Gerenciamento autonômico de energia em redes de sensores sem fio através do escalonamento de atividade dos nós

Abstract

he evolution and development of new devices, increasingly cheaper and more efficient, expanded the use of Wireless Sensor Networks (WSN) and encouraged the creation of new applications in the contemporary scenery of Ubiquitous and Pervasive Computing. However, energy limitation remains a challenge in the field of WSN. This situation is aggravated even more by the infeasibility of energy recharge since, in many cases, WSN are used in inaccessible enviroments. With cheapness devices used in WSN, became easier to employ dense and large-scale networks in environments that will be monitored. The use of dense networks, which have a high degree redundancy of nodes, allows the network remains functional even with the exhaustion of some nodes. In addition to provide fault tolerance, the use of very dense networks offer the opportunity of implementing scheduling mechanisms for redundant nodes, in a way that the network lifetime is even better optimized. Assuming a scenery with very dense networks, this dissertation describes the implementation of an autonomic scheduling mechanism, simple, robust and scalable, in order to further improve the results already presented by BiO4SeL, which is a routing protocol based on Ant Colony and designed to maximize the network lifetime. The results show that the new scheduling scheme effectively improves the WSN lifetime based on BiO4SeL in dense scenarios.