多感知范围无线传感器网络中一种分布式目标覆盖算法

基于多感知范围无线传感器网络中节点与目标的覆盖关系,设计了一种目标生命期评估机制。鉴于网络生命期由具有最小生命期的目标决定,在分析节点感知半径变更影响的基础上,提出了两种提高最小目标生命期的策略,建立了一个动态目标覆盖博弈模型,并证明了该博弈存在纯策略的纳什均衡。本文设计了一种分布式目标覆盖算法,算法中节点根据邻居节点的能量分布和目标覆盖情况,选用最优感知半径,以确保目标完全覆盖并延长最小目标生命期。仿真结果表明,在不同的网络中所提算法均能有效地延长网络生命期。     

传感器网络中数据驱动的睡眠调度机制

在能量受限的传感器网络中,尽量延长网络寿命同时保证服务质量(如感知覆盖和数据完整)是关键的研究问题.节点睡眠调度能有效延长网络寿命.研究数据驱动的睡眠调度机制,利用感知数据的时空相关性识别冗余节点.核心思想是用非参数回归方法为节点建立预测模型,求解最大支配数的节点支配集,调度多个支配集轮流工作.睡眠节点的数据可以由支配集节点恢复.分别给出集中式、半分布式和分布式3个睡眠调度方法.据知,这是第1个将统计回归模型用于睡眠调度并扩展到大规模网络的研究.实验结果表明,该方法能够有效地减少活跃节点个数,节省能耗从而延长网络寿命,同时在用户指定误差范围内保证数据的完整性.     

Event-based motion control for mobile-sensor networks

In many sensor networks, considerably more units are available than necessary for simple coverage of the space. Augmenting sensor networks with motion can exploit this surplus to enhance sensing while also improving the network's lifetime and reliability. Sensor mobility allows better coverage in areas where events occur frequently. Another use of mobility comes about if the specific area of interest (within a larger area) is unknown during deployment. We've developed distributed algorithms for mobile-sensor networks to physically react to changes or events in their environment or in the network itself. Distribution supports scalability and robustness during sensing and communication failures. We present two classes of motion-control algorithms that let sensors converge on arbitrary event distributions. These algorithms trade off the amount of required computation and memory with the accuracy of the sensor positions. We also present three algorithms that let sensor networks maintain coverage of their environment. These algorithms work alongside either type of motion-control algorithm such that the sensors can follow the control law unless they must stop to ensure coverage.     

Accuracy vs. Lifetime: Linear Sketches for Aggregate Queries in Sensor Networks

The in–network aggregation paradigm in sensor networks provides a versatile approach for evaluating aggregate queries. Traditional approaches need a separate aggregate to be computed and communicated for each query and hence do not scale well with the number of queries. Since approximate query results are sufficient for many applications, we use an alternate approach based on summary data–structures. We consider two kinds of aggregate queries: location range queries that compute the sum of values reported by sensors in a given location range, and value range queries that compute the number of sensors that report values in a given range. We construct summary data–structures called linear sketches, over the sensor data using in–network aggregation and use them to answer aggregate queries in an approximate manner at the base–station. There is a trade–off between accuracy of the query results and lifetime of the sensor network that can be exploited to achieve increased lifetimes for a small loss in accuracy. Most commonly occurring sets of range queries are highly correlated and display rich algebraic structure. Our approach takes full advantage of this by constructing linear sketches that depend on queries. Experimental results show that linear sketching achieves significant improvements in lifetime of sensor networks for only a small loss in accuracy of the queries. Further, our approach achieves more accurate query results than the other classical techniques using Discrete Fourier Transform and Discrete Wavelet Transform. This work was supported in part by NASA under Cooperative Agreement NCC5–315.     

Multiround Distributed Lifetime Coverage Optimization protocol in wireless sensor networks

Coverage and lifetime are two paramount problems in wireless sensor networks (WSNs). In this paper, a method called Multiround Distributed Lifetime Coverage Optimization protocol (MuDiLCO) is proposed to maintain the coverage and to improve the lifetime in wireless sensor networks. The area of interest is first divided into subregions, and then the MuDiLCO protocol is distributed to the sensor nodes in each subregion. The proposed MuDiLCO protocol works in periods during which sets of sensor nodes are scheduled, with one set for each round of a period, to remain active during the sensing phase and thus ensure coverage so as to maximize the WSN lifetime. The decision process is carried out by a leader node, which solves an optimization problem to produce the best representative sets to be used during the rounds of the sensing phase. The optimization problem formulated as an integer program is solved to optimality through a Branch-and-Bound method for small instances. For larger instances, the best feasible solution found by the solver after a given time limit threshold is considered. Compared with some existing protocols, simulation results based on multiple criteria (energy consumption, coverage ratio, and so on) show that the proposed protocol can prolong efficiently the network lifetime and improve the coverage performance.     

