Topology Management Ensuring Reliability in Delay Sensitive Sensor Networks with Arbitrary Node Failures

The lifetime of a sensor network is influenced by the efficient utilization of the resource constrained sensor nodes. The tree-based data gathering offers good quality of service (QoS) for the running applications. However, data gathering at the sink reduces the network lifetime due to a fast failure of highly loaded nodes. Loss of connectivity and sensing coverage affect the performance of the applications that demand critical QoS. In this paper, a data gathering tree management scheme has been proposed to deal with arbitrary node failures in delay-sensitive sensor networks. A load-balanced distributed BFS tree construction procedure has been introduced for an efficient data gathering. Based on the initial tree construction, a tree maintenance scheme and an application message handler have been designed to ensure the reliable delivery of the application messages. The correctness of the proposed scheme has been verified both theoretically and with the help of simulation. The proposed scheme offers low overhead, enhanced network lifetime and good QoS in terms of delay and reliability of the application messages.     

Energy-Efficient Routing Protocol for Wireless Sensor Networks with Static Clustering and Dynamic Structure

Data gathering is an essential operation in wireless sensor networks. For periodic data gathering applications, each sensor node has data that must be sent to a distant base station in a round of communication. Due to the limited battery power of sensor nodes, each sensor node transmitting its sensed data to the base station directly significantly consumes its energy. This work presents a hierarchical ring-based data gathering (HRDG) scheme for dense wireless sensor networks. A hierarchical grid structure is constructed, and only some sensor nodes are elected as grid heads for gathering data, subsequently reducing the total energy consumption per round. Grid heads are then organized into hierarchical rings to decrease the transmission delay of a round. The proposed HRDG scheme focuses on reducing the energy × delay cost in a round of data gathering. Moreover, the energy × delay cost of HRDG is analyzed. Simulation results indicate that the proposed HRDG scheme outperforms other data gathering schemes in terms of the number of rounds, the energy × delay cost and coverage ratio.     

Distributed trajectory design for data gathering using mobile sink in wireless sensor networks

Several studies have demonstrated the benefits of using a mobile sink (MS) to reduce energy consumption resulting from multi-hop data collection using a static sink in wireless sensor networks (WSNs). However, using MS may increase data delivery latency as it needs to visit each sensor node in the network to collect data. This is a critical issue in delay-sensitive applications where all sensed data must be gathered within a given time constraint. In this paper, we propose a distributed data gathering protocol utilizing MS for WSNs. The proposed protocol designs a trajectory for the MS, which minimizes energy consumption and delay. Our protocol operates in four main phases: data sensing, rendezvous point (RP) selection, trajectory design, and data gathering. In data sensing, a number of deployed sensor nodes keep sensing the target field for a specific period of time to capture events. Then, using a cluster-based RP selection algorithm, some sensor nodes are selected to become RPs based on local information. The selected RPs are then used to determine a trajectory for the MS. To do so, we propose three trajectory design algorithms that support different types of applications, namely reduced energy path (REP), reduced delay path (RDP), and delay bound path (DBP). The MS moves through the constructed path to accomplish its data gathering according to an effective scheduling technique that is introduced in this work. We validate the proposed protocol via extensive simulations over several metrics such as energy, delay, and time complexity.     

A new load balancing and data collection algorithm for energy saving in wireless sensor networks

Data gathering is a major function of many applications in wireless sensor networks. The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirements of special applications or users. Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many to one traffic pattern. These three characteristics can lead to severe packet collision, network congestion and packet loss, and even result in hot-spots of energy consumption thus causing premature death of sensor nodes and entire network. In this paper, we propose a load balance data gathering algorithm that classifies sensor nodes into different layers according to their distance to sink node and furthermore, divides the sense zone into several clusters. Routing trees are established between sensor node and sink depending on the energy metric and communication cost. For saving energy consumption, the target of data aggregation scheme is adopted as well. Analysis and simulation results show that the algorithm we proposed provides more uniform energy consumption among sensor nodes and can prolong the lifetime of sensor networks.     

