Optimal Transmit Power in Wireless Sensor Networks

Power conservation is one of the most important issues in wireless ad hoc and sensor networks, where nodes are likely to rely on limited battery power. Transmitting at unnecessarily high power not only reduces the lifetime of the nodes and the network, but also introduces excessive interference. It is in the network designer's best interest to have each node transmit at the lowest possible power while preserving network connectivity. In this paper, we investigate the optimal common transmit power, defined as the minimum transmit power used by all nodes necessary to guarantee network connectivity. This is desirable in sensor networks where nodes are relatively simple and it is difficult to modify the transmit power after deployment. The optimal transmit power derived in this paper is subject to the specific routing and medium access control (MAC) protocols considered; however, the approach can be extended to other routing and MAC protocols as well. In deriving the optimal transmit power, we distinguish ourselves from a conventional graph-theoretic approach by taking realistic physical layer characteristics into consideration. In fact, connectivity in this paper is defined in terms of a quality of service (QoS) constraint given by the maximum tolerable bit error rate (BER) at the end of a multihop route with an average number of hops.     

Energy Optimization in Multihop Wireless Embedded and Sensor Networks

This paper provides an analytical model for the study of energy consumption in multihop wireless embedded and sensor networks where nodes are extremely power constrained. Low-power optimization techniques developed for conventional ad hoc networks are not sufficient as they do not properly address particular features of embedded and sensor networks. It is not enough to reduce overall energy consumption, it is also important to maximize the lifetime of the entire network, that is, maintain full network connectivity for as long as possible. This paper considers different multihop scenarios to compute the energy per bit, efficiency and energy consumed by individual nodes and the network as a whole. The analysis uses a detailed model for the energy consumed by the radio at each node. Multihop topologies with equidistant and optimal node spacing are studied. Numerical computations illustrate the effects of packet routing, and explore the effects of coding and medium access control. These results show that always using a simple multihop message relay strategy is not always the best procedure.     

无线网络能效的优化与评估

文章从能效测度入手,对已有的无线网络能效测度评价体系进行了讨论,并提出以碳排放量为标准和与网络负载相结合的能效测度模型。在能效测度模型的基础上,文章提出减少设备使用、无线资源调度、节点协作等一系列无线网络能效优化方法,并建议在无线网络协议架构中加入能效监控和能效评估模块。文章还对无线网络能效优化和评估方法中存在的技术挑战进行了展望。     

面向能耗控制的无线传感器网络节点协议优化

能量受限是无线传感器网络一个显著的特征。对网络进行能耗优化并延长网络生命周期是无线传感器网络研究的重点。提出了面向能耗控制的无线传感器网络节点协议优化方法。针对网络中数据发送所占较大的能耗比重,通过对协议优化,对发送功率的参数设置方法进行改进,改变以往发射功率的固定参数设置法,通过终端节点之间的距离动态调整发送功率的方法,以达到节省能耗并延长网络生命周期的目的。仿真和实验结果表明,改进后的发射功率动态参数设置法较改进之前的固定参数设置方法能更多地节约网络能耗。     

Distributed Energy Optimization for Target Tracking in Wireless Sensor Networks

Energy constraint is an important issue in wireless sensor networks. This paper proposes a distributed energy optimization method for target tracking applications. Sensor nodes are clustered by maximum entropy clustering. Then, the sensing field is divided for parallel sensor deployment optimization. For each cluster, the coverage and energy metrics are calculated by grid exclusion algorithm and Dijkstra's algorithm, respectively. Cluster heads perform parallel particle swarm optimization to maximize the coverage metric and minimize the energy metric. Particle filter is improved by combining the radial basis function network, which constructs the process model. Thus, the target position is predicted by the improved particle filter. Dynamic awakening and optimal sensing scheme are then discussed in dynamic energy management mechanism. A group of sensor nodes which are located in the vicinity of the target will be awakened up and have the opportunity to report their data. The selection of sensor node is optimized considering sensing accuracy and energy consumption. Experimental results verify that energy efficiency of wireless sensor network is enhanced by parallel particle swarm optimization, dynamic awakening approach, and sensor node selection.     

Energy Efficiency Routing with Node Compromised Resistance in Wireless Sensor Networks

For the energy limited wireless sensor networks, the critical problem is how to achieve the energy efficiency. Many attackers can consume the limited network energy, by the method of capturing some legal nodes then control them to start DoS and flooding attack, which is difficult to be detected by only the classic cryptography based techniques with common routing protocols in wireless sensor networks (WSNs). We argue that under the condition of attacking, existing routing schemes are low energy-efficient and vulnerable to inside attack due to their deterministic nature. To avoid the energy consumption caused by the inside attack initiated by the malicious nodes, this paper proposes a novel energy efficiency routing with node compromised resistance (EENC) based on Ant Colony Optimization. Under our design, each node computes the trust value of its 1-hop neighbors based on their multiple behavior attributes evaluation and builds a trust management by the trust value. By this way, sensor nodes act as router to achieve dynamic and adaptive routing, where the node can select much energy efficiency and faithful forwarding node from its neighbors according to their remaining energy and trust values in the next process of data collection. Simulation results indicate that the established routing can bypass most compromised nodes in the transmission path and EENC has high performance in energy efficiency, which can prolong the network lifetime.     