Optimal energy allocation in heterogeneous wireless sensor networks for lifetime maximization

We consider the problem of optimal energy allocation and lifetime maximization in heterogeneous wireless sensor networks. We construct a probabilistic model for heterogeneous wireless sensor networks where sensors can have different sensing range, different transmission range, different energy consumption for data sensing, and different energy consumption for data transmission, and the stream of data sensed and transmitted from a sensor and the stream of data relayed by a sensor to a base station are all treated as Poisson streams. We derive the probability distribution and the expectation of the number of data transmissions during the lifetime of each sensor and the probability distribution and the expectation of the lifetime of each sensor. In all these analysis, energy consumption of data sensing and data transmission and data relay are all taken into consideration. We develop an algorithm to find an optimal initial energy allocation to the sensors such that the network lifetime in the sense of the identical expected sensor lifetime is maximized. We show how to deal with a large amount of energy budget that may cause excessive computational time by developing accurate closed form approximate expressions of sensor lifetime and network lifetime and optimal initial energy allocation. We derive the expected number of working sensors at any time. Based on such results, we can find the latest time such that the expected number of sensors that are still functioning up to that time is above certain threshold.     

Connectivity and coverage maintenance in wireless sensor networks

One of the main design challenges for wireless sensor networks (WSNs) is to obtain long system lifetime without sacrificing system original performance such as communication connectivity and sensing coverage. A large number of sensor nodes are deployed in redundant fashion in dense sensor networks, which lead to higher energy consumption. We propose a distributed framework for energy efficient connectivity and coverage maintenance in WSNs. In our framework, each sensor makes self-scheduling to separately control the states of RF and sensing unit based on dynamic coordinated reconstruction mechanism. A novel energy-balanced distributed connected dominating set algorithm is presented to make connectivity maintenance; and also a distributed node sensing scheduling is brought forward to maintain the network coverage according to the surveillance requirements. We implemented our framework by C++ programming, and the simulation results show that our framework outperforms several related work by considerably improving the energy performance of sensor networks to effectively extend network lifetime.     

入侵轨迹建模与WSN栅栏覆盖分段调度算法研究

无线传感器网络栅栏覆盖在入侵检测方面发挥着重要作用,如何调度栅栏并延长网络的生存时间已成为重点研究问题.在无线传感器网络中设计合理的调度算法,分时激活传感器节点从而延长网络生存时间是大多数研究的方向,然而仅仅通过分时调度传感器节点已很难大幅度提高网络的生存时间.因此设计了一种分时与分段相结合的无线传感器网络栅栏调度算法,该算法通过分析入侵目标穿越传感器网络部署区域的行为特征,建立入侵目标的轨迹模型,该模型在保证栅栏对入侵目标具有较高检测率的情况下预测入侵目标可能穿越栅栏的区域并分段激活栅栏从而大大减少了传感器节点的能量消耗.最后仿真实验验证了本文算法与传统的分时调度算法相比能大幅度提高网络的生存时间.     

Ant colony optimization based sensor deployment protocol for wireless sensor networks

Sensor deployment is one of the most important issues in wireless sensor networks, because an efficient deployment scheme can reduce the deployment cost and enhance the detection capability of the wireless sensor networks. In addition, it can enhance the quality of monitoring in wireless sensor networks by increasing the coverage area. Ant colony optimization (ACO) algorithm provides a natural and intrinsic way of exploration of search space for multiple knapsack problem (MKP). In this work, we consider the problem of sensor deployment to achieve complete coverage of the service region and maximize the lifetime of the network. We model the deployment problem as the multiple knapsack problem. Based on ACO algorithm, we proposed a deployment scheme to prolong the network lifetime, while ensuring complete coverage of the service region. The simulations show that our algorithm can prolong the lifetime of the network.     

Active node determination for correlated data gathering in wireless sensor networks

In wireless sensor network applications where data gathered by different sensor nodes is correlated, not all sensor nodes need to be active for the wireless sensor network to be functional. Given that the sensor nodes that are selected as active form a connected wireless network, the inactive sensor nodes can be turned off. Allowing some sensor nodes to be active and some sensor nodes inactive interchangably during the lifecycle of the application helps the wireless sensor network to have a longer lifetime. The problem of determining a set of active sensor nodes in a correlated data environment for a fully operational wireless sensor network can be formulated as an instance of the connected correlation-dominating set problem. In this work, our contribution is twofold; we propose an effective and runtime-efficient iterative improvement heuristic to solve the active sensor node determination problem, and a benefit function that aims to minimize the number of active sensor nodes while maximizing the residual energy levels of the selected active sensor nodes. Extensive simulations we performed show that the proposed approach achieves a good performance in terms of both network lifetime and runtime efficiency.     

