e‐LiteSense: Self‐adaptive energy‐aware data sensing in WSN environments

Currently deployed in a wide variety of applicational scenarios, wireless sensor networks (WSNs) are typically a resource‐constrained infrastructure. Consequently, characteristics such as WSN adaptability, low‐overhead, and low‐energy consumption are particularly relevant in dynamic and autonomous sensing environments where the measuring requirements change and human intervention is not viable. To tackle this issue, this article proposes e‐LiteSense as an adaptive, energy‐aware sensing solution for WSNs, capable of auto‐regulate how data are sensed, adjusting it to each applicational scenario. The proposed adaptive scheme is able to maintain the sensing accuracy of the physical phenomena, while reducing the overall process overhead. In this way, the adaptive algorithm relies on low‐complexity rules to establish the sensing frequency weighting the recent drifts of the physical parameter and the levels of remaining energy in the sensor. Using datasets from WSN operational scenarios, we prove e‐LiteSense effectiveness in self‐regulating data sensing accurately through a low‐overhead process where the WSN energy levels are preserved. This constitutes a step‐forward for implementing self‐adaptive energy‐aware data sensing in dynamic WSN environments.     

Time‐aware and energy‐efficient opportunistic routing with residual energy collection in wireless sensor networks

In 1‐dimensional queue wireless sensor networks, how to balance end‐to‐end latency and energy consumption is a challenging problem. However, traditional best path routing and existing opportunistic routing protocols do not address them well because relay hop counts are usually much more, and the link appears more unreliable compared with general mesh topology. In this work, we formulate these 2 problems as a multiobjective optimization problem. Specifically, we first classify network packets into types of time tolerant and time critical and introduce a residual energy collection mechanism of neighboring nodes for forwarder set selection. We then propose a time‐aware and energy‐efficient opportunistic routing protocol (TE‐OR) to optimize energy consumption and to reduce latency for time‐critical packets. We evaluate TE‐OR by different parameters and compare it with existing protocols. The performance results show that TE‐OR achieves a trade‐off between energy consumption and time delay and balances energy consumption among nodes while guaranteeing the latency of time‐critical packets is minimized.     

An energy‐efficient and balanced clustering approach for improving throughput of wireless sensor networks

Maximizing the lifespan of wireless sensor networks is currently drawing a lot of attention in the research community. In order to reduce energy consumption, sensor nodes that are far from the base station avoid sending data directly. As a result, several disjoint clusters are formed, and nodes within a cluster send their data through the cluster head to avoid long transmissions. However, several parameters related to transmission cost need to be considered when selecting a cluster head. While most of the existing research work considers energy and distance as the most stringent parameters to reduce energy consumption, these approaches fail to create a fair and balanced cluster. Consequently, unbalanced clusters are formed, resulting in the degradation of overall performance. In this research work, a cluster head selection algorithm is proposed that covers all parts of the sensing area in a balanced manner, saving a significant amount of energy. Furthermore, a capture effect–based intracluster communication mechanism is proposed that efficiently utilizes the time slot under various traffic conditions. A Näive Bayes classifier is used to adapt the window size dynamically according to the traffic pattern. Finally, a simulation model using OMNeT++ is developed to compare the proposed approach with the pioneer clustering approach, LEACH, and the contemporary LEACH‐MAC protocol in terms of performance. The results of the simulation indicate that the proposed approach improves the overall performance in terms of network lifetime, energy efficiency, and throughput.     

Simulations and experiments for optimal deployment of an RFID‐based location‐aware system

The proliferation of communication and mobile computing devices and local‐area wireless networks has cultivated a growing interest in location‐aware systems and services. An essential problem in location‐aware computing is the determination of physical locations. RFID technologies are gaining much attention, as they are attractive solutions to indoor localization in many healthcare applications. In this paper, we propose a new indoor localization methodology that aims to deploying RFID technologies in achieving accurate location‐aware undertakings with real‐time computation. The proposed algorithm introduces means to improve the accuracy of the received RF signals. Optimal settings for the parameters in terms of reader and reference tag properties were investigated through simulations and experiments. The experimental results indicate that our indoor localization methodology is promising in applications that require fast installation, low cost and high accuracy. Copyright © 2009 John Wiley & Sons, Ltd.     

