— In a Wireless Sensor Network, the most significant parameter of sensor nodes is Energy. One of the demanding concerns in WSNs is Energy Efficiency. The solution to this problem is data aggregation which will decrease the network traffic. Data aggregation can be achieved by using Clustering Schemes which is an essential research area, because it provides multiple benefits such as it upgrades constancy and reduces the network overhead that prolongs the lifespan of the network. The major idea behind the clustering scheme is to deploy the sensor nodes in the network, compress the data gathered from the sensor nodes and then transfers the gathered data to the sink. Cluster head selection is the fundamental part in this procedure. Several Cluster Head Selection Techniques are considered in this paper. This paper proposed a fuzzy interface system which has used to choose a cluster head on the basis of different input parameters given to it. In this method, automated method has followed for the selection. Experimental analysis have performed between proposed, SEP and LEACH protocol on the basis of number of alive nodes, number of dead nodes and throughput. From the analysis, it has been concluded that the proposed technique enhances the lifetime of the network in comparison with other traditional methods

ii Acknowledgements iii Dedication iv List of Figures vii List of Tables ix List of Algorithms x List of Acronyms xi Chapter

With the progress of society and economic development and the expanding deployment scale of substations, the automatic monitoring of the foundation settlement in construction station becomes an important issue of the operation and maintenance in the power grid. BeiDou satellite navigation system is a global navigation and positioning system, which is independently developed to provide navigation, positioning, and timing services in China and its surrounding areas. This article describes the principles of BeiDou high-precision positioning. According to the land subsidence monitoring and warning requirements for substations, multi-antenna technology is introduced in order to solve the problem of the cost of large-scale land subsidence monitoring system. The monitoring interface software is designed to visually reflect the settlement situation. The monitoring system can effectively improve the monitoring efficiency and early warning capability of the ground subsidence in the power company’s substation. The system will also provide a basis for decision-making management and improve the reliability, safety, and stability of power grid operation based on high-precision field accuracy and trend.

With the deepening of wireless sensor network (WSN) applied in various services in smart substation, high data rate and quality of service has become the new research focus. For smart substation equipment condition monitoring, the paper designs clustered smart substation equipment monitoring network based on wireless sensor network. Reference to Zigbee protocol and IEC 61850 relevant regulations, data flow model of monitoring network is built. Combined with OPNET simulation function, QoS of monitoring network is proposed form the three aspects of user perceived QoS, network QoS and node QoS. There are end-to-end delay, MAC delay, MAC throughput, MAC data dropped, collision, packet loss ratio, bit error rate, signal/noise ratio and received power. According to the actual configuration of substation equipment monitoring, simulation network model is built. The analysis shows that QoS comprehensive performance of clustered network has better than tree network and Mesh network.

We propose a load balanced and energy aware routing protocol (LEAR) that is designed to improve the lifetime of large-scale wireless sensor mesh networks by balancing the energy consumption in the nodes. The proposed protocol selects routes to enable equitable traffic distribution across the nodes so that all nodes maintain similar expected lifetimes. We implement LEAR in a commercially available wireless sensor platform and perform extensive experimental evaluations of different aspects of the protocol in the laboratory. Our results show that LEAR can significantly improve the lifetime of large-scale wireless sensor networks that typically experience a high degree of load imbalance and inefficient resource utilization when using a link quality based routing protocol.

We propose a joint power control and quality aware routing scheme for rechargeable wireless sensor networks (WSNs) that are characterized by a high degree of spatial and temporal variations of energy resources. The proposed scheme adapts the energy consumption in the nodes to meet their corresponding energy resources with the objective of attaining network wide reliability of operations. This is achieved by dynamically controlling the transmission powers and route selection. Some initial performance evaluations are presented from experimental studies to show the effectiveness of the proposed scheme.

We propose a joint channel selection and quality aware routing scheme for multi-channel wireless sensor networks to improve the network lifetime. A data collection traffic pattern is assumed, where all sensor nodes perform periodic sensing and forward data to a centralized base station (sink). The proposed scheme achieves improvement of the battery lifetime by reducing the energy consumed from overhearing and also by dynamically balancing the battery lifetimes of nodes. Performance evaluations are presented from experimental studies as well as from extensive simulation studies to show the effectiveness of the proposed scheme.

We propose a joint channel selection and quality aware routing scheme for multi-channel wireless sensor networks that apply asynchronous duty cycling to conserve energy, which is common in many environmental monitoring applications. Energy resources may vary from node to node due to differential consumption as well as availability, as observed in rechargeable sensor networks. A data collection traffic pattern is assumed, where all sensor nodes periodically forward sensor data to a centralized base station (sink). Under these assumptions, the effect of overhearing dominates the energy consumption of the nodes. The proposed scheme achieves lifetime improvement by reducing the energy consumed in overhearing and also by dynamically balancing the lifetimes of nodes. Performance evaluations are presented from experimental tests as well as from extensive simulation studies, which show that the proposed scheme reduces overhearing by ∼60% with just 2 channels without significantly affecting the network performance.

