## 1 Introduction  
In recent years, the demand for wireless sensor networks has increased for many industrial applications such as fault diagnosis and monitoring, surveillance monitoring, industrial control systems, commodity consumption monitoring and plant automation, etc. [1]. In addition, in industrial applications, wireless sensor networks have many medical, military, civil and environmental applications as well body area network monitoring [2], civil structure monitoring [3], target tracking in battlefields [4], earthquake and flood monitoring [5], forest fire monitoring [6], etc. The technological progression in the field of highly integrated digital sensor electronics, small scale microprocessors, low power transceivers and radio frequency devices, collectively resulted in the design of efficient wireless sensors [7]. These wireless sensor devices are responsible for sensing the change in required physical phenomena of their surrounding environment with the help of a small microprocessor, radio transceiver, a few transducers and a low capacity battery [7]. The transducers or sensors perform the specific type of sensing in the surrounding environment and pass the sensing information to a microprocessor for further processing of sensed data [7]. A wireless sensor's radio transceiver is used to transmit and receive the sensed data to/from adjacent wireless sensors or to/from the sink node, depending upon the location of the wireless sensor in the field [7]. Due to low battery capacity, wireless sensor nodes have to adjust their sleep-awake cycle (or working-sleeping cycle) according to scenario requirements in order to maximize the network life time and minimize the overall network delay [8]. The possible existence of these miniaturized wireless sensor devices motivated researchers to emphasize the significance of wireless sensor node collaboration for data sensing, data collection and aggregation purposes which resulted in the discovery of an emerging field known as wireless sensor network (WSN). The purpose of deploying multiple wireless sensor nodes in a field is to have collaboration between these sensor nodes to achieve a shared goal with the help of sensing, data aggregation and data sharing between wireless sensor nodes [9]. The frequent transmission failures, electricity theft and congestion problems in traditional electric grids lead to the consideration that traditional electric grids are insecure and inefficient in terms of energy management. In order to eradicate these problems, we need to incorporate state-of-the-art bidirectional communication interfaces, automated control systems and distributed computing capabilities in our current grid, which will improve energy efficiency, reliability, security and agility in our electric grid [10]. Furthermore, a highly integrated next generation system is needed in which electricity service providers, distributors and prosumers are well aware of real-time energy requirements and capabilities; the system which offers high performance computing, security, scalability, reliability and security with state-of-the-art communication network infrastructure is our \"smart grids\" (SGs) [10; 11]. For better realization of SGs, we need to distribute and gather information remotely and in a timely manner from different phases of our SGs (i.e., generation, transmission, distribution and consumption) [10; 11; 12]. The data acquisition from different devices deployed in the neighborhood area network (NAN) can be efficiently achieved by incorporating WSN in SGs. The upgradation of contemporary electric grids to SGs could be supported by self-governing and self-organizing features of WSN [13]. A traditional electric grid needs installation of costly and inefficient wired monitoring systems, expensive communication cables and a high-maintenance budget [10].