基于网络编码的异构无线传感器网络数据广播协议

本文提出一种适应异构无线传感器网络的能量感知的网络编码数据广播协议(ENCBP)。传感器节点根据邻居能量信息列表实时地计算节点剩余能量的线性映射值。在此基础上,采用能量感知的网络编码转发概率机制,使具有较高剩余能量的节点比低能量节点拥有更高的数据转发优先级,以实现能量均衡的数据传输。另外,采用伪广播机制对协议进行优化,以提高数据包投递率。仿真结果表明,ENCBP不仅可以有效实现网络的能耗均衡,以延长网络的生命周期,还能在一定程度上降低数据包传输时延,从而提高数据通信性能。     

On the energy-delay trade-off in geographic forwarding in always-on wireless sensor networks: A multi-objective optimization problem

The design and development of multi-hop wireless sensor networks are guided by the specific requirements of their corresponding sensing applications. These requirements can be associated with certain well-defined qualitative and/or quantitative performance metrics, which are application-dependent. The main function of this type of network is to monitor a field of interest using the sensing capability of the sensors, collect the corresponding sensed data, and forward it to a data gathering point, also known as sink. Thus, the longevity of wireless sensor networks requires that the load of data forwarding be balanced among all the sensor nodes so they deplete their battery power (or energy) slowly and uniformly. However, some sensing applications are time-critical in nature. Hence, they should satisfy strict delay constraints so the sink can receive the sensed data originated from the sensors within a specified time bound. Thus, to account for all of these various sensing applications, appropriate data forwarding protocols should be designed to achieve some or all of the following three major goals, namely minimum energy consumption, uniform battery power depletion, and minimum delay. To this end, it is necessary to jointly consider these three goals by formulating a multi-objective optimization problem and solving it. In this paper, we propose a data forwarding protocol that trades off these three goals via slicing the communication range of the sensors into concentric circular bands. In particular, we discuss an approach, called weighted scale-uniform-unit sum, which is used by the source sensors to solve this multi-objective optimization problem. Our proposed data forwarding protocol, called Trade-off Energy with Delay (TED), makes use of our solution to this multi-objective optimization problem in order to find a “best” trade-off of minimum energy consumption, uniform battery power depletion, and minimum delay. Then, we present and discuss several numerical results to show the effectiveness of TED. Moreover, we show how to relax several widely used assumptions in order to enhance the practicality of our TED protocol, and extend it to real-world network scenarios. Finally, we evaluate the performance of TED through extensive simulations. We find that TED is near optimal with respect to the energy × delay metric. This simulation study is an essential step to gain more insight into TED before implementing it using a sensor test-bed.     

Energy-aware robust model predictive control based on noisy wireless sensors

Wireless sensor networks (WSNs) are becoming fundamental components of modern control systems due to their flexibility, ease of deployment and low cost. However, the energy-constrained nature of WSNs poses new issues in control design; in particular the discharge of batteries of sensor nodes, which is mainly due to radio communications, must be taken into account. In this paper we present a novel transmission strategy for communication between controller and sensors which is intended to minimize the data exchange over the wireless channel. Moreover, we propose an energy-aware control technique for constrained linear systems based on explicit model predictive control (MPC), providing closed-loop stability in the presence of disturbances. The presented control schemes are compared to traditional MPC techniques. The results show the effectiveness of the proposed energy-aware approach, which achieves a profitable trade-off between energy savings and closed-loop performance.     

An efficient strategy of nonuniform sensor deployment in cyber physical systems

In this paper, we study the sensor deployment pattern problem in cyber physical systems. When designing the sensor deployment pattern, the network lifetime maximization while covering the given area/targets and forwarding sensor data to a sink node is an important issue. In order to prolong the network lifetime by balancing energy depletion across all sensors, we propose a novel nonuniform sensor distribution strategy. Since sensors located closer to the sink are more involved in data forwarding, sensor densities in different areas should be varied according to the distance to the sink. Based on the nonuniform sensor distribution, we propose sensor deployment patterns to satisfy the coverage and connectivity requirements and prolong the network lifetime. A numerical computation is performed to validate and compare the effectiveness of the proposed deployment patterns.     