Variable Bit Rate Flow Routing in Wireless Sensor Networks

Since energy constraint is a fundamental issue for wireless sensor networks, network lifetime performance has become a key performance metric for such networks. In this paper, we consider a two-tier wireless sensor network and focus on the flow routing problem for the upper tier aggregation and forwarding nodes (AFNs). Specifically, we are interested in how to perform flow routing among the nodes when the bit rate from each source node is time-varying. We present an algorithm that can be used to construct a flow routing solution with the following properties: (1) If the average rate from each source node is known a priori, then flow routing solution obtained via such algorithm is optimal and offers provably maximum network lifetime performance; (2) If the average rate of each source node is unknown but is within a fraction (epsiv) of an estimated rate value, then network lifetime by the proposed flow routing solution is within 2epsiv/1-epsiv from the optimum. These results fill in an important gap in theoretical foundation for flow routing in energy-constrained sensor networks.     

Joint Optimization of Power,Packet Forwarding and Reliability in MIMO Wireless Sensor Networks

In this paper, we study the reliable packet forwarding in Wireless Sensor Networks (WSNs) with the multiple-input multiple-output (MIMO) and orthogonal space time block codes (OSTBC) techniques. The objective is to propose a cross-layer optimized forwarding scheme to maximize the Successful Transmission Rate (STR) while satisfying the given end-to-end power consumption constraint. The channel coding, power allocation, and route planning are jointly considered to significantly improve the transmission quality in terms of STR. The joint optimization design is formulated as a global deterministic optimization and also a local stochastic optimization issues. It is found that the stochastic optimization approach can effectively model, analyze, and solve the routing problem. In order to substantially reduce the implementation complication of the global optimization, we propose a low-complexity distributed scheme. The determination of relaying nodes and power budgets are decoupled, i.e. performing route planning and power allocation separately. We have shown that the result in the distributed scheme is able to provide sufficiently accurate predication of the global optimization. In addition, the proposed scheme can clearly reduce the Symbol Error Rate (SER) and achieve higher STR compared with two existing energy-efficient routing protocols, in which no joint design is considered.     

Achieving Energy Efficiency in Wireless Sensor Networks Using Dynamic Channel Polling and Packet Concatenation

There has been a significant interest of re-searchers to combine different schemes focused on op-timizing energy performance while developing a MAC protocol for...     

Energy Efficiency Optimization for Wireless Body Area Networks Under 802.15.6 Standard

Wireless Personal Communications - With the attractive applications in e-Health, a booming interest is granted to wireless body area network (WBAN). Through WBAN, healthcare professionals can...     

Packet Size Optimization for Improving the Energy Efficiency in Body Sensor Networks

Energy consumption is a key issue in body sensor networks (BSNs) since energy‐constrained sensors monitor the vital signs of human beings in healthcare applications. In this paper, packet size optimization for BSNs has been analyzed to improve the efficiency of energy consumption. Existing studies on packet size optimization in wireless sensor networks cannot be applied to BSNs because the different operational characteristics of nodes and the channel effects of in‐body and on‐body propagation cannot be captured. In this paper, automatic repeat request (ARQ), forward error correction (FEC) block codes, and FEC convolutional codes have been analyzed regarding their energy efficiency. The hop‐length extension technique has been applied to improve this metric with FEC block codes. The theoretical analysis and the numerical evaluations reveal that exploiting FEC schemes improves the energy efficiency, increases the optimal payload packet size, and extends the hop length for all scenarios for in‐body and on‐body propagation.     

On Balancing Energy Consumption in Wireless Sensor Networks

Wireless sensor networks (WSNs) require protocols that make judicious use of the limited energy capacity of the sensor nodes. In this paper, the potential performance improvement gained by balancing the traffic throughout the WSN is investigated. We show that sending the traffic generated by each sensor node through multiple paths, instead of a single path, allows significant energy conservation. A new analytical model for load-balanced systems is complemented by simulation to quantitatively evaluate the benefits of the proposed load-balancing technique. Specifically, we derive the set of paths to be used by each sensor node and the associated weights (i.e., the proportion of utilization) that maximize the network lifetime.      

