Adaptive algorithms for sensor activation in renewable energy based sensor systems

Upcoming sensor networks would be deployed with sensing devices with energy harvesting capabilities from renewable energy sources such as solar power. A key research question in such sensor systems is to maximize the asymptotic event detection probability achieved in the system, in the presence of energy constraints and uncertainties. This paper focuses on the design of adaptive algorithms for sensor activation in the presence of uncertainty in the event phenomena. Based upon the ideas from increase/decrease algorithms used in TCP congestion avoidance, we design an online and adaptive activation algorithm that varies the subsequent sleep interval according to additive increase and multiplicative decrease depending upon the sensor’s current energy level. In addition, the proposed algorithm does not depend on global system parameters, or on the degree of event correlations, and hence can easily be deployed in practical scenarios. We analyze the performance of proposed algorithm for a single sensor scenario using Markov chains, and show that the proposed algorithm achieves near-optimal performance. Through extensive simulations, we demonstrate that the proposed algorithm not only achieves near-optimal performance, but also exhibits more stability with respect to sensor’s energy level and sleep interval variations. We validate the applicability of our proposed algorithm in the presence of multiple sensors and multiple event processes through simulations.     

Minimum latency joint scheduling and routing in wireless sensor networks

Wireless sensor networks are expected to be used in a wide range of applications from environment monitoring to event detection. The key challenge is to provide energy efficient communication; however, latency remains an important concern for many applications that require fast response. In this paper, we address the important problem of minimizing average communication latency for the active flows while providing energy-efficiency in wireless sensor networks. As the flows in some wireless sensor network can be long-lived and predictable, it is possible to design schedules for sensor nodes so that nodes can wake up only when it is necessary and asleep during other times. Clearly, the routing layer decision is closely coupled to the wakeup/sleep schedule of the sensor nodes. We formulate a joint scheduling and routing problem with the objective of finding the schedules and routes for current active flows with minimum average latency. By constructing a novel delay graph, the problem can be solved optimally by employing the M node-disjoint paths algorithm under FDMA channel model. We further present extensions of the algorithm to handle dynamic traffic changes and topology changes in wireless sensor networks.     

A probabilistic approach to statistical QoS provision of event detection in sensor networks

It is of significant importance to provide network-wide Quality of Service (QoS) for a wide range of event detection applications in wireless sensor networks. This paper investigates the important problem of QoS provision to abnormal event detection. For event detection applications, there are two key performance metrics, i.e., detection probability and detection latency. This paper considers both metrics, aiming to provide statistical QoS for abnormal event detection. It is, however, a challenging issue because of stringent resource constraints of sensor nodes and unpredictable randomness of physical events. We propose a probabilistic approach to statistical QoS provision for event detection in sensor networks. We propose a distributed algorithm that iteratively determines the active probability of each sensor node. The probability is kept small for energy efficiency but sufficiently large to provide the required detection QoS. Our approach is flexible and can detection QoS customized by applications. Comprehensive simulation experiments have been conducted, which demonstrate that our approach is able to provide the required detection QoS for event detection and achieves considerably longer the system lifetime compared with other competing schemes.     

基于事件优先级的地理哈希表分发算法

无线传感器网络综合了传感器技术,分布式信息处理技术和无线通信技术,能够协作地实时监测、感知和采集各种信息并对其进行处理,进而传给目标用户,能量和效率是传感器网络最重要的考虑因素。GHT-DCS是一种能量高效且在查询时延和存取能效上取得较好平衡的一种数据分发方式。然而,该算法主要集中在降低能量消耗,很少综合考虑查询时延,网络负载均衡,能量消耗这三个方面。针对多优先级的事件查询,在改进GHT-DCS的条件下,该文提出了基于事件优先级的地理哈希表的分发算法GP-GHT,通过划分扇形区域存储,节省存储能耗;通过定义优先级,使得高优先级的事件离查询节点更近,能更快地被搜索到。该算法降低了能源消耗,缩短查询时延,可满足不同优先级事件时延的需求。     