基于AOMDV的多径路由协议改进及仿真分析

Ad Hoc网络是由一些移动节点组成、拓扑结构复杂且动态变化的自组织网络。网络中没有固定的网络基础设施,对路由协议要求较高。通过在每个节点的路由表和发送接收包中增加能量参数等措施,提出基于AOMDV的多路径路由协议改进方案PE-AOMDV协议,最后在NS2仿真平台上实现对改进的AOMDV多路径路由协议仿真分析。仿真结果表明：与AOMDV协议相比,新的基于能量的多路径路由协议PE-AOMDV的传输时延和路由开销都有所降低,并提高了分组投递率,从而提高了网络性能。     

An energy efficient clustering routing algorithm for wireless sensor networks

~~An energy efficient clustering routing algorithm for wireless sensor networks1. Mainwaring A, Polastre J, Szewczyk R, et al. Wireless sensor networks for habitat monitoring. Proceedings of the ACM International Workshop on Wireless Sensor Networks and A…     

Towards a classification of energy aware MAC protocols for wireless sensor networks

Power management is an important issue in wireless sensor networks (WSNs) because wireless sensor nodes are usually battery powered, and an efficient use of the available battery power becomes an important concern specially for those applications where the system is expected to operate for long durations. This necessity for energy efficient operation of a WSN has prompted the development of new protocols in all layers of the communication stack. Provided that, the radio transceiver is the most power consuming component of a typical sensor node, large gains can be achieved at the link layer where the medium access control (MAC) protocol controls the usage of the radio transceiver unit. MAC protocols for sensor networks differ greatly from typical wireless networks access protocols in many issues. MAC protocols for sensor networks must have built‐in power conservation, mobility management, and failure recovery strategies. Furthermore, sensor MAC protocols should make performance trade‐off between latency and throughput for a reduction in energy consumption to maximize the lifetime of the network. This is in general achieved through duty cycling the radio transceiver. Many MAC protocols with different objectives were proposed for wireless sensor networks in the literature. Most of these protocols take into account the energy efficiency as a main objective. There is much more innovative work should be done at the MAC layer to address the hard unsolved problems. In this paper, we first outline and discuss the specific requirements and design trade‐offs of a typical wireless sensor MAC protocol by describing the properties of WSN that affect the design of MAC layer protocols. Then, a typical collection of wireless sensor MAC protocols presented in the literature are surveyed, classified, and described emphasizing their advantages and disadvantages whenever possible. Finally, we present research directions and identify open issues for future medium access research. Copyright © 2009 John Wiley & Sons, Ltd.     

Distributed fuzzy logic based energy‐aware and coverage preserving unequal clustering algorithm for wireless sensor networks

In an energy‐constrained wireless sensor networks (WSNs), clustering is found to be an effective strategy to minimize the energy depletion of sensor nodes. In clustered WSNs, network is partitioned into set of clusters, each having a coordinator called cluster head (CH), which collects data from its cluster members and forwards it to the base station (BS) via other CHs. Clustered WSNs often suffer from the hot spot problem where CHs closer to the BS die much early because of high energy consumption contributed by the data forwarding load. Such death of nodes results coverage holes in the network very early. In most applications of WSNs, coverage preservation of the target area is a primary measure of quality of service. Considering the energy limitation of sensors, most of the clustering algorithms designed for WSNs focus on energy efficiency while ignoring the coverage requirement. In this paper, we propose a distributed clustering algorithm that uses fuzzy logic to establish a trade‐off between the energy efficiency and coverage requirement. This algorithm considers both energy and coverage parameters during cluster formation to maximize the coverage preservation of target area. Further, to deal with hot spot problem, it forms unequal sized clusters such that more CHs are available closer to BS to share the high data forwarding load. The performance of the proposed clustering algorithm is compared with some of the well‐known existing algorithms under different network scenarios. The simulation results validate the superiority of our algorithm in network lifetime, coverage preservation, and energy efficiency.     

An energy‐efficient,scalable and collision‐free MAC layer protocol for wireless sensor networks

Wide range of applications such as disaster management, military and security have fueled the interest in sensor networks during the past few years. Sensors are typically capable of wireless communication and are significantly constrained in the amount of available resources such as energy, storage and computation. Such constraints make the design and operation of sensor networks considerably different from contemporary wireless networks, and necessitate the development of resource conscious protocols and management techniques. In this paper, we present an energy‐efficient, scalable and collision‐free MAC layer protocol for sensor networks. The approach promotes time‐based arbitration of medium access to limit signal interference among the transmission of sensors. Transmission and reception time slots are prescheduled to allow sensors to turn their radio circuitry off when not engaged. In addition, energy consumption due to active to sleep mode transitions is minimized through the assignment of contiguous transmission/reception slots to each sensor. Scalability of the approach is supported through grouping of sensors into clusters. We describe an optimization algorithm for energy conscious scheduling of time slots that prevents intra‐cluster collisions and eliminates packet drop due to buffer size limitations. In addition, we also propose an arbitration scheme that prevents collisions among the transmission of sensors in different clusters. The impact of our approach on the network performance is qualified through simulation.. Copyright © 2004 John Wiley & Sons, Ltd.     

