Radio Access Techniques for Energy Effcient and Energy Harvesting based Wireless Sensor Networks

Traditional Wireless Sensor Networks (WSN) rely on batteries with finite stored energy. In the future with billions of such devices, it will be difficult to replace and dispose their batteries, which can cause a huge environmental threat. Hence, research is being done to eliminate batteries from sensor devices and replace them with harvesters. These harvesters can power the sensor network nodes by extracting energy from ambient sources. Harvesters are already being implemented in many real-life applications like structural health monitoring, environment monitoring and body area networks. A sensor network of multiple energy harvesting enabled devices is known as Energy Harvesting based Wireless Sensor Network (EH-WSN). For uninterrupted operation of EH-WSN, radio protocols must consider the energy harvesting constraints; (i) energy harvesting process unpredictability and; (ii) energy harvesting rate variations in time and space. EH-WSN comes with unique traits which discourage the use of existing WSNs radio protocols, as most of existing protocols are focussed on decreasing the energy consumption and increasing the network lifetime. This thesis work focusses on modifying an existing energyefficient Multipath Rings (MPR) routing protocol for low-power and low-bandwidth EH-WSN and evaluating its performance through simulations. Firstly, the topology setup phase is revised by implementing a new ring formation scheme for better data reliability. Secondly, controlled flooding of data packets is used by enabling selective forwarding, which leads to decrease in network traffic and overall energy consumption. Lastly, every node is equipped with a neighbors’ table on-board which helps in making energy-related routing decisions in multi-hop networks. A periodic energy update packet transmission helps in keeping latest neighbor information. This modified version of MPR routing protocol is called Energy Harvesting based Multipath Rings (EH-MPR) routing. This work also provides a comprehensive survey on existing MAC and Routing protocols for energy efficient and energy harvesting based WSNs. Through this work, the main constraints on using existing energy-efficient protocols for EH-WSN are discussed and depicted with the help of network simulations. The effects of using fixed duty cycle for energy harvesting enabled sensor nodes are outlined by simulating T-MAC (adaptive duty cycle) against S-MAC (fixed duty cycle). For all evaluation metrics, T-MAC outperformed S-MAC. Using Castalia’s realistic wireless channel and radio model, EH-MPR is simulated for low-power, low-data rate and low bandwidth (1 MHz) networks where satisfactory results are obtained for sub-GHz frequencies (433 MHz and 868 MHz). Next, the modified EH-MPR protocol is compared with original MPR routing under practical deployment scenarios. The metrics in consideration are successful packet transmissions, energy consumption, energy harvested-to-consumed ratio and failed packets. After thorough simulations, it was concluded that although the packet success rate is approximately equal for both protocols, EH-MPR has advantages over original MPR routing protocol in terms of energy cost and uninterrupted operations

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer

Radio frequency (RF) energy harvesting and transfer techniques have recently become alternative methods to power the next generation of wireless networks. As this emerging technology enables proactive replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service (QoS) requirement. This article focuses on the resource allocation issues in wireless networks with RF energy harvesting capability, referred to as RF energy harvesting networks (RF-EHNs). First, we present an overview of the RF-EHNs, followed by a review of a variety of issues regarding resource allocation. Then, we present a case study of designing in the receiver operation policy, which is of paramount importance in the RF-EHNs. We focus on QoS support and service differentiation, which have not been addressed by previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design

The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application

An Energy Driven Architecture for Wireless Sensor Networks

Most wireless sensor networks operate with very limited energy sources-their batteries, and hence their usefulness in real life applications is severely constrained. The challenging issues are how to optimize the use of their energy or to harvest their own energy in order to lengthen their lives for wider classes of application. Tackling these important issues requires a robust architecture that takes into account the energy consumption level of functional constituents and their interdependency. Without such architecture, it would be difficult to formulate and optimize the overall energy consumption of a wireless sensor network. Unlike most current researches that focus on a single energy constituent of WSNs independent from and regardless of other constituents, this paper presents an Energy Driven Architecture (EDA) as a new architecture and indicates a novel approach for minimising the total energy consumption of a WS