Energy-efficient target detection in sensor networks using line proxies

One of the fundamental and important operations in sensor networks is sink–source matching, i.e. target detection. Target detection is about how a sink finds the location of source nodes observing the event of interest (i.e. target activity). This operation is very important in many sensor network applications such as military battlefield and environment habitats. The mobility of both targets and sinks brings significant challenge to target detection in sensor networks. Most existing approaches are either energy inefficient or lack of fault tolerance in the environment of mobile targets and mobile sinks. Motivated by these, we propose an energy-efficient line proxy target detection (LPTD) approach in this paper. The basic idea of LPTD is to use designated line proxies as rendezvous points (or agents) to coordinate mobile sinks and mobile targets. Instead of having rendezvous nodes for each target type as used by most existing approaches, we adopt the temporal-based hash function to determine the line in the given time. Then the lines are alternated over time in the entire sensor network. This simple temporal-based line rotation idea allows all sensor nodes in the network to serve as rendezvous points and achieves overall load balancing. Furthermore, instead of network-wide flooding, interests from sinks will be flooded only to designated line proxies within limited area. The interest flooding can further decrease if the interest has geographical constraints. We have conducted extensive analysis and simulations to evaluate the performance of our proposed approach. Our results show that the proposed approach can significantly reduce overall energy consumption and target detection delay. Copyright © 2007 John Wiley & Sons, Ltd.     

Authentic delay bounded event detection in heterogeneous wireless sensor networks

When using wireless sensor networks for real-time event alarming, it is critical to ensure event notification in a timely manner. Additionally, it is extremely important to ensure the alarms generated by the sensors propagate securely through the network to the sink. Another important factor to consider is energy, as it is a limited resource in wireless sensor networks. Accordingly, maximizing network lifetime is always an optimization goal. To address the aforementioned concerns, in this paper we present the Authentic Delay Bounded Event Detection System (ADBEDS). ADBEDS works in rounds, and in each round an event detection tree is responsible for simultaneously detecting events, routing packets to a gateway node, and detecting injection of false packets. The ADBEDS can support k-watching composite events to allow event detection in a redundant manner. Additionally, the corresponding event alarm can be delivered within a user-specified bounded delay. The use of energy-based keying allows smaller, more efficient keys as input to security mechanisms, allowing further reduction in energy consumption of the ADBEDS. We evaluate the energy efficiency and reliability of ADBEDS using theoretical analysis and simulation.     

Delay aware reliable transport in wireless sensor networks

Wireless sensor networks (WSN) are event‐based systems that rely on the collective effort of several sensor nodes. Reliable event detection at the sink is based on collective information provided by the sensor nodes and not on any individual sensor data. Hence, conventional end‐to‐end reliability definitions and solutions are inapplicable in the WSN regime and would only lead to a waste of scarce sensor resources. Moreover, the reliability objective of WSN must be achieved within a certain real‐time delay bound posed by the application. Therefore, the WSN paradigm necessitates a collective delay‐constrained event‐to‐sink reliability notion rather than the traditional end‐to‐end reliability approaches. To the best of our knowledge, there is no transport protocol solution which addresses both reliability and real‐time delay bound requirements of WSN simultaneously. In this paper, the delay aware reliable transport (DART) protocol is presented for WSN. The objective of the DART protocol is to timely and reliably transport event features from the sensor field to the sink with minimum energy consumption. In this regard, the DART protocol simultaneously addresses congestion control and timely event transport reliability objectives in WSN. In addition to its efficient congestion detection and control algorithms, it incorporates the time critical event first (TCEF) scheduling mechanism to meet the application‐specific delay bounds at the sink node. Importantly, the algorithms of the DART protocol mainly run on resource rich sink node, with minimal functionality required at resource constrained sensor nodes. Furthermore, the DART protocol can accommodate multiple concurrent event occurrences in a wireless sensor field. Performance evaluation via simulation experiments show that the DART protocol achieves high performance in terms of real‐time communication requirements, reliable event detection and energy consumption in WSN. Copyright © 2007 John Wiley & Sons, Ltd.     

