An efficient routing scheme with optimal power control in wireless multi-hop sensor networks

Power consumption is a critical problem in providing multimedia communications among wireless sensor nodes (WSNs). To reduce power consumption and satisfying QoS requirements, in this paper, we propose an efficient routing scheme with optimal power management and on-demand quality control for WSNs. Two cost functions are developed to minimize the transmitting power and maximize the link quality under the constraint that an end-to-end frame error probability should be met. The heuristic problem of minimizing power consumption under frame error constraints is formulated and resolved with a closed-form expression. With this closed-form expression, we can determine an optimal route rapidly by calculating the power requirement for each sensor node. Finally, our analytical results indicate that the proposed scheme is superior to a previous work with the same constraint and is also comparable to the results obtained from a heuristic simulation.     

HORSIC: An efficient one-time signature scheme for wireless sensor networks

One-time signature schemes are promising candidates for broadcast authentication, which is an essential security primitive in wireless sensor networks. This paper proposes HORSIC, an efficient one-time signature scheme for broadcast authentication in wireless sensor networks. Different from previous one-time signature schemes, HORSIC can reduce the public key size and signature size simultaneously at the cost of increased overhead in key generation and signature verification.     

An efficient and DoS-resistant user authentication scheme for two-tiered wireless sensor networks

Wireless sensor networks (WSNs) are vulnerable to security attacks due to their deployment and resource constraints.Considering that most large-scale WSNs follow a two-tiered architecture,we propose an efficient and denial-of-service (DoS)-resistant user authentication scheme for two-tiered WSNs.The proposed approach reduces the computational load,since it performs only simple operations,such as exclusive-OR and a one-way hash function.This feature is more suitable for the resource-limited sensor nodes and mobile devices.And it is unnecessary for master nodes to forward login request messages to the base station,or maintain a long user list.In addition,pseudonym identity is introduced to preserve user anonymity.Through clever design,our proposed scheme can prevent smart card breaches.Finally,security and performance analysis demonstrates the effectiveness and robustness of the proposed scheme.     

一种能量高效的无线传感器网络拓扑控制算法

通过对现有拓扑控制算法的研究,针对无线传感器网络中节点能耗分布不均匀的问题,提出了一种能量高效的拓扑控制算法(EETCA)。该算法以均衡全局能耗为目标,综合考虑了节点的剩余能量、簇的规模、数据最优传输跳数等因素,避免了部分节点能量消耗过快,从而有效地均衡网络负载。仿真结果表明:EETCA在能耗均衡方面均优于原来的算法,延长了无线传感器网络的生命周期。     

基于功率控制的WSNs跨层方案

无线传感器网络(W SNs)协议设计中既要考虑网络性能,又要考虑能量消耗。由于考虑的因素众多,传统的分层方法通常不能满足多个目标。提出一种基于功率控制的跨层路由方案,基于微经济学中效用的概念,通过对每个链路的功率进行控制,减少不必要发送功率,减少节点之间相互干扰,节省能耗。通过基于效用的路由度量,均衡网络性能,延长网络生存期。     

An efficient two-factor user authentication scheme with unlinkability for wireless sensor networks

User authentication with unlinkability is one of the corner stone services for many security and privacy services which are required to secure communications in wireless sensor networks (WSNs). Recently, Xue et al. proposed a temporal-credential-based mutual authentication and key agreement scheme for WSNs, and claimed that their scheme achieves identity and password protection, and the resiliency of stolen smart card attacks. However, we observe that Xue et al.’s scheme is subject to identity guessing attack, tracking attack, privileged insider attack and weak stolen smart card attack. In order to fix the drawbacks, we propose an enhanced authentication scheme with unlinkability. Additionally, the proposed scheme further cuts the computational cost. Therefore, the proposed scheme not only remedies its security flaws but also improves its performance. It is more suitable for practical applications of WSNs than Xue et al.’s scheme.     

An adaptive and efficient dimension reduction model for multivariate wireless sensor networks applications

Wireless sensor networks (WSNs) applications are growing rapidly in various fields such as environmental monitoring, health care management, and industry control. However, WSN's are characterized by constrained resources especially; energy which shortens their lifespan. One of the most important factors that cause a rapid drain of energy is radio communication of multivariate data between nodes and base station. Besides, the dynamic changes of environmental variables pose a need for an adaptive solution that cope with these changes over the time. In this paper, a new adaptive and efficient dimension reduction model (APCADR) is proposed for hierarchical sensor networks based on the candid covariance-free incremental PCA (CCIPCA). The performance of the model is evaluated using three real sensor networks datasets collected at Intel Berkeley Research Lab (IBRL), Great St. Bernard (GSB) area, and Lausanne Urban Canopy Experiments (LUCE). Experimental results show 33.33% and 50% reduction of multivariate data in dynamic and static environments, respectively. Results also show that 97–99% of original data is successfully approximated at cluster heads in both environment types. A comparison with the multivariate linear regression model (MLR) and simple linear regression model (SLR) shows the advantage of the proposed model in terms of efficiency, approximation accuracy, and adaptability with dynamic environmental changes.     

