A Survey on Mobile Charging Techniques in Wireless Rechargeable Sensor Networks

The recent breakthrough in wireless power transfer (WPT) technology has empowered wireless rechargeable sensor networks (WRSNs) by facilitating stable and continuous energy supply to sensors through mobile chargers (MCs). A plethora of studies have been carried out over the last decade in this regard. However, no comprehensive survey exists to compile the state-of-the-art literature and provide insight into future research directions. To fill this gap, we put forward a detailed survey on mobile charging techniques (MCTs) in WRSNs. In particular, we first describe the network model, various WPT techniques with empirical models, system design issues and performance metrics concerning the MCTs. Next, we introduce an exhaustive taxonomy of the MCTs based on various design attributes and then review the literature by categorizing it into periodic and on-demand charging techniques. In addition, we compare the state-of-the-art MCTs in terms of objectives, constraints, solution approaches, charging options, design issues, performance metrics, evaluation methods, and limitations. Finally, we highlight some potential directions for future research

Delay-Constrained Mobile Energy Charging in Wireless Sensor Networks

为了延长无线传感网的生存期,基于可充电的移动设备,研究设计了一种无线传感网中移动式能量补充的方法,移动节点可以在为传感器节点补充能量的同时收集数; 据.首先,通过将无线传感器网络监测区域分割为大小相同的子区域,该子区域内的节点组成一个簇;其次,以一个簇内的总能量为计算依据,设计移动节点的路径; 生成算法以确定能量高效的移动路线;最后,使用10种不同的随机网络拓扑图进行了仿真实验,以节点移动速度和时延为限制条件分别得到了对比数据.结果表明; ,本文提出的算法与NJNP( nearest-job-next with preemption)算法相比在时延相同的条件下( 800; s),生存期提升了6 000 s左右,在节点速度5 m/s条件下生存期提升了将近14 000; s.证明本文所提方法有效地提高了充电效率,延长了网络的生存期,可用于大规模的无线传感器网络.In order to prolong the lifetime of wireless sensor networks by using; energy-rechargeable mobile devices,this paper designs a mobile energy; replenishment method wherein a mobile element gathers data and recharges; sensors simultaneously. Firstly,the whole sensor network is divided into; several sub-regions equally and the sensors in each sub-region are; formed into a cluster. Secondly, considering the energy in a whole; cluster,the mobility path is designed to find the energy-efficient; mobile trace of the mobile element. Finally,in the simulation; experiment,we used ten different random network topologies to show the; comparisons with extensive simulation experiments under different; velocities and deadlines. The results indicate that the proposed; algorithm increases lifetime by approximately 6 000 s compared with; Nearest-Job-Next with Pre-emption( NJNP) under the deadline of 800 s.; Moreover,the proposed algorithm increases lifetime by approximately 14; 000 s compared with NJNP at velocity of 5 m/s. Thus,the proposed; algorithm can improve recharging efficiency and prolong the lifetime of; wireless sensor networks,which can be used in large-scale sensor; networks.国家自然科学基金资助项目; 福建省高等学校杰出青年科研人才培育计划资助项

Extending Wireless Rechargeable Sensor Network Life without Full Knowledge

When extending the life of Wireless Rechargeable Sensor Networks (WRSN), one challenge is charging networks as they grow larger. Overcoming this limitation will render a WRSN more practical and highly adaptable to growth in the real world. Most charging algorithms require a priori full knowledge of sensor nodes’ power levels in order to determine the nodes that require charging. In this work, we present a probabilistic algorithm that extends the life of scalable WRSN without a priori power knowledge and without full network exploration. We develop a probability bound on the power level of the sensor nodes and utilize this bound to make decisions while exploring a WRSN.We verify the algorithm by simulating a wireless power transfer unmanned aerial vehicle, and charging a WRSN to extend its life. Our results show that, without knowledge, our proposed algorithm extends the life of a WRSN on average 90% of what an optimal full knowledge algorithm can achieve. This means that the charging robot does not need to explore the whole network, which enables the scaling of WRSN. We analyze the impact of network parameters on our algorithm and show that it is insensitive to a large range of parameter values

Improving sensor network performance with wireless energy transfer

Through recent technology advances in the field of wireless energy transmission Wireless Rechargeable Sensor Networks have emerged. In this new paradigm for wireless sensor networks a mobile entity called mobile charger (MC) traverses the network and replenishes the dissipated energy of sensors. In this work we first provide a formal definition of the charging dispatch decision problem and prove its computational hardness. We then investigate how to optimise the trade-offs of several critical aspects of the charging process such as: a) the trajectory of the charger; b) the different charging policies; c) the impact of the ratio of the energy the Mobile Charger may deliver to the sensors over the total available energy in the network. In the light of these optimisations, we then study the impact of the charging process to the network lifetime for three characteristic underlying routing protocols; a Greedy protocol, a clustering protocol and an energy balancing protocol. Finally, we propose a mobile charging protocol that locally adapts the circular trajectory of the MC to the energy dissipation rate of each sub-region of the network. We compare this protocol against several MC trajectories for all three routing families by a detailed experimental evaluation. The derived findings demonstrate significant performance gains, both with respect to the no charger case as well as the different charging alternatives; in particular, the performance improvements include the network lifetime, as well as connectivity, coverage and energy balance properties

Mobile charging and data gathering in multiple sink wireless sensor networks: how and why

Recently, the problem of using efficient the number of mobile devices starting from multi-sink to go to charge and collect data of sensors such that sensors can work forever has received a great deal of attention in Wireless Rechargeable Sensor Network (WRSN). Many methods have been proposed for the WRSN systems such that mobile device can charge and collect data from sensors. However, most of previous works often require lots of mobile devices while the cost of mobile device is very high. In this paper, we investigate the Periodic Energy Replenishment and Data Collection with multiple sink (PERDCMS) problem and propose a new algorithm, called the Mobile Device Scheduling Algorithm (MDSA), to using limited number of mobile devices for charging and collecting data for sensors. Simulation results show that the MDSA has better performance than other method

Load Balanced AOMDV-An Enhancement to AOMDV Protocol

MANETs are one of the most challenging and growing search fields because of their demand and challenges in delivering services. Load balancing is one of MANET's key problems since network load balancing is essential for better network life, QoS, and congestion control. The approach proposed in the research emphasizes on load stability and the distribution of traffic on the network on the basis of energy of the nodes. The simulations are performed in NS2. The results show that the proposed algorithm was able to reach the distribution and performance of the battery pack without increasing overhead in the network. But Average remaining energy is still more in case of AOMDV which further leads to trade-off. The algorithm proposed has also managed to consume a balanced energy of all nodes in the network

Energy Efficient Algorithm for AOMDV with Load Balanced Feature

MANET is one of the most challenging and growing research fields due to their demand and challenges in the provision of services. Load balancing is one of the main problems of MANET since the load balancing of the network is essential for a better network life, QoS and congestion control. The approach proposed in the research emphasizes the stability of the load and the distribution of traffic in the network based on the energy of the nodes. The simulations are done in NS2. The results show that the proposed algorithm was able to reach the distribution and performance of the battery pack without increasing the overload in the network. But the average residual energy is even greater in the case of AOMDV, which leads to further compensation. The proposed algorithm has also managed to consume a balanced energy of all the nodes of the network

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