We propose a RSSI based localization scheme for wireless sensor networks that mitigates the effects of shadowing caused by obstacles that are scattered in the field of operation. The proposed scheme applies a spatial correlation mechanism to eliminate RSSI signals that are affected by obstructions. The effectiveness of the proposed scheme is validated using simulations as well as some initial experimental results.

We propose PCOR, a power control and routing scheme for rechargeable wireless sensor networks (WSNs) that are characterized by spatial and temporal variations of energy resources. The proposed scheme is applied to asynchronous WSNs where overhearing plays a dominant role in the energy consumption. PCOR performs quality aware route selection while reducing the energy consumption in sensor nodes that have low remaining battery life through cooperative and network-wide adaptations of transmit power levels and parent selection. Performance evaluations are presented from extensive simulation studies as well as from an experimental testbed.

We consider wireless sensor networks with data collection traffic that apply asynchronous duty cycling to conserve energy, which is common in many environmental monitoring applications. Under these assumptions, the effect of overhearing dominates the energy consumption of the nodes. We propose multichannel operation with dynamic channel selection and power control for reducing the effect of overhearing in such asynchronous networks. A mathematical model is presented to calculate the maximum network lifetime under these considerations.

We consider the channel assignment problem in multi-channel wireless sensor networks for maximizing the network lifetime. We assume a data collection traffic pattern where all nodes forward data periodically to a sink and propose a distributed channel selection scheme that tries to maximize the lifetime of the nodes by controlling the energy consumption from overhearing. Some initial experimental results are included to show the effectiveness of the proposed scheme.

The work reported in this thesis is concerned with the design, development and testing of a wireless 802.11 condition monitoring sensor for an electrical substation environments. The work includes a comprehensive literature review and the design and development of a novel continuous wireless data acquisition sensor. Laboratory and field tests were performed to evaluate the data acquisition performance of the developed wireless sensor. The sensor‟s wireless immunity to interference performance was also evaluated in laboratory and field tests. The literature survey reviews current condition monitoring practices in electrical substation environments with a focus on monitoring high voltage insulators and substation earth impedance. The data acquisition performance of the wireless sensor was tested in a laboratory using two artificially polluted insulators, in a fog chamber that applied clean fog. Analysis of the test results were found to be in good agreement with those recorded directly through a data acquisition card and transmitted via coaxial cable. The wireless impedance measurement of a 275kV transmission earth tower base field test was also performed and was found to be in agreement with previous published results from standard earth measurements. The sensor‟s wireless interference performance was evaluated at a field test site when no high voltage experiments were taking place. The sensors wireless interference performance was then tested in a laboratory environment before and during high voltage tests taking place. The results of these tests were compared to each other and to published results. These tests demonstrate the suitability of the sensor‟s design and its immunity to interference. The experimental work conducted using the developed wireless sensor has led to an understanding that continuous wireless data acquisition is possible in high voltage environments. However, novel condition monitoring systems that make use of such wireless sensors, have to take into account data losses and delays adequately. Furthermore, a solar power source was designed and constructed to be used for outdoor substation applications and the solar battery charging performance of the wireless sensor was tested in a solar laboratory.

The quality of service is severely degraded by coverage holes in wireless sensor networks. This paper focuses on the coverage hole healing (CHH) problem for big data collection in a large-scale wireless sensor network (LS-WSN) where the LS-WSN containing both static sensors and mobile sensors with the topology control of LEACH algorithm. Meanwhile, the data volume transmitted by each sensor node may be inconsistent. Specifically, the target of the CHH problem is to find an optimal subset of mobile nodes from all mobile nodes while maximizing the transmission times (TT) that all dispatched mobile nodes can transmit in their lifetime. Hence, from the data-centric perspective, we propose a greedy healing algorithm (GHA) via the greedy-based heuristic strategy with low computational complexity to solve this CHH problem. Simulation results show that the proposed GHA can efficiently heal the coverage holes which significantly prolongs the network lifetime and observably enhances the quality of service (QoS) of WSNs while increasing the TT, transmitted data volume (TDV) and average residual energy of all dispatched mobile nodes.

The quality of service (QoS) and lifetime of wireless sensor networks (WSNs) are severely degraded by coverage holes generated by random deployment or battery exhaustion of sensors. This work firstly introduces a novel confident information coverage CIC) model to dramatically reduce the density of sensor nodes and accurately detect confident information coverage holes (CICHs). Then, the problem of repairing confident information coverage holes (RCICHs) for big data collection in a large-scale heterogeneous WSN (LS-HWSN) which widely spreads over a geographic area with thousands of stationary sensor nodes and mobile sensor nodes is formulated, called as RCICH problem, which is to effectively repair CICHs considering that the transmitted data velocity of sensor nodes is different. Furthermore, we prove it to be NP-completeness. The target of the problem is to find a subset of mobile sensor nodes from all mobile sensor nodes while minimizing the amount of lost throughputs LTs) of all dispatched mobile sensor nodes or maximizing the amount of repairing transmission times (RTTs) for all dispatched mobile sensor nodes, with different objectives. Finally, based on the CIC model and the data-centric perspective, two heuristic schemes including a centralized dispatch scheme and a distributed dispatch scheme are proposed to effectively solve the RCICH problem. Simulation results show that the proposed schemes effectively repair CICHs while increasing the QoS and lifetime of the LS-HWSN with the topology control of a fan-shaped clustering (FSC) protocol.