Virtual region based data gathering method with mobile sink for sensor networks

To solve the hotspot problem in wireless sensor networks, a type of virtual region based data gathering method (VRDG) with one mobile sink is proposed. Network is divided into several virtual regions consisting of three or less data gathering unit. One or more leaders are selected in each region according to their residual energy as well as the distance to all of the neighbors. Only the leaders upload data to sink in data gathering phase that effectively reduce energy consumption and end-to-end delay. Moreover, the “maximum step distance” could be calculated out by nodes to find out the best transmission path to the leader which further balance energy consumption of the whole network. Simulation results show that VRDG is energy efficient in comparing with MSE, SEP and LEACH. It also does well in prolonging network lifetime as well as in enhancing the efficiency of data collection.

     

能量有效的多级无线传感网络数据采集方法

The majority of the energy consumption by the sensors is the energy requirement for data transmission in Wireless Sensor Networks (WSNs). Therefore, introducing mobile collectors to collect data instead of multi-hop data relay is essential. However, for many proposed data gathering approaches, long data delay is the main problem. Hence, the problem of how to decrease the energy consumption and the data delay needs to be solved. In this paper, a low delay data collection mechanism using multiple mobile collectors is proposed. First, a self-organization clustering algorithm is designed. Second, sensor nodes are organized into three-level clusters. Then a collection strategy based on the hierarchical structure is proposed, which includes two rules to dispatch mobile collectors rationally. Simulation results show that the proposed mechanism is superior to other existing approaches in terms of the reduction in energy expenditure and the decrease in data delay.     

Convergecast tree management from arbitrary node failure in sensor network

The efficiency and reliability of convergecast in sensor network depends on the correct and efficient accumulation of data to the sink. A tree, rooted at the sink, that utilizes sensor resources properly is an ideal topology for data gathering. Resource constrained sensor nodes are highly prone to sudden crash. So the application demands a quick and efficient repairing of the tree when a node dies. The proposed scheme builds a data gathering tree rooted at the sink. The tree eventually becomes a Breadth First Search (BFS) tree where each node maintains the shortest hop-count to the root to reduce the routing delay. Each node collects some extra neighborhood information during the tree construction. Thus a little pre-processing at each node helps in taking prompt actions to repair the tree through local adjustment if any arbitrary single or multiple nodes fail in future. On failure of a node, each affected node in its vicinity fixes the parent through a pair of control message transmissions. Simulation results show that the repairing delay is significantly less in average and the convergecast messages are delivered with minimum data loss and no redundancy even in presence of node crash.     

WSN低功耗低时延路径式协同计算方法

针对云计算应用于无线传感器网络(Wireless Sensor Network,WSN)时延敏感型业务时存在的高传输时延问题,提出了一种WSN低功耗低时延路径式协同计算方法.该方法基于一种云雾网络架构开展研究,该架构利用汇聚节点组成雾计算层;在数据传输过程中基于雾计算层的计算能力分步骤完成任务计算,降低任务处理时延;由...     

Deterministic binary matrix based compressive data aggregation in big data WSNs

In big data wireless sensor networks, the volume of data sharply increases at an unprecedented rate and the dense deployment of sensor nodes will lead to high spatial-temporal correlation and redundancy of sensors’ readings. Compressive data aggregation may be an indispensable way to eliminate the redundancy. However, the existing compressive data aggregation requires a large number of sensor nodes to take part in each measurement, which may cause heavy load in data transmission. To solve this problem, in this paper, we propose a new compressive data aggregation scheme based on compressive sensing. We apply the deterministic binary matrix based on low density parity check codes as measurement matrix. Each row of the measurement matrix represents a projection process. Owing to the sparsity characteristics of the matrix, only the nodes whose corresponding elements in the matrix are non-zero take part in each projection. Each projection can form an aggregation tree with minimum energy consumption. After all the measurements are collected, the sink node can recover original readings precisely. Simulation results show that our algorithm can efficiently reduce the number of the transmitted packets and the energy consumption of the whole network while reconstructing the original readings accurately.     

