二值传感器网络的分布式稀疏LMS算法

在基于无线传感器网络的参数估计中,每个节点在数据采集、存储、处理和传输等方面的能力是有限的。二值传感器网络中的每个节点只能提供低精度1比特测量值,与能够提供模拟测量值（无限精度）的传感器相比,二值传感器有较低的使用成本。如何利用低成本二值传感器网络获得较好的参数估计性能近些年已引起广泛关注,基于该二值传感器网络,论文提出了一种分布式稀疏参数估计的自适应最小均方（LMS）算法。该算法采用稀疏惩罚最大似然优化,并结合期望最大化和LMS方法,获得稀疏信号的在线估计。仿真实验表明,尽管只采用1比特测量,提出的算法仍具有较好的收敛性,并且稳定状态的估计误差接近于非1比特测量的同类算法。      

Efficient Hardware-Based Image Compression Schemes for Wireless Sensor Networks: A Survey

Multidimensional sensors, such as digital camera sensors in the visual sensor networks VSNs generate a huge amount of information compared with the scalar sensors in the wireless sensor networks WSNs. Processing and transmitting such data from low power sensor nodes is a challenging issue through their limited computational and restricted bandwidth requirements in a hardware constrained environment. Source coding can be used to reduce the size of vision data collected by the sensor nodes before sending it to its destination. With image compression, a more efficient method of processing and transmission can be obtained by removing the redundant information from the captured image raw data. In this paper, a survey of the main types of the conventional state of the art image compression standards such as JPEG and JPEG2000 is provided. A literature review of their advantages and shortcomings of the application of these algorithms in the VSN hardware environment is specified. Moreover, the main factors influencing the design of compression algorithms in the context of VSN are presented. The selected compression algorithm may have some hardware-oriented properties such as; simplicity in coding, low memory need, low computational load, and high-compression rate. In this survey paper, an energy efficient hardware based image compression is highly requested to counter the severe hardware constraints in the WSNs.     

TDMA scheduling algorithms for wireless sensor networks

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.     

Cooperative Communications in Resource-Constrained Wireless Networks

Cooperative communications have been proposed to exploit the spatial diversity gains inherent in multiuser wireless systems without the need of multiple antennas at each node. This is achieved by having the users relay each others messages and thus forming multiple transmission paths to the destination. In resource constrained networks, such as wireless sensor networks, the advantages of cooperation can be further exploited by optimally allocating the energy and bandwidth resources among users based on the available channel state information (CSI) at each node. In the first part of this article, we provide a tutorial survey on various power allocation strategies for cooperative networks based on different cooperation strategies, optimizing criteria, and CSI assumptions. In the second part, we identify the similarities between cooperative networks and several sensor network applications that utilize collaboration among distributed sensors to achieve the system goal. These applications include decentralized detection/estimation and data gathering. The techniques developed in cooperative communications can be used to solve many sensor network problems     

Energy Efficient Four Level Cooperative Opportunistic Communication for Wireless Personal Area Networks (WPAN)

For wireless sensor networks (WSNs), energy is a scarce resource. Due to limited battery resources, the energy consumption is the critical issue for the transmission as well as reception of the signals in the wireless communication. WSNs are infrastructure-less shared network demanding more energy consumption due to collaborative transmissions. This paper proposes a new cooperative opportunistic four level model for IEEE 802.15.4 wireless personal area network. The average per node energy consumption is observed merely about 0.17 mJ for the cooperative wireless communication which proves the proposed mechanism to be energy efficient. This paper further proposes four levels of cooperative data transmission from source to destination to improve network coverage with energy efficiency.     

Distributed Estimation in Energy-Constrained Wireless Sensor Networks

In this paper, we consider distributed estimation of a noise-corrupted deterministic parameter in energy-constrained wireless sensor networks from energy-distortion perspective. Given a total energy budget allowable to be used by all sensors, there exists a tradeoff between the subset of active sensors and the energy used by each active sensor in order to minimize the estimation MSE. To determine the optimal quantization bit rate and transmission energy of each sensor, a concept of equivalent unit-energy MSE function is introduced. Based on this concept, an optimal energy-constrained distributed estimation algorithm for homogeneous sensor networks and a quasi-optimal energy-constrained distributed estimation algorithm for heterogeneous sensor networks are proposed. Moreover, the theoretical energy-distortion performance bound for distributed estimation is addressed and it is shown that the proposed algorithm is quasi-optimal within a factor 2 of the theoretical lower bound. Simulation results also show that the proposed method can achieve a significant reduction in the estimation MSE when compared with other uniform schemes. Finally, the proposed algorithm is easy to implement in a distributed manner and it adapts well to the dynamic sensor environments.     