Network lifetime bounds for hierarchical wireless sensor networks in the presence of energy constraints

In previous years, one popular problem that is constantly being researched into is how to prolong the lifetime of wireless sensor networks (WSNs). Many approaches to maximize network lifetime have been proposed and each approach provides different levels of energy savings and are efficient in their own aspects. However, these proposed algorithms are not suitable for use in a hard network lifetime environment where participating sensors should be working till the strict network lifetime requirement. The predictability of the network lifetime plays an important role in supporting guaranteed network lifetime services. This can be provided through the schedulability test that complements the online operations of safe and critical sensor network systems. In this paper, we focus on the study of the predictability of the network lifetime to enable the High Energy First clustering algorithm (HEF) to work in a hard lifetime environment and present a schedulability test to verify whether HEF can make the set of sensors schedulable in terms of N-of-N and K-of-N alive nodes.     

Heuristic routing with bandwidth and energy constraints in sensor networks

Most of the routing algorithms devised for sensor networks considered either energy constraints or bandwidth constraints to maximize the network lifetime. In the real scenario, both energy and bandwidth are the scarcest resource for sensor networks. The energy constraints affect only sensor routing, whereas the link bandwidth affects both routing topology and data rate on each link. Therefore, a heuristic technique that combines both energy and bandwidth constraints for better routing in the wireless sensor networks is proposed. The link bandwidth is allocated based on the remaining energy making the routing solution feasible under bandwidth constraints. This scheme uses an energy efficient algorithm called nearest neighbor tree (NNT) for routing. The data gathered from the neighboring nodes are also aggregated based on averaging technique in order to reduce the number of data transmissions. Experimental results show that this technique yields good solutions to increase the sensor network lifetime. The proposed work is also tested for wildfire application.     

A pre-determined node deployment strategy to prolong network lifetime in wireless sensor network

Energy is one of the scarcest resources in a wireless sensor network (WSN). Therefore, the need to conserve energy is of utmost importance in WSN. There are many ways to conserve energy in such a network. One fundamental way of conserving energy is judicious deployment of sensor nodes within the network area so that the energy flow remains balanced throughout the network. This avoids the problem of occurrence of ‘energy holes’ and ensures prolonged network lifetime. We have investigated the problem of uniform node distribution and shown its incapability to deal with the energy hole problem. Next we have derived the principle of non-uniform node distribution that ensures energy balancing. Further, we have developed a non-uniform, location-wise pre-determined node deployment strategy based on this principle leading to an increase in network lifetime. Finally exhaustive simulation is performed to substantiate our claim of energy balancing and subsequent enhancement of network lifetime. The results are compared with an existing work to prove the efficacy of our scheme.     

Using mobile data collectors to improve network lifetime of wireless sensor networks with reliability constraints

In this paper, we focus on maximizing network lifetime of a Wireless Sensor Network (WSN) using mobile Data Collectors (DCs) without compromising on the reliability requirements. We consider a heterogeneous WSN which consists of a large number of sensor nodes, a few DCs, and a static Base Station (BS). The sensor nodes are static and are deployed uniformly in the terrain. The DCs have locomotion capabilities and their movement can be controlled. Each sensor node periodically sends sensed event packets to its nearest DC. The DCs aggregate the event packets received from the sensor nodes and send these aggregate event packets to the static BS. We address the following problem: the DCs should send the aggregate event packets to the BS with a given reliability while avoiding the hotspot regions such that the network lifetime is improved. Reliability is achieved by sending each aggregate event packet via multiple paths to the BS. The network lifetime is maximized by moving the DCs in such a way that the forwarding load is distributed among the sensor nodes. We propose both centralized and distributed approaches for finding a movement strategy of the DCs. We show via simulations that the proposed approaches achieve the required reliability and also maximize the network lifetime compared to the existing approaches.     

Rate-lifetime tradeoff for reliable communication in wireless sensor networks

The network lifetime and application performance are two fundamental, yet conflicting, design objectives in wireless sensor networks. There is an intrinsic tradeoff between network lifetime maximization and application performance maximization, the latter being often correlated to the rate at which the application can send its data reliably in sensor networks. In this paper we study this tradeoff by investigating the interactions between the network lifetime maximization problem and the rate allocation problem with a reliable data delivery requirement. Severe bias on the allocated rates of some sensor nodes may exist if only the total throughput of the sensor network is maximized, hence we enforce fairness on source rates of sensor nodes by invoking the network utility maximization (NUM) framework. To guarantee reliable communication, we adopt the hop-by-hop retransmission scheme. We formulate the network lifetime maximization and fair rate allocation both as constrained maximization problems. We characterize the tradeoff between them, give the optimality condition, and derive a partially distributed algorithm to solve the problem. Furthermore, we propose an approximation of the tradeoff problem using NUM framework, and derive a fully distributed algorithm to solve the problem.     