无线传感器网络中负载均衡的sink节点移动策略

在无线传感器网络中,部分传感器节点由于担任过多数据中转任务,需要消耗较多的能量.使其过早死亡.缩短了网络的寿命.本文提出基于sink节点移动的策略.将感知区域分割成有限个虚拟单元格,并以每个虚拟单元格的中心作为sink节点的备选移动位置.然后,通过解线性规划问题确定sink节点的移动位置和停留时间.通过此方法.在一定程度上均衡了传感器节点的负载.延长了网络寿命.     

传感网中时延受限的移动式数据收集方法综述

数据收集是无线传感器网络中研究的热点问题之一,然而在传统的无线传感器网络中,基站附近的节点由于承担了大量数据转发任务而导致自身能量过早耗尽,缩短了网络的生命期.不少研究通过引入能量较为充足的移动性节点来收集数据,以节省普通传感器节点的能量,但是却导致了数据收集时延过大,如何在保证数据收集时延的前提下最大化网络生命期已成为近几年研究的热点问题.对目前主要的时延受限的移动式数据收集方法进行了充分调研,通过对这些方法的详细分类和比较,归纳了时延受限的移动式数据收集的各类方法的特点,分析了这些方法的优缺点和适用范围,总结了存在的主要问题,并指出了未来的研究方向.     

VIBE: An energy efficient routing protocol for dense and mobile sensor networks

We present a new protocol that manages wireless sensor networks in several scenarios including large scale, high density and high mobility deployments. An example of one of the main applications is to communicate important information from inaccessible areas by spreading “enough” mobile sensors which must self-configure and assemble. According to our protocol, virtual infrastructure-based energy-efficient (VIBE) routing, the information is routed in a multihop, cluster level fashion by enabling each sensor to make individual decisions regarding its mode of operation. The aim is to prolong the network's lifetime by minimising the average energy spent for each communication. VIBE is capable of addressing mobility requirements as it is completely independent of any kind of topological knowledge and control messages. We show by extended experiments that VIBE performs very well in terms of consumed energy by comparing it to standard directed flooding and greedy forwarding protocols. We also compare it to LEACH (Rabiner Heinzelman et al., 2000) and a more recent protocol, namely MECH (Chang and Kuo, 2006). VIBE proves to save large amounts of energy when compared to the first three and up to 15% compared to MECH.     

Fault-tolerant and efficient data propagation in wireless sensor networks using local,additional network information

We propose a new data dissemination protocol for wireless sensor networks, that basically pulls some additional knowledge about the network in order to subsequently improve data forwarding towards the sink. This extra information is still local, limited and obtained in a distributed manner. This extra knowledge is acquired by only a small fraction of sensors thus the extra energy cost only marginally affects the overall protocol efficiency. The new protocol has low latency and manages to propagate data successfully even in the case of low densities. Furthermore, we study in detail the effect of failures and show that our protocol is very robust. In particular, we implement and evaluate the protocol using large scale simulation, showing that it significantly outperforms well known relevant solutions in the state of the art.     

Distributed load balancing mechanism for detouring schemes of geographic routing in wireless sensor networks

Well-known ‘routing hole’ problem of geographic routing is hardly avoided in wireless sensor networks because of various actual geographical environments. Existing geographic routing protocols use perimeter routing strategies to find a detour path around the boundary of holes when they encounter the local minimum during greedy forwarding. However, this solution may lead to uneven energy consumption around the holes since it consumes more energy of the boundary sensors. It becomes more serious when holes appear in most of routing paths in a large-scale sensor network. In this paper, we propose a novel distributed strategy to balance the traffic load on the boundary of holes by virtually changing the sizes of these holes. The proposed mechanism dynamically controls holes to expand and shrink circularly without changing the underlying forwarding strategy. Therefore, it can be applied to most of the existing geographic routing protocols which detour around holes. Simulation results show that our strategy can effectively balance the load around holes, thus prolonging the network life of sensor networks when an existing geographic routing protocol is used as the underlying routing protocol.     

