Wireless Sensor Networks (WSN) have largely integrated all areas, including the military and civil fields. Their main limitation is their energy resources, which are very limited. Charging or replacing their batteries is often complicated or impossible, due to the high costs involved. The development of new approaches to energy management techniques for these autonomous systems has identified two strategic categories of energy management classification. The first category "Software" targets the development of algorithms for routing protocols to make transmissions smarter and more energy-efficient. The second category "Hardware", focused more on new energy recovery technologies, has drawn the attention of academicians and industrialists because they bring a new manner of energy storage with life extension performance. Furthermore, this category has inspired new ways of supporting WSN administered applications such as real-time processes. In this paper, we review different current sources of Energy Harvesting Technologies and Strategies with WSN (EHTS-WSN) and their various areas of applications. Our review provided a current analysis and future prospects for energy harvesting purposes in WSN. Hence, we propose that it would be required to ensure a compromise that combined the ''Software'' and ''Hardware'' designs of WSN in order to optimize energy consumption and therefore the lifetime of the network.

Wireless sensor network (WSN) is a group of small sensor nodes deployed for physical environment measurement. The main features of these small sensor nodes are their limited capabilities in term of the energy reserve, the processing ability and the memory storage. So that, the data gathering protocols design for WSN is a crucial challenge since those protocols should be simple, energy-aware, and scalable. They should also be self-configurable to node failures and changes of the network topology dynamically. In this paper, we present a new algorithm for gathering sensor readings based on short chain forming. To allow network lifetime extension, the short chain is used, instead of starting from the furthest node and using greedy algorithm as PEGASIS do. Thus, the network lifetime is increased compared to PEGASIS, which is proved through simulation results.