WSN中一种基于延迟限定的数据收集算法

数据收集是无线传感器网络研究中的一个关键问题,目前基于树的数据收集方法经常会造成节点负载不均衡、树的高度无法控制等问题,从而使得数据收集延迟加大。针对该问题提出了一个新的算法——基于延迟限定的数据收集算法(DBDG),该算法从一棵最少跳数树(Fewest Hops Tree,FHT)出发,迭代地选择网络中的一条边加入树,通过限定树的高度来满足延迟限定,然后通过使树上"瓶颈节点"的度最小化来延长树的生命周期。仿真实验表明,与目前已有的协议相比,DBDG能在限定的高度内构造生命周期更长的生成树。     

Secure data aggregation without persistent cryptographic operations in wireless sensor networks

In-network data aggregation is an essential operation to reduce energy consumption in large-scale wireless sensor networks. With data aggregation, however, raw data items are invisible to the base station and thus the authenticity of the aggregated data is hard to guarantee. A compromised sensor node may forge an aggregation value and mislead the base station into trusting a false reading. Due to the stringent constraints of energy supply and computing capability on sensor nodes, it is challenging to detect a compromised sensor node and keep it from cheating, since expensive cryptographic operations are unsuitable for tiny sensor devices. This paper proposes a secure aggregation tree (SAT) to detect and prevent cheating. Our method is essentially different from other existing solutions in that it does not require any cryptographic operations when all sensor nodes work honestly. The detection of cheating is based on the topological constraints in the aggregation tree. We also propose a weighted voting scheme to determine a misbehaving node and a secure local recovery scheme to avoid using the misbehaving node.     

时延受限传感器网络移动Sink路径选择方法研究

已有研究表明sink移动方案能有效提升无线传感器网络的能耗效率,但sink点移动速度的限制通常会带来较大的数据收集时延,与某些实时性要求较高的应用产生矛盾.为解决该问题,本文以满足时延要求和最小化网络整体能耗为优化目标,提出了一种基于虚拟点优先级的移动sink路径优化选择方法.仿真试验结果表明,与基准算法相比,该方法在牺牲少量能耗的前提下能显著降低算法时间复杂度,具有良好的规模可扩展性.     

查询驱动模式下两层传感器网络Top-k查询汇聚算法研究

在两层传感器网络中,查询驱动模式是将查询请求在下层传感器网络层进行分布式处理的一种查询处理模式.在传感器节点产生数据的频率较高而用户发出查询请求的频率较低的情况下,查询驱动模式能够大大减少数据传输量,降低节点的能量消耗.在这种模式下,如何有效支持局部区域性Top-k查询是一个很有挑战性的问题.针对这一问题,本文首先构造了一种新的数据汇聚树(DAT),接着在DAT的基础上提出了一种支持区域性Top-k查询的数据汇聚方案.理论分析和仿真实验表明,与已有算法相比,本文提出的方案更加高效.     

V-BLAST-Based Virtual MIMO for Distributed Wireless Sensor Networks

A virtual multiple-input multiple-output (MIMO) communications architecture based on vertical Bell Laboratories layered space-time (V-BLAST) receiver processing is proposed for wireless sensor networks (WSNs). The proposed scheme does not require transmitter-side node cooperation unlike previously proposed virtual MIMO schemes. The energy and delay efficiencies of the proposed virtual MIMO scheme are derived for networks with both single-and multiple-antenna data gathering nodes (DGNs). Numerical results show the significant energy savings offered by the proposed method. These results also indicate that rate optimization over transmission distance is not essential as in virtual MIMO systems based on Alamouti scheme. In most scenarios, a fixed-rate virtual MIMO system with 4-quadrature amplitude modulation can achieve performance very close to that of an optimized, variable-rate system. In the case of single-antenna DGNs, the proposed scheme typically incur larger delay values compared to traditional single-input single-output communication, making it a good candidate for energy-starved but delay-tolerant WSNs.     