一种高跟踪质量保证的预先节点选择策略

为保证传感器网络节点高质量的目标跟踪效果,采用在目标移动的方向上提前选择一些节点进行监控的策略,保证当目标移动到新的位置时总有监测节点进行持续的监测,使这些监测节点总是离目标最近,感知质量最高;该策略依据网络能量消耗的不均衡性,在能量有剩余的区域提前唤醒更多的节点,而在能量消耗紧张的区域少唤醒节点,与其他策略相比并没有降低网络寿命。通过实验性能分析对比表明：该策略可以在不降低网络寿命的前提下大幅度提升跟踪质量。     

Energy-efficient area monitoring for sensor networks

The nodes in sensor networks must self-organize to monitor the target area as long as possible. Researchers at the Fundamental Computer Science Laboratory of Lille are developing strategies for selecting and updating an energy-efficient connected active sensor set that extends the network lifetime. We report on their work to optimize energy consumption in three separate problems: area coverage, request spreading, and data aggregation.     

Wireless Sensor Network Lifetime Analysis Using Interval Type-2 Fuzzy Logic Systems

Extending the lifetime of the energy constrained wireless sensor networks is a crucial challenge in sensor network research. In this paper, we present a novel approach based on fuzzy logic systems to analyze the lifetime of a wireless sensor network. We demonstrate that a type-2 fuzzy membership function (MF), i.e., a Gaussian MF with uncertain standard deviation (std) is most appropriate to model a single node lifetime in wireless sensor networks. In our research, we study two basic sensor placement schemes: square-grid and hex-grid. Two fuzzy logic systems (FLSs): a singleton type-1 FLS and an interval type-2 FLS are designed to perform lifetime estimation of the sensor network. We compare our fuzzy approach with other nonfuzzy schemes in previous papers. Simulation results show that FLS offers a feasible method to analyze and estimate the sensor network lifetime and the interval type-2 FLS in which the antecedent and the consequent membership functions are modeled as Gaussian with uncertain std outperforms the singleton type-1 FLS and the nonfuzzy schemes.     

Distributed optimal dynamic base station positioning in wireless sensor networks

Base station (BS) positioning is an effective method for improving the performance of wireless sensor networks (WSNs). A metric-aware optimal BS positioning and relocation mechanism for WSNs is proposed. This technique locates the BS with respect to the available resources and the amount of traffic traveling through the sensor nodes. The BS calculates its own position over time in response to the dynamic environment in which the sensor nodes operate. In most WSN environments, communication channel experiences nonlinearity that is influenced by path loss, attenuation of signal as it propagated through space, greater than 2. In this work, we solved the problem of BS positioning in nonlinear environments. We propose a weighted linear or nonlinear least squares optimization depending on the value of the path loss exponent. We also propose a distributed algorithm that can effectively handle the required computation by exploiting node cooperation. The goal is to minimize the total energy consumption and to prolong lifetime of the WSNs. The performance of the proposed technique is evaluated for various network setups and conditions. Our simulation results demonstrate that BS positioning and relocation can significantly improve the lifetime and power efficiency in WSNs.     

Algorithm for equalization of cluster lifetimes in a multi-level Beacon enabled 802.15.4 sensor network

We consider the problem of maintaining the prescribed event sensing reliability while maximizing cluster and network lifetime in a multi-cluster 802.15.4 sensor network. Clusters are connected through bridges which also act as cluster coordinators; both ordinary nodes and bridges resolve contention using the CSMA-CA algorithm. Cluster lifetime is maximized through the use of redundant sensors which are periodically sent to sleep using a simple distributed activity management algorithm. Network lifetime is maximized by equalizing energy consumption per backoff period in all clusters through the adjustment of the number of nodes. We model this problem analytically using the datasheet for tmote_sky ultra low power IEEE 802.15.4 compliant wireless sensor module [tmote sky lowpower wireless sensor module, Moteiv Corporation, San Francisco, CA, www.moteiv.com, tmote datasheet 802.15.4, 2006] and derive the probability distribution of the network lifetime. We also derive the expression for node count that compensates for the increased load due to contention caused by the bridge. Numerical results show that this technique easily equalizes cluster lifetimes.