The poor computation ability and limited storage of power of nodes have seriously restricted wireless sensor network (WSN) applied to smart substation equipment condition monitoring. According to the application of substation equipment condition monitoring, clustering network model for equipment monitoring is proposed. And single-hop and multi-hop network consumption model is established respectively. Then using group search optimization algorithm, energy consumption optimization problem is analyzed under the influence of equipment monitoring network coverage, number of network nodes, node sensing radius and the distance of equipment monitoring node to information fusion node, information fusion node to sink node, in order to achieve minimal node cluster and cluster-head energy consumption. Compared to the particle swarm optimization, the simulation results show that the GSO algorithm is simpler and easier to implement, and has better performance in terms of convergence and computation speed. The results have direct reference value for optimization design of smart substation equipment condition monitoring used in WSN.

The next generation electricity grid, i.e. the smart grid, will integrate significant sensing capabilities including distributed data collection and sensing infrastructures. Wireless Sensor Networks (WSNs) have been widely considered as promising candidates for monitoring and control applications in the smart grid. However, with the proliferation of sensing entities, utilities need to efficiently manage the data collected from these sensors in order to optimize the utilization of communication networks, as well as reduce their response times to minimize the duration and impact of failures and service interruptions. To this end, this paper introduces a behavioral multi-agent-based approach for managing sensor networks' information in smart grids. In particular, we are interested in sensor networks deployed for monitoring applications. We propose PriBaCC, an in-network data processing approach allowing to only retain and communicate significant data to the concerned entities, while reducing communication over-head. Simulation results show that the proposed approach provides a scalable and efficient data management solution for WSNs monitoring applications in smart grids.

The majority of low-cost and off-the-shelf Wireless Sensor Networks (WSNs) solutions cannot adequately address issues related to an unattended deployment in a harsh environment, especially if the network needs to scale and achieve high density or high coverage or both. This is usually the case in environmental applications. In this chapter, this problem is investigated and extensive discussion on the pros and cons of a specific WSN design is presented. However, before moving from generic and well-established WSN solutions to customization, a detailed analysis of the gains of having a tailored design is necessary. Accordingly, a case study involving sparse deployments in outdoors is used to illustrate the process.

The electrical power grid has recently been embracing the advances in Information and Communication Technologies (ICT) for the sake of improving efficiency, safety, reliability and sustainability of electrical services. For a reliable smart grid, accurate, robust monitoring and diagnosis tools are essential. Wireless Sensor Networks (WSNs) are promising candidates for monitoring the smart grid, given their capability to cover large geographic regions at low-cost. On the other hand, limited battery lifetime of the conventional WSNs may create a performance bottleneck for the long-lasting smart grid monitoring tasks, especially considering that the sensor nodes may be deployed in hard to reach, harsh environments. In this context, recent advances in Radio Frequency (RF)-based wireless energy transfer can increase sustainability of WSNs and make them operationally ready for smart grid monitoring missions. RF-based wireless energy transfer uses Electromagnetic (EM) waves and it operates in the same medium as the data communication protocols. In order to achieve timely and efficient charging of the sensor nodes, we propose the Sustainable wireless Rechargeable Sensor network (SuReSense). SuReSense employs mobile chargers that charge multiple sensors from several landmark locations. We propose an optimization model to select the minimum number of landmarks according to the locations and energy replenishment requirements of the sensors.

The Smart Grid (SG) is conceived as the evolution of the current electrical grid representing a big leap in terms of efficiency, reliability and flexibility compared to today's electrical network. To achieve this goal, the Wireless Sensor Networks (WSNs) are considered by the scientific/engineering community to be one of the most suitable technologies to apply SG technology to due to their low-cost, collaborative and long-standing nature. However, the SG has posed significant challenges to utility operators—mainly very harsh radio propagation conditions and the lack of appropriate systems to empower WSN devices—making most of the commercial widespread solutions inadequate. In this context, and as a main contribution, we have designed a comprehensive ad-hoc WSN-based solution for the Smart Grid (SENSED-SG) that focuses on specific implementations of the MAC, the network and the application layers to attain maximum performance and to successfully deal with any arising hurdles. Our approach has been exhaustively evaluated by computer simulations and mathematical analysis, as well as validation within real test-beds deployed in controlled environments. In particular, these test-beds cover two of the main scenarios found in a SG; on one hand, an indoor electrical substation environment, implemented in a High Voltage AC/DC laboratory, and, on the other hand, an outdoor case, deployed in the Transmission and Distribution segment of a power grid. The results obtained show that SENSED-SG performs better and is more suitable for the Smart Grid than the popular ZigBee WSN approach.