Termite-hill: Performance optimized swarm intelligence based routing algorithm for wireless sensor networks

A wireless sensor network (WSN) is a large collection of sensor nodes with limited power supply, constrained memory capacity, processing capability, and available bandwidth. The main problem in event gathering in wireless sensor networks is the formation of energy-holes or hot spots near the sink. Due to the restricted communication range and high network density, events forwarding in sensor networks is very challenging, and require multi-hop data forwarding. Improving network lifetime and network reliability are the main factors to consider in the research associated with WSN. In static wireless sensor networks, sensors nodes close to the sink node run out of energy much faster than nodes in other parts of the monitored area. The nodes near the sink are more likely to use up their energy because they have to forward all the traffic generated by the nodes farther away to the sink. The uneven energy consumption results in network partitioning and limit the network lifetime. To this end, we propose an on-demand and multipath routing algorithm that utilizes the behavior of real termites on hill building termed Termite-hill which support sink mobility. The main objective of our proposed algorithm is to efficiently relay all the traffic destined for the sink, and also balance the network energy. The performance of our proposed algorithm was tested on static, dynamic and mobile sink scenarios with varying speed, and compared with other state-of-the-art routing algorithms in WSN. The results of our extensive experiments on Routing Modeling Application Simulation Environment (RMASE) demonstrated that our proposed routing algorithm was able to balance the network traffic load, and prolong the network lifetime.     

异构无线传感器网络基于区分服务的网络编码协议

通过将来自多条链路的数据包融合为一个单独的编码信息流进行传输,网络编码技术能够显著地提高无线 多}a}网络的容量。提出一种基于区分服务的异构无线传感器网络编码协议(DI3NO。协议的核心思想是周期性地计 算节点剩余能量的均值和标准差,对节点进行动态分类。在此基础上,将服务质量需求映射到网络编码协议中。为 此,引入能量感知编码包转发机制,以高效地利用节点的能量;另一方面,设计多优先级数据包调度策略,目的是创造 更多的编码机会。仿真结果表明,DI3NC不仅可以保障数据的可靠传输,而且可有效地减少低能量节点的能耗,从而 延长网络的生命周期。     

Mobility-assisted minimum connected cover in a wireless sensor network

All properties of mobile wireless sensor networks (MWSNs) are inherited from static wireless sensor networks (WSNs) and meanwhile have their own uniqueness and node mobility. Sensor nodes in these networks monitor different regions of an area of interest and collectively present a global overview of monitored activities. Since failure of a sensor node leads to loss of connectivity, it may cause a partitioning of the network. Adding mobility to WSNs can significantly increase the capability of the WSN by making it resilient to failures, reactive to events, and able to support disparate missions with a common set of sensor nodes. In this paper, we propose a new algorithm based on the divide-and-conquer approach, in which the whole region is divided into sub-regions and in each sub-region the minimum connected sensor cover set is selected through energy-aware selection method. Also, we propose a new technique for mobility assisted minimum connected sensor cover considering the network energy. We provide performance metrics to analyze the performance of our approach and the simulation results clearly indicate the benefits of our new approach in terms of energy consumption, communication complexity, and number of active nodes over existing algorithms.     

Improved sensor network lifetime with multiple mobile sinks

A critical issue for data gathering in wireless sensor networks is the formation of energy holes near the sinks. Sensors near the sinks have to participate in relaying data on behalf of other sensors and thus will deplete their energy very quickly, resulting in network partitioning and limitation of the network lifetime. The solution that we propose in this paper is to use mobile sinks that change their location when the nearby sensors’ energy becomes low. In this way the sensors located near sinks change over time. In deciding a new location, a sink searches for zones with richer sensor energy.First, we study the improvement in network lifetime when sinks move on a predetermined path, along the perimeter of a hexagonal tiling. Two cases are considered for data gathering when sinks stop in the hexagon’s corners and when the sinks stop on multiple locations on the hexagon perimeter. This study shows an improvement of up to 4.86 times in network lifetime. Second, we design a distributed and localized algorithm used by the sinks to decide their next movement location such that the virtual backbone formed by the sinks remains interconnected at all times. Two extensions of the distributed algorithm, coverage requirement and limitation of the time-delivery requirement, are also addressed. Simulation results are presented to verify our approaches.     

