无线传感器网络服务质量的随机控制策略

为使网络具有给定的感知范围或覆盖率,必须保证WSN传感器具有一定空间密度,因此网络中活动的传感器数量可作为QoS的一种度量[1]。在这种定义下,提出两种QoS控制方法,基于贪心算法的集中式控制方法和基于寿命的分布式随机控制方法。如果传感器能够存储运行状态信息或每隔一段时间能够交换节点寿命信息,前者可以获得最优的网络寿命;后者则通过交换初始传感器节点寿命,利用平均寿命信息随机调度活动的节点,从而延缓存活节点数的降低。仿真结果证实了这两种方法的有效性。     

无线传感器网络满足QoS带宽需求 的能量最优路由方案

有效使用片上受限资源以保持最长的生命周期是无线传感器网络的核心问题.QoS路由技术解决了无线传感器网络要求支持多种业务的差别服务和全网范围的资源有效利用的问题.本文提出了一种可以满足QoS带宽需求的能量最优路由发现方法.该方法构建了节点选择模型、能量评价模型和节点能耗权重模型,使用遗传算法利用可用节点集合建立满足QoS带宽需求的能量最优路由.利用Markov链证明该算法是可收敛并且是以指数速度概率强收敛的.另外,通过实验仿真与分析,给出了本文遗传算法的控制参数的选择区间,实验显示本文提出的满足QoS带宽需求的路由发现方法对无线传感器网络具有更好的适应性和更长的网络寿命.     

无线传感器网络中基于非端到端的区分队列服务

在无线传感器网络中,通信的一方是汇聚节点,通信的另一方不是某一个传感器节点而是一群传感器节点。适用于端到端通信的服务质量方法不再适用于无线传感器网络。为此,提出了一套新的非端到端的事件服务质量参数,并基于此提出了一种基于区分队列服务算法的、为网络中不同的事件提供不同服务质量的方法。通过这一策略,汇聚节点可以及时可靠地检测到待处理的紧急事件。仿真实验结果验证了该方法的可靠性。     

Delay characterization and performance evaluation of cluster-based WSN with different deployment distributions

Provisioning of quality of service (QoS) is the ultimate goal for any wireless sensor network (WSN). Several factors can influence this requirement such as the adopted cluster formation algorithm. Almost all WSNs are structured based on grouping the sensors nodes into clusters. Not all contemporary cluster formation and routing algorithms (e.g. LEACH) were designed to provide/sustain certain QoS requirement such as delay constraint. Another fundamental design issue is that, these algorithms were built and tested under the assumption of uniformly distributed sensor nodes. However, this assumption is not always true. In some industrial applications and due to the scope of the ongoing monitoring process, sensors are installed and condensed in certain areas, while they are widely separated in other areas. Also unlike the random deployment distributions, there are many applications that need deterministic deployment of sensors like grid distribution. In this work, we investigated and characterized the impact of sensor node deployment distributions on the performance of different flavors of LEACH routing algorithm. In particular, we studied via extensive simulation experiments how LEACH cluster formation approach affects the delay (inter and intra-cluster delay) and energy efficiency expressed in terms of packet/joule for different base station locations and data loads. In this study, we consider four deployment distributions: grid, normal, exponential and uniform. The results showed the significant impact of nodes distribution on the network energy efficiency, throughput and delay performance measures. These findings would help the architects of real time application wireless sensor networks such as secure border sensor networks to design such networks to meet its specifications effectively and fulfill their critical mission.     

Distributed data source verification in wireless sensor networks

In-network data aggregation is favorable for wireless sensor networks (WSNs): It allows in-network data processing while reducing the network traffic and hence saving the sensors energy. However, due to the distributed and unattended nature of WSNs, several attacks aiming at compromising the authenticity of the collected data could be perpetrated. For example, an adversary could capture a node to create clones of the captured one. These clones disseminated through the network could provide malicious data to the aggregating node, thus poisoning/disrupting the aggregation process. In this paper we address the problem of detecting cloned nodes; a requirement to be fulfilled to provide authenticity of the data fusion process.First, we analyze the desirable properties a distributed clone detection protocol should meet. Specifically: It should avoid having a single point of failure; the load should be totally distributed across the nodes in the network; the position of the clones in the network should not influence the detection probability. We then show that current solutions do not meet the exposed requirements. Next, we propose the Information Fusion Based Clone Detection Protocol (ICD). ICD is a probabilistic, completely distributed protocol that efficiently detects clones. ICD combines two cryptographic mechanisms: The pseudo-random key pre-distribution, usually employed to secure node pairwise communications, with a sparing use of asymmetric crypto primitives. We show that ICD matches all the requirements above mentioned and compare its performance with current solutions in the literature; experimental results show that ICD has better performance than existing solutions for all the cost parameters considered: Number of messages sent, per sensor storage requirement, and signature verification. These savings allow to increase the network operating lifetime. Finally, note that ICD protocol could be used as an independent layer by any data aggregation mechanism.     

