Wireless Power Transfer and Data Collection in Wireless Sensor Networks

In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using Wireless Power Transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, while the other nodes waste their harvested energy, which is more than they need to transmit their packets. In this paper, we investigate a novel optimal scheduling strategy, called EHMDP, aiming to minimize data packet loss from a network of sensor nodes in terms of the nodes' energy consumption and data queue state information. The scheduling problem is first formulated by a centralized MDP model, assuming that the complete states of each node are well known by the base station. This presents the upper bound of the data that can be collected in a rechargeable wireless sensor network. Next, we relax the assumption of the availability of full state information so that the data transmission and WPT can be semi-decentralized. The simulation results show that, in terms of network throughput and packet loss rate, the proposed algorithm significantly improves the network performance.Comment: 30 pages, 8 figures, accepted to IEEE Transactions on Vehicular Technolog

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

Networking Protocols For Energy Harvesting Wireless Sensor Networks

Ph.DDOCTOR OF PHILOSOPH

Data and Energy Integrated Communication Networks for Wireless Big Data

This paper describes a new type of communication network called data and energy integrated communication networks (DEINs), which integrates the traditionally separate two processes, i.e., wireless information transfer (WIT) and wireless energy transfer (WET), fulfilling co-transmission of data and energy. In particular, the energy transmission using radio frequency is for the purpose of energy harvesting (EH) rather than information decoding. One driving force of the advent of DEINs is wireless big data, which comes from wireless sensors that produce a large amount of small piece of data. These sensors are typically powered by battery that drains sooner or later and will have to be taken out and then replaced or recharged. EH has emerged as a technology to wirelessly charge batteries in a contactless way. Recent research work has attempted to combine WET with WIT, typically under the label of simultaneous wireless information and power transfer. Such work in the literature largely focuses on the communication side of the whole wireless networks with particular emphasis on power allocation. The DEIN communication network proposed in this paper regards the convergence of WIT and WET as a full system that considers not only the physical layer but also the higher layers, such as media access control and information routing. After describing the DEIN concept and its high-level architecture/protocol stack, this paper presents two use cases focusing on the lower layer and the higher layer of a DEIN network, respectively. The lower layer use case is about a fair resource allocation algorithm, whereas the high-layer section introduces an efficient data forwarding scheme in combination with EH. The two case studies aim to give a better explanation of the DEIN concept. Some future research directions and challenges are also pointed out

Resource Allocation Challenges and Strategies for RF-Energy Harvesting Networks Supporting QoS

This paper specifically addresses the resource allocation challenges encountered in wireless sensor networks that incorporate RF energy harvesting capabilities, commonly referred to as RF-energy harvesting networks (RF-EHNs). RF energy harvesting and transmission techniques bring substantial advantages for applications requiring Quality of Service (QoS) support, as they enable proactive replenishment of  wireless devices. We commence by providing an overview of RF-EHNs, followed by an in-depth examination of the resource allocation challenges associated with this technology. In addition, we present a case study that focuses on the design of an efficient operating strategy for RF-EHN receivers. Our investigation highlights the critical aspects of service differentiation and QoS support, which have received limited attention in previous research. Besides, we explore previously unexplored areas within these domains

Bandwidth and Power Management in Broadband Wireless Networks

Bandwidth and power are considered as two important resources in wireless networks. Therefore, how to management these resources becomes a critical issue. In this thesis, we investigate this issue majorally in IEEE 802.16 networks. We first perform performance analysis on two bandwidth request mechanisms defined in IEEE 802.16 networks. We also propose two practical performance objectives. Based on the analysis, we design two scheduling algorithm to achieve the objectives. Due to the characteristics of popular variable bit rate (VBR) traffic, it is very difficult for subscriber stations (SSs) to make appropriate bandwidth reservation. Therefore, the bandwidth may not be utilized all the time. We propose a new protocol, named bandwidth recycling, to utilized unused bandwidth. Our simulation shows that the proposed scheme can improve system utilization averagely by 40\%. We also propose a more aggressive solution to reduce the gap between bandwidth reservation and real usage. We first design a centralized approach by linear programming to obtain the optimal solution. Further, we design a fully distributed scheme based on game theory, named bandwidth reservation (BR) game. Due to different quality of service (QoS) requirements, we customize the utility function for each scheduling class. Our numerical and simulation show that the gap between BR game and optimal solution is limited. Due to the advantage of dynamical fractional frequency reuse (DFFR), the base station (BS) can dynamically adjust transmission power on each frequency partition. We emphasis on power allocation issue in DFFR to achieve most ecomicical data transmission. We first formulate the problem by integer linear programming (ILP). Due to high computation complexity, we further design a greedy algorithm. Our simulation shows that the results of the greedy algorithm is very close to the ILP results