Forwarding via checkpoints: Geographic routing on always-on sensors

Data forwarding is an essential function in wireless sensor networks (WSNs). It is well-known that geographic forwarding is an efficient scheme for WSNs as it requires maintaining only local topology information to forward data to a central gathering point, called the sink (or base station), for further analysis and processing. In this paper, we propose an energy-efficient data forwarding protocol for WSNs, called Weighted Localized Delaunay Triangulation-based data forwarding (WLDT), with a goal to extending the network lifetime. Specifically, WLDT selects as forwarders the sensors with high remaining energy and whose locations lie nearer the shortest path between source sensors and a single sink, thus helping the sensors minimize their average energy consumption. More precisely, WLDT defines checkpoints to build energy-efficient data forwarding paths and uses a 1-lookahead scheme to guarantee data delivery to the sink. We show that WLDT, which favors data forwarding through short Delaunay edges, achieves an energy gain percentage in the order of 55% for the free space model and close to 100% for the multi-path model compared to BVGF and GPSR, which forward data through long distances and which we have slightly updated to account for energy in the selection of next forwarders. We prove that these checkpoints yield an energy gain percentage in the order of 30% in comparison with a similar protocol, called WLDT-w/c (or WLDT without checkpoints), which forwards data via short distances but does not use checkpoints.     

基于能量感知的双簇头数据收集协议

针对无线传感器网络的簇结构中簇头节点消耗能量过快而容易成为死亡节点的问题,提出了一种能量感知的双簇头数据收集协议EADC,通过在簇内增加一个副簇头来负责主簇头节点的数据转发功能,分担了主簇头的能量消耗,使主簇头成为死亡节点的概率降低,从而有效延长了网络寿命。实验分析结果表明,与EADEEG算法相比,EADC能够将死亡节点出现的时间有效延长30轮,使网络使用寿命明显延长。     

Autoregressive energy-efficient context forwarding in wireless sensor networks for pervasive healthcare systems

Driven by technological advances in low-power network systems and medical sensors, we have witnessed during the recent years the adoption of wireless sensor networks (WSNs) in electronic healthcare. Improving the quality of electronic healthcare and the prospects of ‘ageing in place’ through WSNs requires solving difficult problems in scale, energy management, and data acquisition. Medical and pervasive healthcare application (or mobile healthcare application) based on WSNs is influenced by many factors such as transmission errors and power consumption. We propose a multivariate context forwarding model that achieves energy-efficient WSN operation. A node adopts multivariate autoregression for forecasting contextual information (bio-signals or vital parameters) and locally decides whether context retransmission is required or not. This scheme is applied in patient telemonitoring systems where accurate yet energy-aware transmission of bio-signals to a remote control unit is crucial. Simulation results are reported indicating the capability of the proposed model in minimizing energy consumption in WSNs having as application domain the electronic healthcare systems.     

