Research Article Energy Measure Semigraph-Based Connected Edge Domination Routing Algorithm in Wireless Sensor Networks T. Suriya Praba , 1 T. Sethukarasi, 2 and S. Saravanan 3 1 School of Computing, SASTRA Deemed University, anjavur, India 2 Department of CSE, R. M. K. Engineering College, Gummidipoondi, India 3 Department of Mathematics, R. M. D. Engineering College, Chennai, India Correspondence should be addressed to T. Suriya Praba; suriyathiyagarajan03@gmail.com Received 4 June 2019; Revised 16 October 2019; Accepted 29 October 2019; Published 27 November 2019 Academic Editor: Adrian Kliks Copyright © 2019 T. Suriya Praba et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In wireless sensor networks (WSNs), batteries are used as power source which is limited, and replacement of the battery is difficult. Since communication between nodes consumes most of the node power, topology-based power control is essential for reducing energy consumption. It is necessary to use optimized topology-based energy control model, so the selected nodes are used to generate a virtual backbone, which reduces unwanted routing of data. e virtual backbone for optimized topology can be created by connected dominating set (CDS) of graph theory. However, generating the virtual backbone by using the CDS algorithm is an NP-hard problem because of larger network size. To overcome this problem, in this paper, a novel distributed connected edge dominating set-based semigraph model (S-CEDS) is proposed. e performance ratio of the proposed S-CEDS is measured as (4 + ln ′) |opt|, where |opt| represents the network size. e proposed S-CEDS is implemented using the ns-2 simulator and evaluated with conventional routing protocols such as AODV and DSDV. e results show that the proposed S-CEDS approach increases throughput and network lifetime. Also, it reduces energy consumption and average number of hops required for data transmission. 1. Introduction Wireless sensor networks (WSNs) have caught the eye of researchers, as a result of the major developments being made in the field of embedded systems [1, 2]. WSN refers to the group of dedicated sensor nodes which are spatially dispersed and deployed. Deployed sensors measure envi- ronmental conditions like temperature, pressure, humidity, and sound. WSNs are similar to wireless ad hoc networks because they do not rely on any fixed infrastructure, as formation of their network will be done spontaneously with wireless connectivity. In WSN, the most demanding task is the conservation of energy. e major work of sensor nodes is classified as sensing, processing the sensed data, and communicating the sensed information with the peers. Since the communication module consumes most of the sensor energy, it could be controlled by effective topology con- struction. But WSNs are ad hoc in nature, so this makes the task of topology construction and designing the routing protocols a challenging one. However, this can be achieved with virtual backbone overlay network modeling in WSN. In this model, the selected nodes are considered for virtual backbone construction, and CDS (connected dominating set) of graph theory is used for making the virtual backbone by considering the network as the graph and sensor nodes as the vertices of the graph [3, 4]. is is done because the CDS can extend the lifetime of the wireless network, thus keeping the energy depletion and deportation rate at a minimum. An interconnected subset of nodes that are put up in the entire network to aid routing is called the virtual backbone [5, 6]. In WSNs, the nodes can use these backbones for communication between them since there is no established architecture for centralized control. We can define a dominating set (DS) of a network as a small subset of nodes such that each node either belongs to the subset or to the neighbor of some elements in that subset. e CDS, which is formed by connecting the nodes of the DS, is essentially responsible for the passage of messages Hindawi Mobile Information Systems Volume 2019, Article ID 4761304, 10 pages https://doi.org/10.1155/2019/4761304