Power efficient scheme for self localization in wireless sensor networks

With the tremendous applications of the wireless sensor network, self-localization has become one of the challenging subject matter that has gained attention of many researchers in the field of wireless sensor network. Localization is the process of assigning or computing the location of the sensor nodes in a sensor network. As the sensor nodes are deployed randomly, we do not have any knowledge about their location in advance. As a result, this becomes very important that they localize themselves as manual deployment of sensor node is not feasible. Also, in WSN the main problem is the power as the sensor nodes have very limited power source. This paper provides a novel solution for localizing the sensor nodes using controlled power of the beacon nodes such that we will have longer life of the beacon nodes which plays a vital role in the process of localization as it is the only special nodes that has the information about its location when they are deployed such that the remaining ordinary nodes can localize themselves in accordance with these beacon node. We develop a novel model that first finds the distance of the sensor nodes then it finds the location of the unknown sensor nodes in power efficient manner. Our simulation results show the effectiveness of the proposed methodology in terms of controlled and reduced power.     

An efficient mutual authentication and key agreement scheme without password for wireless sensor networks

The Journal of Supercomputing - Wireless sensor networks (WSNs) are usually deployed in hostile or unattended areas, and users need to obtain real-time data from WSNs. The data collected by sensor...     

Low-complexity and energy efficient image compression scheme for wireless sensor networks

Currently most energy-constrained wireless sensor networks are designed with the object of minimizing the communication power at the cost of more computation. To achieve high compression efficiency, the main image compression algorithms used in wireless sensor networks are the high-complexity, state-of-the-art image compression standards, such as JPEG2000. These algorithms require complex hardware and make the energy consumption for computation comparable to communication energy dissipation. To reduce the hardware cost and the energy consumption of the sensor network, a low-complexity and energy efficient image compression scheme is proposed. The compression algorithm in the proposed scheme greatly lowers the computational complexity and reduces the required memory, while it still achieves required PSNR. The proposed implementation scheme of the image compression algorithm overcomes the computation and energy limitation of individual nodes by sharing the processing of tasks. And, it applies transmission range adjustment to save communication energy dissipation. Performance of the proposed scheme is investigated with respect to image quality and energy consumption. Simulation results show that it greatly prolongs the lifetime of the network under a specific image quality requirement.     

A secure and efficient data aggregation scheme for wireless sensor networks

In resource‐constrained wireless sensor networks, data aggregation is a key technique for power‐efficient information acquisition. Consequently, the intermediate sensor nodes performing aggregation tasks known as aggregators are valuable and attractive targets for attackers. We address the problem of defending against malicious adversaries who intend to stealthily change some aggregates to entice the base station to accept deceiving results. A secure and efficient aggregation scheme is proposed, in which the base station composes a secret configuration matrix and each sensor node is pre‐loaded with a limited part of the matrix known as a secret share containing certain local instructions. For each aggregation session, a set of scrambled aggregates are constructed in such a manner that there exists a secret yet unrevealed relationship between these values. The base station, aware of the relationship derived from the configuration matrix, can both extract the intended result from the received aggregates and verify it on its own. Our scheme avoids the interactive verification phase which existent protocols typically take to ensure the aggregation integrity, and thus observably lowers the communication overhead. The proposed scheme also features protection of data confidentiality, and analysis shows that it can detect stealthy alteration attacks with a significant probability. Copyright © 2010 John Wiley & Sons, Ltd.     

Transmission power control techniques for wireless sensor networks

Communication is usually the most energy-consuming event in Wireless Sensor Networks (WSNs). One way to significantly reduce energy consumption is applying transmission power control (TPC) techniques to dynamically adjust the transmission power. This article presents two new TPC techniques for WSNs. The experimental evaluation compares the performance of the TCP techniques with B-MAC, the standard MAC protocol of the Mica 2 platform. These experiments take into account different distances among nodes, concurrent transmissions and node mobility. The new transmission power control techniques decrease energy consumption by up to 57% over B-MAC while maintaining the reliability of the channel. Under a low mobility scenario, the proposed protocols delivered up to 95% of the packets, showing that such methods are able to cope with node movement. We also show that the contention caused by higher transmission levels might be lower than analytical models suggest, due to the action of the capture effect.     