DLRDG: distributed linear regression-based hierarchical data gathering framework in wireless sensor network

For many applications in wireless sensor network (WSN), the gathering of the holistic sensor measurements is difficult due to stringent constraint on network resources, frequent link, indeterminate variations in sensor readings, and node failures. As such, sensory data extraction and prediction technique emerge to exploit the spatio-temporal correlation of measurements and represent samples of the true state of the monitoring area at a minimal communication cost. In this paper, we present DLRDG strategy, a distributed linear regression-based data gathering framework in clustered WSNs. The framework can realize the approximate representation of original sensory data by less than a prespecified threshold while significantly reducing the communication energy requirements. Cluster-head (CH) nodes in WSN maintain linear regression model and use historical sensory data to perform estimation of the actual monitoring measurements. Rather than transmitting original measurements to sink node, CH nodes communicate constraints on the model parameters. Relying on the linear regression model, we improved the CH node function of representative EADEEG (an energy-aware data gathering protocol for WSNs) protocol for estimating the energy consumption of the proposed strategy, under specific settings. The theoretical analysis and experimental results show that the proposed framework can implement sensory data prediction and extracting with tolerable error bound. Furthermore, the designed framework can achieve more energy savings than other schemes and maintain the satisfactory fault identification rate on case of occurrence of the mutation sensor readings.     

基于维诺图和二分图的水面移动基站路径规划方法

水面传感器网络（Surface sensor networks,SSNs）具有节点稀疏布置的特点（节点间距离通常大于节点通信半径）,因此难以通过节点间的多跳路由汇聚数据,目前主要采用移动基站（Mobile sink,MS）收集网络中的数据,其中移动基站的路径规划是一个关键问题.该文提出一种基于维诺图和二分图的水面移动基站路径规划方法,首先利用维诺图理论生成数据收集“候选点”;然后以二分图描述候选点对网络中传感器节点的支配关系,并基于支配集理论求解出“最小有效支配集”,即可以收集网络中所有节点数据的最小的候选点集合;最后针对最小有效支配集形成最优路径.大量实验结果表明该方法可以有效地规划出水面传感器网络中移动基站的路径,不仅可以完成全网数据收集任务,而且具有路径长度短、能量效率高和节点能耗均衡的优点.     

C3: an energy-efficient protocol for coverage,connectivity and communication in WSNs

The lower layer of ubiquitous and pervasive systems consists of wireless ad hoc and sensor networks. In wireless sensor networks (WSNs), sensors consume most of their energy in data transmission and idle listening. Hence, efficient usage of energy can be ensured by improved protocols for topology control (i.e., coverage and connectivity), sleep scheduling, communication, and aggregation and compression of data. Though several protocols have been proposed for this purpose, they are not energy-efficient. We propose an integrated and energy-efficient protocol for Coverage, Connectivity, and Communication (C3) in WSNs. The C3 protocol uses received signal strength indicator to divide the network into virtual rings, defines clusters with clusterheads more probably at alternating rings, defines dings that are rings inside a cluster and uses triangular tessellation to identify redundant nodes, and communicates data to sink through clusterheads and gateways. The proposed protocol strives for near-optimal deployment, load balancing, and energy-efficient communication. Simulation results show that the C3 protocol ensures partial coverage of more than 90 % of the total deployment area, ensures one connected network, and facilitates energy-efficient communication while expending only one-fourth of the energy compared to other related protocols such as the coverage and connectivity protocol, and the layered diffusion-based coverage control.     

无线传感器网络中能耗均衡的覆盖控制算法

覆盖控制作为无线传感器网络的一个基本问题,对网络的生存时间、部署策略、通信协议和组网等问题的解决具有重要影响。在传感器节点随机冗余部署方式下,传统的方式 是在保证覆盖要求和通信连通的前提下仅将最少量的节点投入活跃工作状态,从而降低网络能耗。但是,若频繁地激活同一批节点,会造成这些节点由于能耗过快而较早失效效,使整个网络的冗余程度降低。然而,冗余度是传感器网络在单个节点性能有限的情况下提高整个网络的可靠性、容错性、精确性等的基础。为此,本文提出了一个能耗均衡ECB的覆盖问题,指出它是NP完全的,并给出了一个集中式近似算法。该算法根据节点的剩余能量赋于每个节点非负权,再基于Voronoi划分和贪心边方法,在保证覆盖要求的同时选择权和最小的节点激活。仿真实验结果表明,ECB算法求得的活跃节点集小,可以达到有效覆盖,并且可以保持网络的冗余度。