AODV、AOMDV和AODV-UU路由协议性能仿真与分析

使用NS-2(Network Simulator Version 2)仿真软件,选取分组投递率、端到端平均时延、归一化路由开销和路由发现频率4个指标对按需距离矢量路由(AODV,Ad hoc On-Demand Distance Vector Routing)、多径按需距离矢量路由(AOMDV,Ad Hoc On-Demand Multipath Distance Vector Routing)和乌普萨拉大学开发的按需距离矢量路由(AODV-UU,Ad Hoc On-Demand Distance Vector Routing developed by Uppsala University)进行了性能仿真,通过改变节点最大运动速度和业务源连接对数分析比较这些参数对3个协议性能的影响,研究结果表明了AODV-UU协议的优越性。并提出了对AODV-UU协议的改进。     

一种加强的主动队列管理算法--EBLUE

作为一种典型的主动队列管理算法,BLUE明显不同于其它方法,它使用丢包和连接空闲事件来控制拥塞。试验表明BLUE的丢包率明显小于RED,但是其参数设置仍然存在一些不足之处。本文在BLUE算法的基础之上,通过引进自适应的思想对其进行了改进,提出了一种加强的BLUE队列算法——EBLUE。大量的仿真实验表明本文的改进算法能够进一步提高BLUE的性能。     

Low‐jitter slot assignment algorithm for deadline‐aware packet transmission in wireless video surveillance sensor networks

This work presents a distributed time‐slot assignment algorithm which adopts TDMA as Medium Access Control, specially suited to support applications with strict delay, jitter, and throughput requirements characterized by convergecast traffic pattern in sensor networks. (e.g. wireless video surveillance sensor networks). The proposed algorithm has three characteristics: (1) every node is guaranteed a path to the base station for its data delivery. In the path, sufficient resource is reserved and weighted fairness can be achieved. (2) It uses cascading time‐slot assignment and jitter minimization algorithm in each node to minimize jitter and end‐to‐end delay. (3) Nodes are only active during their scheduled slots and sleep otherwise. This offers energy saving by reducing idle listening and avoiding overhearing. The performance of the proposed algorithm is evaluated over simulations and analyzed theoretically in comparison with existing slot assignment algorithm. The results show that our algorithm provides lower end‐to‐end delay, jitter, and higher throughput. Copyright © 2010 John Wiley & Sons, Ltd.     

A study of deploying smooth‐ and responsive‐TCPs with different queue management schemes

While there exist extensive research works on congestion control and active queue management, or the joint dynamics of a congestion control strategy with the random early detection (RED) algorithm, little has been done on the interactions between different window adjustment strategies and different queue management schemes such as DropTail and RED. In this paper, we consider a spectrum of TCP‐friendly additive increase and multiplicative decrease (AIMD) parameters. At the one end of this spectrum, smooth‐TCP enhances smoothness for multimedia applications by reducing the window decrease ratio upon congestion, at the cost of the additive increase speed and the responsiveness to available bandwidth. At the other end, responsive‐TCP enhances the responsiveness by increasing the additive increase speed, at the cost of smoothness. We investigate the network dynamics with various combinations of AIMD parameters and queue management schemes, under different metrics. The investigation is conducted from the deployment (especially incremental deployment) point of view. We discussed the impact of the interactions on the goodput, fairness, end‐to‐end delay, and its implications to energy consumption on mobile hosts. Copyright © 2008 John Wiley & Sons, Ltd.     

A distributed,multi‐hop,adaptive, tree‐based energy‐balanced routing approach

To accomplish the primary objective of data sensing and collection of wireless sensor networks (WSN), the design of an energy efficient routing algorithm is very important. However, the energy constrained sensing nodes along with the intrinsic properties of the (WSN) environment makes the routing a challenging task. To overcome this routing dilemma, an improved distributed, multi‐hop, adaptive, tree‐based energy‐balanced (DMATEB) routing scheme is proposed in this paper. In this scheme, a relay node is selected in view of minimum distance and high energy from a current sensing node. Further, the parent node is chosen among the selected relay nodes on the basis of high residual energy and less power consumption with due consideration of its associated child nodes. As each sensing node itself selects its parent among the available alternatives, the proposed scheme offers a distributive and adaptive approach. Moreover, the proposed system does not overload any selected parent of a particular branch as it starts acting as a child whenever its energy lowers among the other available relay nodes. This leads to uniform energy utilization of nodes that offers a better energy balance mechanism and improves the network lifespan by 20% to 30% as compared with its predecessors.     