无线传感器网络分簇路由节能研究

在大规模传感和环境监测中,节约能源延长传感器节点生命已成为无线传感器网络最重要的研究课题之一。提供合理的能源消耗和改善无线网络生命周期的传感器网络系统,必须设计一种新的有效的节能方案和节能路由体系。方案采用一种聚类算法减少无线传感器网络的能量消耗,创建一种cluster-tree分簇路由结构的传感器网络。该方案主要目标是做一个理想的分簇分配,减少传感器节点之间的数据传输距离,降低传感器节点能源消耗,延长寿命。实验结果表明,该方案有效地降低了能源消耗从而延长无线传感器网络生命。     

Power management in SMAC-based energy-harvesting wireless sensor networks using queuing analysis

One of the most important constraints in traditional wireless sensor networks is the limited amount of energy available at each sensor node. The energy consumption is mainly determined by the choice of media access mechanism. SMAC is a typical access mechanism that has drawn much attention in recent years. In WSNs, sensors are usually equipped with capacity-limited battery sources that can sustain longer or shorter period, depending on the energy usage pattern and the activeness level of sensor nodes. To extend the lifetime of the sensor networks, ambient energy resources have been recently exploited in WSNs. Even though solar radiation is known as the superior candidate, its density varies over time depending on many factors such as solar intensity and cloud states, which makes it difficult to predict and utilize the energy efficiently. As a result, how to design an efficient MAC in a solar energy harvesting based WSN becomes a challenging problem. In this paper, we first incorporate a solar energy-harvesting model into SMAC and conduct its performance analysis from a theoretical aspect. Our research works provide a fundamental guideline to design efficient MAC for energy harvesting based WSNs. Our major contribution includes three folders: firstly, we model solar energy harvesting in a photovoltaic cell and then derive the throughput of SMAC in the energy-harvesting based WSNs. Second, we develop a new model based on queuing theory to calculate the average number of energy packets in battery in terms of both duty cycle and throughput. Finally, we form an optimization problem to find a suitable range for the duty cycle to satisfy both quality of service (QoS) and network lifetime requirements.     

无线传感器网络能量最优的QoS路由发现方法

针对无线传感器网络的动态网络环境和节点能源受限,且通常无法补充的能源特性等不利因素,提出了一种可以实现能量最优的QoS路由发现方法。该方法利用节点选择机制和节点邻居表来建立满足QoS带宽需求的可供选择的节点集合,从而减少路由发现过程中的所要监测的节点数量。所提方法还构建了无线传感器网络的能量评价模型和节点能耗权重模型,使用遗传算法从可供选择的节点集合中构建可实现能量最优的QoS路由,自适应的实现对节点调度,从而延长无线传感器网络的寿命。通过实验仿真与分析,给出了实现无线传感器网络能量最优的遗传算法控制参数的选择区间。实验结果显示:该方法对无线传感器网络具有更好的适应性,且能保证其有更长的寿命。     

Energy efficient and QoS based routing protocol for wireless sensor networks

The increasing demand for real-time applications in Wireless Sensor Networks (WSNs) has made the Quality of Service (QoS) based communication protocols an interesting and hot research topic. Satisfying Quality of Service (QoS) requirements (e.g. bandwidth and delay constraints) for the different QoS based applications of WSNs raises significant challenges. More precisely, the networking protocols need to cope up with energy constraints, while providing precise QoS guarantee. Therefore, enabling QoS applications in sensor networks requires energy and QoS awareness in different layers of the protocol stack. In many of these applications (such as multimedia applications, or real-time and mission critical applications), the network traffic is mixed of delay sensitive and delay tolerant traffic. Hence, QoS routing becomes an important issue. In this paper, we propose an Energy Efficient and QoS aware multipath routing protocol (abbreviated shortly as EQSR) that maximizes the network lifetime through balancing energy consumption across multiple nodes, uses the concept of service differentiation to allow delay sensitive traffic to reach the sink node within an acceptable delay, reduces the end to end delay through spreading out the traffic across multiple paths, and increases the throughput through introducing data redundancy. EQSR uses the residual energy, node available buffer size, and Signal-to-Noise Ratio (SNR) to predict the best next hop through the paths construction phase. Based on the concept of service differentiation, EQSR protocol employs a queuing model to handle both real-time and non-real-time traffic.     

