The world of internet of things (IoT) and automation has been catching a robust pace to impact wide range of commercial and domestic applications for some time now. The IoT holds ad-hoc or wireless sensor networks (WSNs) at its very primary implementation level, the hardware level. The increasing requirement of these networks demands a renewed and better design of the network that improves the already existing setbacks of WSNs, which is mainly the power consumption and optimization. Routing highly affects the power consumed in the nodes in WSNs, hence having a modified routing algorithm which is specific to the application and meets its needs, particularly it is a good approach instead of having a generalized existent routing approach. Currently, for WSN having adequate number of nodes, routing involves maximum number of nodes and hops so as to reduce power consumption. However, for restricted areas and limited nodes, this scenario concludes with using up more number of nodes simultaneously resulting in reducing several batteries simultaneously. A routing algorithm is proposed in this paper for such applications that have a bounded region with limited resources. The work proposed in this paper is motivated from the routing algorithm positional attribute based next-hop determination approach (PANDA-TP) which proposes the increase in number of hops to reduce the requirement of transmission power. The aim of the proposed work is to compute the distance between the sending and receiving node and to measure the transmission power that would be required for a direct(path with minimum possible hops) and a multi-hop path. If the node is within the thresh-hold distance of the source, the packet is undoubtedly transferred directly; if the node is out of the thresh-hold distance, then the extra distance is calculated. Based on this, the power boosting factor for the source node, and if necessary, then the extra number of nodes that would be required to transmit is determined. An extra decision-making step is added to this approach which makes it convenient to utilize in varied situations. This routing approach suits the current level of robustness that the WSNs demand.
LQG Control via Wireless Sensor Networks with Minimal Transmission Power
