNs [4, 5]. In this paper, Ef is defined as the number of received messages by the master node (MN) in relation to the estimated number of
%U http://www.hindawi.com/journals/isrn.communications.networking/2012/720286/