Maximizing network lifetime in wireless sensor networks with regular topologies

Limited energy supply (battery-powered) is a crucial problem in wireless sensor networks (WSNs). Sensor node placement schemes and routing protocols are mostly proposed to address this problem. In this paper, we first present how to place sensor nodes by use of a minimal number of them to maximize the coverage area when the communication radius of the sensor node is different from the sensing radius, which results in the application of regular topology to WSNs deployment. With nodes placed at an equal distance and equipped with an equal power supply, the problem of unbalanced energy consumption in 2-D regular topologies becomes more severe and much more difficult to tackle than that in 1-D chains, though the latter is known as an already quite hard problem. We address this problem and propose an adaptive data collection scheme by employing different communication radii for nodes in different locations to balance the energy consumption in WSNs. In order to achieve the ultimate goal of maximizing network lifetime in grid-based WSNs, we give a mathematical formulation, which shows the problem of maximizing network lifetime is a nonlinear programming problem and NP-hard even in the 1-D case. We discuss several heuristic solutions and show that the halving shift data collection scheme is the best solution among them. We also generalize the maximizing network lifetime problem to the randomly-deployed WSNs, which shows the significance of our mathematical formulation for this crucial problem in WSNs.     

高斯分布无线传感器网络簇头选择算法

针对无线传感器网络的能量受限问题,通常采用分簇聚合减少数据传输来实现能量节省。提出了一种基于高斯分布的分簇网络模型的簇头选择算法,构建了簇头选择函数的概率模型。模型以信道增益、剩余能量、簇内节点间距离及节点位置为参数,通过比较节点的概率函数值选择簇头。结果表明该选择算法能较大程度地提高网络能耗效率、延长网络生存时间。     

HACH: Heuristic Algorithm for Clustering Hierarchy protocol in wireless sensor networks

Wireless sensor networks (WSNs) require energy management protocols to efficiently use the energy supply constraints of battery-powered sensors to prolong its network lifetime. This paper proposes a novel Heuristic Algorithm for Clustering Hierarchy (HACH), which sequentially performs selection of inactive nodes and cluster head nodes at every round. Inactive node selection employs a stochastic sleep scheduling mechanism to determine the selection of nodes that can be put into sleep mode without adversely affecting network coverage. Also, the clustering algorithm uses a novel heuristic crossover operator to combine two different solutions to achieve an improved solution that enhances the distribution of cluster head nodes and coordinates energy consumption in WSNs. The proposed algorithm is evaluated via simulation experiments and compared with some existing algorithms. Our protocol shows improved performance in terms of extended lifetime and maintains favourable performances even under different energy heterogeneity settings.     

A color-theory-based energy efficient routing algorithm for mobile wireless sensor networks

Wireless sensor networks (WSNs) with nodes spreading in a target area have abilities of sensing, computing, and communication. Since the GPS device is expensive, we used a small number of fixed anchor nodes that are aware of their locations to help estimate the locations of sensor nodes in WSNs. To efficiently route sensed data to the destination (the server), identifying the location of each sensor node can be of great help. We adopted a range-free color-theory based dynamic localization (CDL) [Shen-Hai Shee, Kuochen Wang, I.L. Hsieh, Color-theory-based dynamic localization in mobile wireless sensor networks, in: Proceedings of Workshop on Wireless, Ad Hoc, Sensor Networks, August 2005] approach, to help identify the location of each sensor node. Since sensor nodes are battery-powered, we propose an efficient color-theory-based energy efficient routing (CEER) algorithm to prolong the life time of each sensor node. The uniqueness of our approach is that by comparing the associated RGB values among neighboring nodes, we can efficiently choose a better routing path with energy awareness. Besides, the CEER has no topology hole problem. Simulation results have shown that our CEER algorithm can save up to 50–60% energy than ESDSR [Mohammed Tarique, Kemal E. Tepe, Mohammad Naserian, Energy saving dynamic source routing for ad hoc wireless networks, in: Proceedings of Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, April 2005, pp. 305–310] in mobile wireless sensor networks. In addition, the latency per packet of CEER is 50% less than that of ESDSR.     