An Energy Efficient Autonomous Method for Coverage Optimization in Wireless Multimedia Sensor Networks

In this paper, a distributed method for coverage optimization of random deployed WMSNs utilizing motility and mobility capabilities of nodes, is proposed. The aims followed by the method are first, maximizing the coverage ratio by minimizing both the covered overlapping areas, and the coverage holes after random deployment, and second, enhancing energy efficiency of the coverage optimization procedure, by minimizing the needed rotations and specially movements, comparing with the previous schemes. To these aims, the most appropriate location and orientation of the nodes are calculated round by round considering all the possible nested compositions of rotation and movement. But, rotating and moving the nodes are performed after terminating the algorithm rounds and achieving the decisive results. So, the proposed method does not impose the overhead of trial and error of rotation or relocation on the network nodes. The performance of the proposed approach has been compared with the previous works for different network configurations; simulation results show that the proposed approach outperforms the previous schemes in terms of both coverage ratio and energy efficiency.     

Nonconvex Optimization for Power Control in Wireless CDMA Networks

In this paper, we propose an efficient power control algorithm for the downlink wireless CDMA systems. The goal of our paper is to achieve the optimum and fair resource utilization by maximizing a weighted sum utility with the power constraint. In fact, the objective function in the power optimization problem is always nonconcave, which makes the problem difficult to solve. We make progress in solving this type of optimization problem using PSO (particle swarm optimization). PSO is a new evolution algorithm based on the movement and intelligence of swarms looking for the most fertile feeding location, which can solve discontinuous, nonconvex and nonlinear problems efficiently. It’s proved that the proposed algorithm converges to the global optimal solutions in this paper. Numerical examples show that our algorithm can guarantee the fast convergence and fairness within a few iterations. It also demonstrates that our algorithm can efficiently solve the nonconvex optimization problems when we study the different utility functions in more realistic settings.     

Modeling and Optimization of a Solar Energy Harvester System for Self-Powered Wireless Sensor Networks

In this paper, we propose a methodology for optimizing a solar harvester with maximum power point tracking for self-powered wireless sensor network (WSN) nodes. We focus on maximizing the harvester's efficiency in transferring energy from the solar panel to the energy storing device. A photovoltaic panel analytical model, based on a simplified parameter extraction procedure, is adopted. This model predicts the instantaneous power collected by the panel helping the harvester design and optimization procedure. Moreover, a detailed modeling of the harvester is proposed to understand basic harvester behavior and optimize the circuit. Experimental results based on the presented design guidelines demonstrate the effectiveness of the adopted methodology. This design procedure helps in boosting efficiency, allowing to reach a maximum efficiency of 85% with discrete components. The application field of this circuit is not limited to self-powered WSN nodes; it can easily be extended in embedded portable applications to extend the battery life.     

Joint Throughput Optimization for Wireless Mesh Networks

In this paper, we address the problem of joint channel assignment, link scheduling, and routing for throughput optimization in wireless networks with multiradios and multichannels. We mathematically formulate this problem by taking into account the interference, the number of available radios the set of usable channels, and other resource constraints at nodes. We also consider the possible combining of several consecutive channels into one so that a network interface card (NIC) can use the channel with larger range of frequencies and thus improve the channel capacity. Furthermore, we consider several interference models and assume a general yet practical network model in which two nodes may still not communicate directly even if one is within the transmission range of the other. We designed efficient algorithm for throughput (or fairness) optimization by finding flow routing, scheduling of transmissions, and dynamic channel assignment and combining. We show that the performance, fairness and throughput, achieved by our method is within a constant factor of the optimum. Our model also can deal with the situation when each node will charge a certain amount for relaying data to a neighboring node and each flow has a budget constraint. Our extensive evaluation shows that our algorithm can effectively exploit the number of channels and radios. In addition, it shows that combining multiple channels and assigning them to a single user at some time slots indeed increases the maximum throughput of the system compared to assigning a single channel.     

无线传感器网络节能策略分析

无线传感器网络作为当今广泛使用的一项技术,其生存周期一般都很长,但节点多采用电池供电,能量有限。而网络的节点的数目太多,如要更换电池工作量太大无法实现。因此,在正常运行和保证系统功能的条件下,尽量减少能耗的节能技术,是本文所研究的问题。     

Energy Harvesting System Design and Optimization Using High Bandwidth Rectenna for Wireless Sensor Networks

Wireless Personal Communications - Today’s world has a keen interest in systems which are battery-less and can harvest energy from their surroundings. There is an increased demand for...     

无线传感器网络跨层优化研究

无线传感器网络系统的跨层优化理论在当前是一个研究热点.在传统的无线网络设计中,一般是沿用有线网络的设计思想,特别是利用因特网的设计思想来设计无线网络.然而由于无线传感器具有网络资源和能量受限的特点,这就使得传统的有线网络中分层设计的思想遇到了未曾预计的尴尬与挑战.本文对无线传感器网络中的跨层优化工作原理进行了叙述,比较了各个跨层优化技术的特点.最后阐述了当前跨层设计技术面临的挑战.