Exploiting Reactive Mobility for Collaborative Target Detection in Wireless Sensor Networks

Recent years have witnessed the deployments of wireless sensor networks in a class of mission-critical applications such as object detection and tracking. These applications often impose stringent Quality-of-Service requirements including high detection probability, low false alarm rate, and bounded detection delay. Although a dense all-static network may initially meet these Quality-of-Service requirements, it does not adapt to unpredictable dynamics in network conditions (e.g., coverage holes caused by death of nodes) or physical environments (e.g., changed spatial distribution of events). This paper exploits reactive mobility to improve the target detection performance of wireless sensor networks. In our approach, mobile sensors collaborate with static sensors and move reactively to achieve the required detection performance. Specifically, mobile sensors initially remain stationary and are directed to move toward a possible target only when a detection consensus is reached by a group of sensors. The accuracy of final detection result is then improved as the measurements of mobile sensors have higher Signal-to-Noise Ratios after the movement. We develop a sensor movement scheduling algorithm that achieves near-optimal system detection performance under a given detection delay bound. The effectiveness of our approach is validated by extensive simulations using the real data traces collected by 23 sensor nodes.     

无线传感器网络的蚁群自组织算法

探测效能与能量节省的综合性能优化是无线传感器网络研究的一个热点问题.提出了一种分布式、自适应的无线传感器网络蚁群自组织算法,将无线传感器网络节点映射为情绪蚂蚁,通过蚁群间的协同对节点的唤醒概率进行群体智能优化,从而实现无线传感器网络自组织,并以定理的形式给出了性能指标和相关参数的设计方法.仿真表明,算法实现在唤醒较少节点的前提下,对目标保持了较好的探测能力.     

Effective Energy Adaptive and Consumption in Wireless Sensor Network Using Distributed Source Coding and Sampling Techniques

Multimedia is the process of handling multiple medium of messages over network with high rate data services in wireless cellular area networks. Communication is the process of exchanging information form one service to another. In wireless networks are significantly growth of affecting network performance and energy consumption. The major problem is end to end delay in each node and meets the quality of services. The followings are considered for implementing wireless sensor network such as reduces the network delay, propagation delay and energy consumption. The senor node can sense the encoding value and reduce the network traffic delay using mitigation method. This paper propose a unique approach to provide simple routing services with reduced traffic delay, end to end delay network performance and to achieve better performance using Distributed Source Coding and Effective Energy Consumption methods. In this paper we use optimal early detection algorithm for improving network performance and energy consumption problem. An iterative Shannon fano and Tuker method is used for finding optimal solution of each node values. Network Simulator-3 is used for simulating network environments and setup the experiments. Our proposed method shows high data rate, good performance and low energy consumptions. The results compare with existing methodologies and performance is good.

     

基于移动Agent和WSN的突发事件场景数据收集算法研究

该文针对无线传感器网络应用于突发事件监测场景的能量消耗和网络延迟问题,提出了基于移动Agent的无线传感器网络簇式数据收集算法.动态成簇过程基于事件严重程度,并由其决定簇的生命周期和覆盖范围.Sink和簇头之间形成以Sink节点为簇头的虚拟簇.移动Agent迁移路径规划过程中下一跳节点的选取基于节点剩余能量、路径损耗及受刺激强度.移动Agent通过节点遍历的方式完成对所有簇内成员节点信息的收集.仿真结果表明,相对于C/S数据收集模型,基于移动Agent的模型具有更好的节能效果,并能一定程度地减少网络延迟,尤其适用于大规模无线传感器网络应用.     

Simultaneous spectrum sensing,data transmission and Energy harvesting in multi‐channel cognitive sensor Networks with imperfect signal cancellation

In multichannel cognitive sensor networks, the sensor users which have limited energy budgets sense the spectrum to determine the activity of the primary user. If the spectrum is idle, the sensor user can access the licensed spectrum. However, during the spectrum sensing, no data transmits. For improving the network throughput and saving more energy consumption, we propose the simultaneous spectrum sensing and data transmission scheme where the sensor receiver decodes the received signal, and from the remaining signal, the status of the channel (idle/busy) is determined. We also consider that the sensor users are powered by a radio‐frequency (RF) energy harvester. In this case, energy harvesting, data transmission, and spectrum sensing are done simultaneously. On the other hand, we select the proper sensor users for spectrum sensing and energy harvesting. We also allocate the best channels for data transmission simultaneously so that the network throughput maximizes and the constraints on the energy consumption and the detection performance are satisfied for each band. We formulate the problem and model it as a coalition game in which sensors act as game players and decide to make coalitions. Each coalition selects one of the channels to sense and transmit data, while the necessary detection probability and false alarm probability and also the energy consumption constraints are satisfied. The utility function of a coalition is proposed based on the energy consumption, false alarm probability, detection probability, and the network throughput. This paper proposes an efficient algorithm to reach a Nash‐stable coalition structure. It is demonstrated that the proposed method maximizes the network throughput and reduces the energy consumption while it provides sufficient detection quality, in comparison to other existent methods.     