基于元胞蚁群优化算法的农业无线传感器网络路由研究

无线传感器网络(WSNs)进行农业信息采集时,针对传感器节点数量多,能量消耗不均衡的特点,提出基于元胞蚁群优化(CACO)的WSNs路由算法。算法将网络中的节点映射成CACO算法中的元胞,通过改进蚂蚁信息素更新模型,引入睡眠唤醒机制,有效地减少了节点间的通信,从而改善能量消耗不均衡。仿真结果表明:该算法有效地减少了网络耗能、节点消亡数量,延长了网络生命期。     

WSNs能量异构节点部署与区域覆盖优化

针对无线传感器网络（WSNs）的热点区域问题所导致的节点能量异构、能量空洞等问题,对网络进行重新部署以满足区域覆盖的要求。建立WSNs能量异构节点区域覆盖优化模型,以网络覆盖率为目标函数,节点位置作为决策变量,采用差分进化算法优化该目标,同时获得各节点的最佳位置。仿真实验表明：该模型能充分调度各节点的剩余能量,对热区问题导致的能量空洞进行重新部署,该策略能够延长网络的生命周期,提高网络的可靠性。     

无线传感器网络中一种节点负载均衡的分簇算法

无线传感器网络节点的能量有限,而分簇算法能有效解决节点能耗受限与不同节点能量开销不平衡问题。在网络路由分簇的基础上,提出了一种节点负载均衡的分簇算法。该算法对经典的分簇协议LEACH的簇头选择机制进行了改进,应用量子粒子群对簇头选取进行优化。为解决算法后期易陷入局部极小的问题,采用了基于群体适应值方差的早熟判断机制,结合模拟退火算法进行局部优化。仿真结果表明:该算法使网络节点负载更均衡,有效提高了无线传感器网络的性能。     

An effective node-selection scheme for the energy efficiency of solar-powered WSNs in a stream environment

Previous research on scheduling and solar power issues of wireless sensor networks (WSNs) assumes that the sensors are deployed in a general environment. While monitoring the stream environment, sensors are attached to the stream side to collect the sensed data and transmit the data back to the sink. The stream environment can be scaled in several similar environments. This type of geographic limitation not only exists in a stream environment but also on streets, roads, and trails. This study presents an effective node-selection scheme to enhance the efficiency of saving power and coverage of solar-powered WSNs in a stream environment. Analysis of the sensor deployment in the stream environment permits sensors to be classified into different segments, and then allows the selection of active nodes for building inter-stream connections, inter-segment connections, and intra-segment connections. Based on these connections, the number of active nodes and transmitted packets is minimized. Simulation results show that this scheme can significantly increase the energy efficiency and maintain the monitoring area in solar-powered WSNs.     

Evaluation of quality of service provisioning in large-scale pervasive and smart collaborative wireless sensor and actor networks

With the production of low cost sensors, classical concept of Wireless Sensor Networks (WSNs) evolved into large-scale concept hosting thousands of nodes within a network and generating abundant quantities of data. As these networks are being continuously developed a new class of WSNs are proposed: Wireless Sensor and Actor Networks (WSANs). These networks introduce the actuating component, alongside with the sensing component, where QoS is becoming a very significant factor. The authors of this paper approach the problem of QoS support in large-scale WSAN from a physical layer, where the deployment parameters effects on QoS metrics are demystified. The analysis is formulated on two scenarios: worst case scenario (all nodes transmit data towards the network sink) and best case scenario (a single node transmits a stream of data towards a network sink). For both scenarios two routing protocols were compared, a simple flooding algorithm and a simple distance vector protocol. Also, a new relation between hop count and latency based on transmission power is observed, not reported in the available literature, resulting in a new proposed empirical latency model.     

Using central nodes for efficient data collection in wireless sensor networks

We study the problem of data collection in Wireless Sensor Networks (WSN). A typical WSN is composed of wireless sensor nodes that periodically sense data and forward it to the base station in a multi-hop fashion. We are interested in designing an efficient data collection tree routing, focusing on three optimization objectives: energy efficiency, transport capacity, and hop-diameter (delay).In this paper we develop single- and multi-hop data collection, which are based on the definition of node centrality: centroid nodes. We provide theoretical performance analysis for our approach, present its distributed implementation and discuss the different aspects of using it. Most of our results are for two-dimensional WSNs, however we also show that the centroid-based approach is asymptotically optimal in three-dimensional random node deployments. In addition, we present new construction for arbitrary network deployment based on central nodes selection. We also present extensive simulation results that support our theoretical findings.     

Topology control based on optimally rigid graph in wireless sensor networks

This paper presents an optimization scheme of sensor networks for node scheduling and topology control, aiming to reduce energy consumption for heterogeneous Wireless Sensor Networks (WSNs) with non-uniform transmission ranges. Motivated by geographical adaptive fidelity (GAF), we partition sensors into groups based on the location of sensors, such that a connected backbone network can be maintained by keeping only one arbitrary node from each group in active status while putting others to sleep. In addition, optimally rigid geographical adaptive fidelity (ORGAF) approach is proposed to decrease the communication complexity and reduce the energy dissipation. Furthermore, we prove the topology derived under ORGAF is 2-connected; and the average degree of nodes in the topology converges to four approximately. Simulation results show that ORGAF can improve the network performance as well as reducing the energy consumption.