Abstract: Energy and delay are critical issues to any WSN. Among the many solutions till date, intelligent data forwarding has been extensively researched. This grounds us to consider a query routing tree to analyze the impact of schedule-based data transmissions to the sink. On the assumption of a hierarchical topology, our algorithm analyses and compares the route tree structure generated based on a pre-schedule to the usually adopted minimum spanning tree and Dijkstra algorithm-based routing trees. Our approach also analyses the impact of considering residual energy of the nodes. We apply both residual energies as well a pre-determined schedule to transmit data and observe that the energy conservation of the nodes is increased manifold. Keywords: Dijkstra algorithm, Energy conservation, Minimum spanning tree, Query routing tree, Wireless sensor networks. Scheduling Sensor Nodes for Enhancing Energy Savings in a Wireless Sensor Network Shashank Srigiri 1* , Rishabh Ranjan 2 and Itu Snigdh 3 1 Department of CSE, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India. Email: shashank10456@gmail.com 2 Department of CSE, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India. Email: rishabh.ranjan01567@gmail.com 3 Assistant Professor, Department of CSE, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India. Email: itusnigdh@bitmesra.ac.in *Corresponding Author I. IntroductIon A WSN essentially comprises of sensor nodes and a communicating interface. The sensor nodes are autonomous enough to decide which node to communicate to, given their energy level constraints and assigned sensing range. However, they are not intelligent enough to decide a schedule to forward data so as to minimize the network congestion or optimize the channel utilization. The associated intelligence in these contexts are added by means of scheduling algorithms or effcient MAC protocols [1], [2]. These approaches are usually either to reduce the energy expenses or to reduce the incurring delay in the transmission of data packets. As sensor nodes are responsible for forwarding messages and data to one another in the network, scheduling of sensor nodes for their effective utilization becomes critical for the overall network health. These constraints however are different for a query driven sensor network. In a query driven WSN network application, communication is initiated by the sink, and the data needs to travel from a source S to a destination D which is usually unidirectional or converge cast. This is so because every typical query based WSN has a coordinator or a sink to store the collected data and forward it for further processing and hence they control the fow of data in the network. The effciency of such WSNs depends on the coordinators’ potential to collaborate as well as the extent to which the decided route is robust against the typical WSN constraints like battery power, network congestion, connectivity issues and link unavailability. The initial phase of such sensor networks is its establishment if we assume that it would be static in nature once deployed. Post deployment, a query based WSN either arranges itself in the form of a graph or a hierarchical structure. The data and route queries in a query driven WSN are forwarded between the base station and the location where the target phenomenon has occurred or is observed as cited by Georgios et al. (2010) [9]. As data packets would be initiated only on the event of query initiated at the sink, it would result in lesser collision or contest for the channel thereby reducing the end to end delay. The frst approach for realizing a Q-WSN is based on a single hop approach where each sensor node directly communicates with the base station or the sink. We know that radio signals require a lot of power. Unlike messages running through wires, they decay in an accelerated manner. Also, as sound and radio decay according to the inverse square law [6], on doubling the distance we require four times the amount of power. The major limitation of this approach is severe energy depletion of the farther nodes and this eventually causes profound limitation in the lifetime of the network. This shortcoming of the direct communication approach is overcome by multi hop packet transmissions over short communication ranges. This approach saves energy considerably and reduces the communication interference among the nodes competing for channel access. In addition to these approaches, scheduling has also been widely adopted Journal of Network and Information Security 6 (2), December 2018, 05-09 http://www.publishingindia.com/jnis