RESIDENT: a reliable residue number system-based data transmission mechanism for wireless sensor networks

Retransmission is the most common data transmission mechanism in wireless sensor networks, and can improve data transmission reliability via the acknowledgement mechanism. However, the simple acknowledgement retransmission is associated with some negative factors such as data delay, low throughput among others. To overcome the shortcomings of the retransmission mechanism, redundancy coding is introduced to wireless communications, which has been widely applied in 4G communication. Unfortunately, not all redundant erasure codes are suitable for wireless sensor networks, as nodes’ energy, processing power, and storage capacity are all limited. Moreover, we also need to consider data transmission delay. Therefore, to improve data transmission reliability, we must take into account the complexity of algorithm, data transmission delay, node energy consumption, and other factors. In this article, we propose a REliable reSIDuE number system-based data transmission mechanism (RESIDENT) for WSNs, which can improve data transmission reliability via hybrid automatic repeat requests in hop-by-hop scenarios. In order to decrease the complexity of decoding, we present our algorithm and the proof of correctness, and report the performance using extensive set of simulation experiments. Our simulation results show that RESIDENT exhibits a good performance when compared to the previous studies, not only in terms of reliable data transmission, but also in end-to-end delay and energy consumption.     

Energy Planning for Progressive Estimation in Multihop Sensor Networks

Multihop sensor networks where transmissions are conducted between neighboring sensors can be more efficient in energy and spectrum than single-hop sensor networks where transmissions are conducted directly between each sensor and a fusion center. With the knowledge of a routing tree from all sensors to a destination node, we present a digital transmission energy planning algorithm as well as an analog transmission energy planning algorithm for progressive estimation in multihop sensor networks. Unlike many iterative consensus-type algorithms, the proposed progressive estimation algorithms along with their transmission energy planning further reduce the network transmission energy while guaranteeing any pre-specified estimation performance at the destination node within a finite time. We also show that digital transmission is more efficient in transmission energy than analog transmission if the available transmission time-bandwidth product for each link and each observation sample is not too limited.     

Bounded end-to-end delay with Transmission Power Control techniques for rechargeable wireless sensor networks

Due to sporadic availability of energy, a fundamental problem in rechargeable wireless sensor networks is nodes have to adjust their duty cycles continuously. On the other hand, the energy harvested from surrounding environment usually is not enough to power sensor nodes continually. Therefore, the nodes have to operate in a very low duty cycle. These unique characteristics cause packet delivery latency is critical in Rechargeable WSNs. At the same time, energy storage device of a node is always limited. Hence, the node cannot be always beneficial to conserve energy when a network can harvest excessive energy from the environment. In this work, we introduce a scheme by improving transmission power of nodes to bound E2E delay. We provide an algorithm for finding the minimal sleep latency from a node to a sink by increasing minimal h number of nodes whose transmission power improved. For bounding E2E delay from source node to the sink, we propose an E2E delay maintenance solution. Through extensive simulation and experiments, we demonstrate our delay bound maintenance scheme is efficient to provide E2E delay guarantees in rechargeable wireless sensor networks.     

多传感器分布式检测系统的跨层优化设计

目标检测就是判断被监测对象是否出现,是无线传感器网络应用的首要前提.由于传感器节点协作执行检测任务,因此,应用于通信网中的解耦和最大吞吐量的网络设计不能使系统检测性能最优.提出了集成物理层、MAC层和应用层的跨层设计,设计了感知信息质量、信道状态和有效能量协同的传输控制策略,该传输策略可以有效地调节节点和融合中心的通信使系统的检测性能最优.最后,通过解决非线性约束优化问题分别为ALOHA和TDMA传感器网络得到最优的设计变量,并与典型的解耦和最大吞吐量设计比较检测性能增益.     