An efficient scheme of target classification and information fusion in wireless sensor networks

In this paper, an efficient target classification and fusion scheme for wireless sensor networks (WSNs) is proposed and evaluated. When a classification algorithm for WSN nodes is designed, parametric approaches such as Gaussian mixture model (GMM) should be more preferred to non-parametric ones due to the hard limitation in resources. The GMM algorithm not only shows good performances for target classification in WSNs but it also requires very small resources. Based on the classifier, a decision tree generated by the classification and regression tree algorithm is used to fuse the information from heterogeneous sensors. This node-level classification scheme provides a satisfactory classification rate, 94.10%, with little resources. Finally, a confidence-based fusion algorithm improves the overall accuracy by fusing the information among sensor nodes. Our experimental results show that the proposed group-level fusion algorithm improves the accuracy by an average of 4.17% accuracy with randomly selected nodes.     

无线传感器网络自适应性拓扑控制的研究

自适应拓扑控制方法用到多跳两层无线传感器网络(WSNs),在每个簇中用两类传感器,有效且低开销的传感器节点N感知环境现象信息,并传输它们的信息到汇聚节点S,所有Ss协同工作去除随机信息并传输数据到基站BS。因为覆盖范围依赖于它的汇聚节点的工作情况,而汇聚节点的能耗在网络的生命期中是关键性因素。这个方法主要是从节点路由能量匹配角度出发,设计可控制数据流路由路径,用于尽可能有效地保持网络能量,并不是仅仅考虑路径的最优选择,而是考虑能效的最优方式选择路由,从而增加整个网络的生命期。     

EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks

In recent years, there has been a growing interest in wireless sensor networks. One of the major issues in wireless sensor network is developing an energy-efficient clustering protocol. Hierarchical clustering algorithms are very important in increasing the network’s life time. Each clustering algorithm is composed of two phases, the setup phase and steady state phase. The hot point in these algorithms is the cluster head selection. In this paper, we study the impact of heterogeneity of nodes in terms of their energy in wireless sensor networks that are hierarchically clustered. We assume that a percentage of the population of sensor nodes is equipped with the additional energy resources. We also assume that the sensor nodes are randomly distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. Homogeneous clustering protocols assume that all the sensor nodes are equipped with the same amount of energy and as a result, they cannot take the advantage of the presence of node heterogeneity. Adapting this approach, we introduce an energy efficient heterogeneous clustered scheme for wireless sensor networks based on weighted election probabilities of each node to become a cluster head according to the residual energy in each node. Finally, the simulation results demonstrate that our proposed heterogeneous clustering approach is more effective in prolonging the network lifetime compared with LEACH.     

An energy-efficient compression scheme for wireless multimedia sensor networks

Multimedia Tools and Applications - In this paper, we propose an energy-efficient compression scheme for wireless multimedia sensor networks. To do this, we analyze the characteristics of...     

An efficient range-free localization algorithm for wireless sensor networks

Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to...     

一种高效可靠的无线传感器网络定位算法

提出了一种新的基于接收信号强度(RSSI)的无线传感器网络定位算法,将固定锚节点之间的距离和信号强度信息同时作为参考来校正每个固定锚节点的权值,每个节点收集自身到其一跳邻节点的RSSI值,当收集数量达到要求时,对数据进行滤波并求平均值处理.通过理论推导证明该方法可以有效降低RSSI不规则网络的定位误差,进而实现高效定位.仿真结果表明,该定位算法可以降低定位误差,具有高效的可用性,能够应用于实际的无线传感器网络中.     

一种无线传感器网络安全方案*

提出了一种无线传感器网络安全方案.它不但提供了一般的安全手段,还支持网内安全处理以延长网络生命期以及概率性多路径冗余传输来识别恶意节点.     

无人机辅助的无线传感网络AoI最小化方案研究

针对无线传感器网络中海量数据处理过程中信息新鲜度问题,基于无人机飞行速度、高度、避碰和可靠传输等约束,以系统信息年龄AoI为考核参数提出了一种联合采集点选择、轨迹优化及无人机工作时间权衡的AoI最小化非凸优化方案。以一个多无人机在同频段条件下为多个传感器节点传输能量并收集传感数据为场景,对多架无人机在三维空间中的信息采集过程进行模拟验证。通过SCA优化算法将建立的非凸问题转化为一个凸优化问题进行求解,最终得到无人机飞行过程中的最优采集点、最优飞行策略及能量输送时间与信息传输时间分配权衡指数,使系统性能达到最优,实验结果表明,所提方案求得的最优解可有效实现系统AoI最小化。