XMSN: An efficient cross‐layer protocol for mixed wireless sensor networks

The application of wireless sensor networks (WSNs) technology in monitoring systems is demanding more efficient services to fulfill the requirements of the monitoring task. For this purpose, the simultaneous presence of features such as different communication mediums (air and water) used by nodes and various sizes of data generated by heterogeneous nodes are the key obstacles to build a communication protocol, which can ensure the reliable data delivery. This work terms such WSNs as mixed wireless sensor networks (MWSNs) which contains the aforementioned features. In this paper, we introduce a new cross‐layer protocol for mixed wireless sensor network (XMSN) which can adapt these features. The proposed cross layer protocol XMSN for such mixed environment is implemented and analyzed extensively in Castalia simulator. The performance of XMSN is compared with composition of well‐known protocols, namely, CTP plus BoX‐MAC‐2. The result shows that XMSN has better efficiency in terms of end‐to‐end delay, energy consumption, and goodput than that of CTP plus BoX‐MAC‐2 protocol.     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

Distributed beamforming with one-bit feedback and clustering for multi-node wireless energy transfer

To resolve energy depletion issues in massive Internet of Things sensor networks, we developed a set of distributed energy beamforming methods with one-bit feedback and clustering for multi-node wireless energy transfer, where multiple single-antenna distributed energy transmitters (Txs) transfer their energy to multiple nodes wirelessly. Unlike previous works focusing on distributed information beamforming using a single energy receiver (Rx) node, we developed a distributed energy beamforming method for multiple Rx nodes. Additionally, we propose two clustering methods in which each Tx node chooses a suitable Rx node. Furthermore, we propose a fast distributed beamforming method based on Tx sub-clustering. Through computer simulations, we demonstrate that the proposed distributed beamforming method makes it possible to transfer wireless energy to massive numbers of sensors effectively and rapidly with small implementation complexity. We also analyze the energy harvesting outage probability of the proposed beamforming method, which provides insights into the design of wireless energy transfer networks with distributed beamforming.     

An optimal energy‐efficient clustering method in wireless sensor networks using multi‐objective genetic algorithm

In this study, an optimal method of clustering homogeneous wireless sensor networks using a multi‐objective two‐nested genetic algorithm is presented. The top level algorithm is a multi‐objective genetic algorithm (GA) whose goal is to obtain clustering schemes in which the network lifetime is optimized for different delay values. The low level GA is used in each cluster in order to get the most efficient topology for data transmission from sensor nodes to the cluster head. The presented clustering method is not restrictive, whereas existing intelligent clustering methods impose certain conditions such as performing two‐tiered clustering. A random deployed model is used to demonstrate the efficiency of the proposed algorithm. In addition, a comparison is made between the presented algorithm other GA‐based clustering methods and the Low Energy Adaptive Clustering Hierarchy protocol. The results obtained indicate that using the proposed method, the network's lifetime would be extended much more than it would be when using the other methods. Copyright © 2011 John Wiley & Sons, Ltd.     

QoS‐aware target coverage in wireless sensor networks

Wireless sensor networks have emerged recently as an effective way of monitoring remote or inhospitable physical targets, which usually have different quality of service (QoS) constraints, i.e., different targets may need different sensing quality in terms of the number of transducers, sampling rate, etc. In this paper, we address the problem of optimizing network lifetime while capturing those diversified QoS coverage constraints in such surveillance sensor networks. We show that this problem belongs to NP‐complete class. We define a subset of sensors meeting QoS requirements as a coverage pattern, and if the full set of coverage patterns is given, we can mathematically formulate the problem. Directly solving this formulation however is difficult since number of coverage patterns may be exponential to number of sensors and targets. Hence, a column generation (CG)‐based approach is proposed to decompose the original formulation into two subproblems and solve them iteratively. Here a column corresponds to a feasible coverage pattern, and the idea is to find a column with steepest ascent in lifetime, based on which we iteratively search for the maximum lifetime solution. An initial feasible set of patterns is generated through a novel random selection algorithm (RSA), in order to launch our approach. Experimental data demonstrate that the proposed CG‐based approach is an efficient solution, even in a harsh environment. Simulation results also reveal the impact of different network parameters on network lifetime, giving certain guidance on designing and maintaining such surveillance sensor networks. Copyright © 2009 John Wiley & Sons, Ltd.     

Improving MANET performance by a hop‐aware and energy‐based buffer management scheme

A hop‐aware and energy‐based buffer management scheme (HEB) is proposed in this paper. HEB can provide better quality of service to packets with real‐time requirements and improve MANET power efficiency. In our algorithm, the buffer is divided into real‐time and non‐real‐time partitions. We consider the number of hops passed, the power levels of the transmitting node, the predicted number of remaining hops, and waiting time in the buffer to determine packet transmission priority. In addition, specialized queue management and a probabilistic scheduling algorithm are proposed to decrease retransmissions caused by packet losses. Mathematical derivations of loss rates and end‐to‐end delays are also proposed. Coincidence between mathematical and simulation results is also shown. Finally, the HEB is compared with first in first out, random early detection, and hop‐aware buffering scheme. Simulation results show that the proposed algorithm reduces loss rates, power consumption, and end‐to‐end delays for real‐time traffic, considerably improving the efficiency of queue management in MANET. Copyright © 2012 John Wiley & Sons, Ltd.