Research Article VCH-ECCR: A Centralized Routing Protocol for Wireless Sensor Networks Rohit Pachlor and Deepti Shrimankar Department of Computer Science & Engineering, Visvesvaraya National Institute of Technology, Nagpur, Maharashtra 440010, India Correspondence should be addressed to Rohit Pachlor; rohit.pachlor@gmail.com Received 19 June 2017; Revised 24 September 2017; Accepted 8 October 2017; Published 14 December 2017 Academic Editor: Hana Vaisocherova Copyright © 2017 Rohit Pachlor and Deepti Shrimankar. This 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. A wireless sensor network (WSN) is a collection of hundreds to thousands of compact, battery-operated sensors. It is deployed to accumulate useful information from the nearby environment. Depending upon the type of application, the sensors have to work for months to years with a finite energy source. In some extreme environments, the replacement of energy source is challenging and sometimes not feasible. Therefore, it is vital for sensors to perform their duties in an energy efficient way to improve the longevity of the network. This paper proposes an energy-efficient centralized cluster-based routing protocol called Vice-Cluster- Head-Enabled Centralized Cluster-based Routing protocol (VCH-ECCR). The VCH-ECCR uses a two-level hierarchy of vice cluster heads to use the energy of sensors efficiently and to cut back the frequency of the clustering. The performance of VCH- ECCR is compared with low-energy adaptive clustering hierarchy (LEACH), LEACH-Centralized (LEACH-C), and base station controlled dynamic clustering protocol (BCDCP). The experimental results show that the VCH-ECCR outperforms over its comparative in terms of network lifetime, overall energy consumption, and throughput. 1. Introduction When deployed in a target area, sensors monitor the sur- rounding events and cooperatively communicate monitored information to a base station (BS) [1]. The sensors are equipped with limited energy, communication, sensing, and processing resources. The size and cost of sensors limit their resources. The size of a sensor may differ from a brick such as a weather station to a microscopic particle such as a tooth sensor. The cost of a sensor also varies with the extent of required capabilities—high for powerful sensors (equipped with complex hardware resources) and low for simple sen- sors. Changes in the size and cost of the sensor directly change the sensor’s resource limitations [2]. The battery is the most precious and critical resource of a sensor as it has a significant impact on the overall lifetime of a WSN. Therefore, sensors must be operated in an energy effi- cient manner [3]. After deployment, the possible ways through which the energy consumption of a sensor node can be reduced are the following: (i) Data aggregation [4, 5]: readings of nearby sensors are spatially correlated. Data aggregation eliminates this redundant data transmission thereby reducing the bandwidth usage and energy consumption of the network. The energy consumption of a sensor is directly proportional to the number of packets sent by the node. (ii) Reduce transmission power [6, 7]: the energy con- sumption of a sensor is directly proportional to the distance at which it transmits data. It can be reduced by adjusting the transmission power of the sensor and transmitting data at short distances. Sensors are capable of dynamically controlling their trans- mission power. (iii) Save idle time and energy [8]: sensors which send data periodically can save substantial idle time and energy using duty cycles. The sensor turns on its radio component at times depending on whether it has data to transmit or not. Hindawi Journal of Sensors Volume 2017, Article ID 8946576, 10 pages https://doi.org/10.1155/2017/8946576