Energy-aware redundancy-aware clustering in wireless sensor networks using Spined Loach Searching Optimization

Wireless sensor networks play dominant role in data communication in many engineering applications and faces lot of challenges in its implementation. Energy conservation is also significantly required in these systems as the sensor nodes are battery operated. Hence, the energy efficient-based technique needs to be implemented in data transmission. The most widely used methods are clustering-based data transmission and energy efficient routing detection. In clustering, the proper selection of cluster head (CH) node is important to ensure energy balancing. The CH node should have more residual energy as it does many transmissions in the network. Moreover, the location of CH node should be nearer to all member nodes in the cluster. The clustering process must also perform the job of avoiding unnecessary transmissions. By considering these factors, the CH node can be optimally selected using Spined Loach Searching Optimization algorithm. The food searching behavior and environmental suitability for spiny loach fish living are deliberated to develop this bio-inspired algorithm. In addition, the redundant transmissions inside the clusters can be reduced by employing a new technique called Least Difference Threshold Based Similarity Grouping. This work improves energy efficiency comparing with the conventional low energy adaptive clustering hierarchy protocol, and it is evaluated by setting the network in simulation environment. The network lifetime is increased; energy consumption, delay of transmission and the message cost are reduced.     

A Simple Algorithm for Data Compression in Wireless Sensor Networks

Power saving is a critical issue in wireless sensor networks (WSNs) since sensor nodes are powered by batteries which cannot be generally changed or recharged. As radio communication is often the main cause of energy consumption, extension of sensor node lifetime is generally achieved by reducing transmissions/receptions of data, for instance through data compression. Exploiting the natural correlation that exists in data typically collected by WSNs and the principles of entropy compression, in this Letter we propose a simple and efficient data compression algorithm particularly suited to be used on available commercial nodes of a WSN, where energy, memory and computational resources are very limited. Some experimental results and comparisons with, to the best of our knowledge, the only lossless compression algorithm previously proposed in the literature to be embedded in sensor nodes and with two well- known compression algorithms are shown and discussed.     

基于ERPMT改进启发式方法的WSN寿命最大化算法

针对传感器节点的电池容量限制导致无线传感网络寿命低的问题,基于容量最大化(CMAX)、线上最大化寿命(OML)两种启发式方法以及高效路由能量管理技术(ERPMT),提出了基于ERPMT改进启发式方法的无线传感网络寿命最大化算法。首先,通过启发式方法初始化每个传感器节点,将节点能量划分为传感器节点起源数据和其它节点数据延迟;然后利用加入的一种优先度量延迟一跳节点的能量消耗;最后,根据路径平均能量为每个路由分配一个优先级,并通过ERPMT实现最终的无线传感网络优化。针对不同分布类型网络寿命的实验验证了本文算法的有效性及可靠性,实验结果表明,相比较为先进的启发式方法CMAX及OML,本文算法明显增大了无线传感网络的覆盖范围,并且大大地延长了网络的寿命。     

Minimizing the Number of Multicast Transmissions in Single-Hop WDM Networks

The problem of minimizing the number of transmissions for a multicast transmission under the condition that the packet delay is minimum in single-hop wavelength division multiplexing (WDM) networks is studied in this paper. This problem is proved to be NP-complete. A heuristic multicast scheduling algorithm is proposed for this problem. Extensive simulations are performed to compare the performance of the proposed heuristic algorithm with two other multicast scheduling algorithms, namely, the greedy and no-partition scheduling algorithms. The greedy algorithm schedules as many destination nodes as possible in the earliest data slot. The no-partition algorithm schedules the destination nodes of a multicast packet to receive the packet in the same data slot without partitioning the multicast transmission into multiple unicast or multicast transmissions. Our simulation results show that (i) an algorithm which partitions a multicast transmission into multiple unicast or multicast transmissions may not always produce lower mean packet delay than the no-partition algorithm when the number of data channels in the system is limited and (ii) the proposed heuristic algorithm always produces lower mean packet delay than the greedy and the no-partition algorithms because this algorithm not only partitions a multicast transmission into multiple unicast or multicast transmissions to keep the packet delay low but also reduces the number of transmissions to conserve resources.     