物联网感知层多路径传输策略研究

多路径数据传输是无线传感器网络亟需解决的一个关键问题.本文针对节点故障、链路失效和外界干扰影响网络稳定性和可靠性,提出一种基于混合蛙跳算法的无线传感器网络多路径传输策略.首先我们详细介绍了蛙跳算法及其原理,之后我们将其应用到无线传感器网络多路径传输策略之中,接着运用混合蛙跳算法对传感网络节点其进行更新、划分、重组以便选择出最优节点建立传输最优路径,提高网络的稳定性和可靠性.通过算法仿真与结果对比提出的算法与AODV、粒子群PSO算法相比,在网络能耗、传输时延、丢包率、连通率和可靠度等方面都具有较好的性能.其中网络能耗比AODV、PSO算法降低了62.5％和35.8％.     

Hierarchical Tree Alternative Path (HTAP) algorithm for congestion control in wireless sensor networks

Recent advances in wireless sensor networks (WSNs) have lead to applications with increased traffic demands. Research is evolving from applications where performance is not considered as a crucial factor, to applications where performance is a critical factor. There are many cases in the fields of automation, health monitoring, and disaster response that demand wireless sensor networks where performance assurances are vital, especially for parameters like power, delay, and reliability. Due to the nature of these networks the higher amount of traffic is observed when the monitored event takes place. Exactly at this instance, there is a higher probability of congestion appearance in the network. Congestion in WSNs is tackled by the employment of two methods: either by reducing the load (“traffic control”), or by increasing the resources (“resource control”). In this paper we present the Hierarchical Tree Alternative Path (HTAP) algorithm, a “resource control” algorithm that attempts, through simple steps and minor computations, to mitigate congestion in wireless sensor networks by creating dynamic alternative paths to the sink. HTAP is evaluated in several scenarios in comparison with another “resource control” algorithm (TARA), as well as with a “traffic control” algorithm (SenTCP), and also the case where no congestion control exists in the network (“no CC”). Results show that HTAP is a simple and efficient algorithm capable of dealing successfully with congestion in WSNs, while preserving the performance characteristics of the network.     

Queue‐based congestion detection and multistage rate control in event‐driven wireless sensor networks

Protocols for sensor networks have traditionally been designed using the best effort delivery model. However, there are many specific applications that need reliable transmissions. In event‐driven wireless sensor networks, the occurrence of an event may generate a large amount of data in a very short time. Among them, some critical urgent information needs to be transmitted reliably in a timely manner. In this scenario, congestion is inevitable because of the constraints in available resources. How to control the congestion is very important for the reliable transmission of urgent information. To address this problem, we propose a queue‐based congestion detection and a multistage rate control mechanism. In our proposed mechanism, not only the current queue length but also the queue fluctuation are adopted as indications of congestion. Each sensor node evaluates its congestion level locally and determines its congestion state with a state machine. We design a multistage rate adjustment mechanism for nodes to adjust their rates depending on their congestion states. We also distinguish high‐priority critical traffic from low‐priority non‐critical traffic. Extensive simulation results confirm the superior performance of our proposed protocol with respect to throughput, loss probability, and delay.Copyright © 2012 John Wiley & Sons, Ltd.     

A lifetime enhancement protocol in cluster‐based wireless sensor networks with guaranteed delay

Wireless sensor networks nowadays find application in all the fields of the world. Rare event detection is an important application in which the wireless sensor network is used. In the case of rare event detection, event of interest or the important event occurs very rarely. Battery‐powered sensor nodes are deployed to detect the event and report to the base station. Sensing and communicating the low priority events happen in major portion of the lifetime for the sensor nodes. However, if the event occurs, then it should be detected and communicated at the earliest to the base station or to the sink node. To reduce the network traffic due to low priority data, we propose a cross layered algorithm to improve the lifetime of the sensor nodes in the case of clustered architecture. In spite of the increase in the network lifetime, the time to detect and communicate to the base station is maintained as that of the traditional clustering approach. The proposed algorithm is simulated, and results show significant improvement in the lifetime of the sensor nodes with guaranteed latency. In this paper, we also suggest methods to support the latency to sensor nodes on priority basis for continuous reporting.