Towards broadcast redundancy minimization in duty‐cycled wireless sensor networks

Broadcast is an essential operation in wireless sensor networks. Because of the necessity of energy conservation, minimizing the number of transmissions is always a challenging issue in broadcasting scheme design. This paper studies the minimum‐transmission broadcast problem in duty‐cycled wireless sensor networks where each sensor operates under active/dormant cycles. To address the problem, our proposed scheme, Broadcast Redundancy Minimization Scheduling (BRMS), finds a set of forwarding nodes, which minimizes the number of broadcast transmissions. Then, it constructs a forest of sub‐trees based on the relationship between each forwarding node and its corresponding receivers. A broadcast tree is constructed ultimately by connecting all sub‐trees with a minimum number of connectors. Theoretical analysis shows that BRMS obtains a lower approximation ratio as well as time complexity compared with existing schemes. A set of extensive simulations is conducted to evaluate the performance of BRMS. The results reveal that BRMS outperforms others and its solution is close to the lower bound of the problem in terms of the total number of transmissions. Copyright © 2016 John Wiley & Sons, Ltd.     

Polynomial time solution to minimum forwarding set problem in wireless networks under disk coverage model

In this paper, we consider a practical problem, called Minimum Forwarding Set Problem (MFSP), that emerges within the context of implementing (energy efficient) communication protocols for wireless ad hoc or sensor networks. For a given node v, MFSP asks for a minimum cardinality subset of 1-hop neighbors of v to cover v’s 2-hop neighbors. MFSP problem is also known as multi-point relay (MPR) problem. It is shown to be an NP-complete problem for its general case that does not consider the coverage characteristics of wireless transmissions. In this paper, we present two polynomial time algorithms to solve the MFSP problem under disk coverage model for wireless transmissions. In our earlier work, we presented a polynomial time algorithm for this problem under unit disk coverage model. In the current work, we present several observations on the geometric characteristics of wireless transmissions under disk coverage model and build two alternative dynamic programming based solutions with different run time and space complexities to the problem. Disk coverage model is a more general model because it allows nodes to use arbitrary power levels for transmissions. As a result, the presented algorithms provide a more practical solution that can be used as a building block for energy efficient communication protocols designed for wireless ad hoc and sensor networks.     

无线传感器网络中基于概率的能量平衡算法

各传感器节点的能耗不平衡严重地影响了无线传感器网络的生命周期。该文提出了基于传输概率的能量平衡算法。首先把圆形区域网络模型划分成若干圆环,每一圆环中的传感器节点以混合传输的方式传输数据。其次,为使每个传感器节点能耗均衡,提出了一种混合传输概率求解算法,获得一组传输概率决定节点传输数据的方式,从而更好地平衡网络能耗。然后对圆环宽度进行了分析和优化。仿真结果证明这些算法可以有效地降低网络能耗,延长网络生命周期。     

改进的自适应物联网技术节能优化控制仿真

研究异构传感网节能优化拓扑控制优化问题.在异构传感器网络中,每个传感器节点普遍存在初始能量异构,节点在无线通信过程中通信链路异构等异构现象.为了延长网络的生存期,提出一种自适应优化异构无线传感器网络拓扑结构控制算法.算法主要难点技术问题在于对参数E的选择控制问题.该算法基于传输数据跳数和相邻传感器之间通信距离,依据相似三角形几何原理,结合具体应用场景对传感器节点的分簇、成簇等操作进行自适应优化控制.仿真实验表明,改进的算法可以高效控制给定数据采集监测区域所有节点的网络拓扑同时极大地延长了异构传感网的生命周期.     

无线传感器网络高可靠低维护地理路由协议

无线传感器网络地理路由协议要求节点根据少量本地路由信息将数据分组传输路由到目标节点。为了消除路由环,地理路由算法通常需要将网络拓扑平面化。然而现有的平面化算法要么假设节点的通信半径是一固定值,在实际应用中不适用;要么对每一条链路都进行检测是否有交叉链路,路由维护代价很高。针对以上问题,提出一种具有高可靠性和低维护成本的地理路由协议RPR(region partitioning-based routing),其基本思想是将网络划分为规则多边形区域,并在贪心路由失败时将多边形区域内的所有节点看作一个虚拟节点进行周边路由。多边形区域间通信能够降低平均路由路径长度,从而提高了路由的可靠性。基于区域划分的网络平面化策略不需要检测和删除相交链路,因此减少了路由维护开销。模拟实验结果显示,RPR协议比现有方法的平均路由路径长度更短,路由维护开销更低。     

Connectivity constrained wireless sensor deployment using multiobjective evolutionary algorithms and fuzzy decision making

Deployment of sensor nodes is an important issue in designing sensor networks. The sensor nodes communicate with each other to transmit their data to a high energy communication node which acts as an interface between data processing unit and sensor nodes. Optimization of sensor node locations is essential to provide communication for a longer duration. An energy efficient sensor deployment based on multiobjective particle swarm optimization algorithm is proposed here and compared with that of non-dominated sorting genetic algorithm. During the process of optimization, sensor nodes move to form a fully connected network. The two objectives i.e. coverage and lifetime are taken into consideration. The optimization process results in a set of network layouts. A comparative study of the performance of the two algorithms is carried out using three performance metrics. The sensitivity analysis of different parameters is also carried out which shows that the multiobjective particle swarm optimization algorithm is a better candidate for solving the multiobjective problem of deploying the sensors. A fuzzy logic based strategy is also used to select the best compromised solution on the Pareto front.     

Power efficient range-free localization algorithm for wireless sensor networks

Considering energy consumption, hardware requirements, and the need of high localization accuracy, we proposed a power efficient range-free localization algorithm for wireless sensor networks. In the proposed algorithm, anchor node communicates to unknown nodes only one time by which anchor nodes inform about their coordinates to unknown nodes. By calculating hop-size of anchor nodes at unknown nodes one complete communication between anchor node and unknown node is eliminated which drastically reduce the energy consumption of nodes. Further, unknown node refines estimated hop-size for better estimation of distance from the anchor nodes. Moreover, using average hop-size of anchor nodes, unknown node calculates distance from all anchor nodes. To reduce error propagation, involved in solving for location of unknown node, a new procedure is adopted. Further, unknown node upgrades its location by exploiting the obtained information in solving the system of equations. In mathematical analysis we prove that proposed algorithm has lesser propagation error than distance vector-hop (DV-Hop) and other considered improved DV-Hop algorithms. Simulation experiments show that our proposed algorithm has better localization performance, and is more computationally efficient than DV-Hop and other compared improved DV-Hop algorithms.     

Distributed Estimation Via Random Access

In this correspondence, the problem of distributed Bayesian estimation is considered in the context of a wireless sensor network. The Bayesian estimation performance is analyzed in terms of the expected Fisher information normalized by the transmission rate of the sensors. The sensors use a communication scheme known as the type-based random access (TBRA) scheme. Under a constraint on the expected transmission energy, an optimal spatio-temporal allocation scheme that maximizes the performance metric is characterized. It is shown that the performance metric is crucially dependent on the fading parameter known as the channel coherence index. For channels with low coherence indices, sensor transmissions tend to cancel each other, and there exists an optimal finite mean transmission rate that maximizes the performance metric. On the other hand, for channels with high coherence indices, there should be as many simultaneous transmissions as allowed by the network. The presence of a critical coherence index where the change from one behavior to another occurs is established.     

Time and power scheduling in an ad hoc network with bidirectional relaying and network coding

Network coding (NC) is a technique that allows intermediate nodes to combine the received packets from multiple links and forwarded to subsequent nodes. Compared with pure relaying, using NC in a wireless network, one can potentially improve the network throughput, but it increases the complexity of resource allocations as the quality of one transmission is often affected by the transmission conditions of multiple links. In this paper, we consider an ad hoc network, where all the links have bidirectional communications, and a relay node forwards traffic between the source and the destination nodes using NC. All transmissions share the same frequency channel, and simultaneous transmissions cause interference to each other. We consider both digital NC and analog NC strategies, referred to as DNC and ANC, respectively, and schedule transmission time and power of the nodes in order to maximize the overall network throughput. For DNC, an optimum scheduling is formulated and solved by assuming that a central controller is available to collect all the link gain information and make the scheduling decisions. Distributed scheduling schemes are proposed for networks using DNC and ANC. Our results indicate that the proposed scheduling scheme for DNC achieves higher throughput than pure relaying, and the scheduling scheme for ANC can achieve higher throughput than both DNC and pure relaying under certain conditions. Copyright © 2013 John Wiley & Sons, Ltd.     

An efficient UE cluster head selection algorithm in wireless sensor networks and cellular networks

Wireless Sensor Networks (WSNs) have been applied in many different areas. Energy efficient algorithms and protocols have become one of the most challenging issues for WSN. Many researchers focused on developing energy efficient clustering algorithms for WSN, but less research has been concerned in the mobile User Equipment (UE) acting as a Cluster Head (CH) for data transmission between cellular networks and WSNs. In this paper, we propose a cellular-assisted UE CH selection algorithm for the WSN, which considers several parameters to choose the optimal UE gateway CH. We analyze the energy cost of data transmission from a sensor node to the next node or gateway and calculate the whole system energy cost for a WSN. Simulation results show that better system performance, in terms of system energy cost and WSNs life time, can be achieved by using interactive optimization with cellular networks.