移动低占空比传感网中基于分段拟合压缩的数据容灾存储算法

数据存储是无线传感器网络中数据管理的基础操作.在移动低占空比传感网中,由于节点的移动性,每个节点需要频繁更新邻居节点集合,使得节点能量消耗过大;同时,节点大部分时间处于睡眠状态,仅在少部分时间内苏醒工作,造成数据备份的通信延迟过大.提出一种快速的低能耗数据保存机制.首先,源节点基于连续时间序列对感知数据进行分段线性拟合压缩;接着,节点根据预估故障概率和存储空间大小,计算出合理的压缩数据备份数量.在此基础上,设计一种动态自适应传输协议.实验仿真表明,与已有存储算法比较,该机制具有更低的传输能耗和通信延迟.     

Energy efficient dispatch strategy for the dual-functional mobile sink in wireless rechargeable sensor networks

Scavenging energy from radio-frequency (RF) signals has drawn significant attention in recent years. By introducing the technology of RF energy harvesting into wireless sensor networks, a new type of network named mobile data gathering based wireless rechargeable sensor network (MGWRSN) is considered in this paper. In the MGWRSN, a dual-functional mobile sink (MS) which has the abilities of data collecting and RF energy generating is employed. Data sensed by sensor nodes is gathered at several selected head nodes (HNs). Through using the RF energy supplied by the MS, the HNs deliver the gathered data to the MS arriving at the corresponding rendezvous points (RPs). In our works, the network energy consumption model of the MGWRSN is built, and the energy efficient dispatch strategy for the MS is studied, aiming at cutting down the total network energy consumption. For the simplest case, i.e., the one-HN MGWRSN, the optimal location of the RP is provided to minimize the total network energy consumption. After that, the researches are extended into the case of multi-HN MGWRSN and a heuristic dispatch strategy named HEEDS is proposed. Theoretical analysis and numerical results show that: (1) in the one-HN MGWRSN, the optimal location of the RP is close related to the data bulk to be transmitted, the unit mobility energy cost, the required bit error rate, the modulation scheme, and the departure position of the MS; (2) comparing with the existing algorithm WRP which directly dispatches the MS to the locations of HNs to collect data, the proposed strategy HEEDS is shown to be more energy efficient. Moreover, when a high energy transfer power is available at the MS, HEEDS renders shorter packet delay compared to WRP.     

Nature inspired discrete firefly algorithm for optimal mobile data gathering in wireless sensor networks

Nowadays wireless sensor networks enhance the life of human beings by helping them through several applications like precision agriculture, health monitoring, landslide detection, pollution control, etc. The built-in sensors on a sensor node are used to measure the various events like temperature, vibration, gas emission, etc., in the remotely deployed unmanned environment. The limited energy constraint of the sensor node causes a huge impact on the lifetime of the deployed network. The data transmitted by each sensor node cause significant energy consumption and it has to be efficiently used to improve the lifetime of the network. The energy consumption can be reduced significantly by incorporating mobility on a sink node. Thus the mobile data gathering can result in reduced energy consumption among all sensor nodes while transmitting their data. A special mobile sink node named as the mobile data transporter (MDT) is introduced in this paper to collect the information from the sensor nodes by visiting each of them and finally it sends them to the base station. The Data collection by the MDT is formulated as a discrete optimization problem which is termed as a data gathering tour problem. To reduce the distance traveled by the MDT during its tour, a nature-inspired heuristic discrete firefly algorithm is proposed in this paper to optimally collect the data from the sensor nodes. The proposed algorithm computes an optimal order to visit the sensor nodes by the MDT to collect their data with minimal travel distance. The proposed algorithm is compared with tree-based data collection approaches and ant colony optimization approach. The results demonstrate that the proposed algorithm outperform other approaches minimizing the tour length under different scenarios.     

Dual head static clustering algorithm for wireless sensor networks

Clustering of nodes is often used in wireless sensor networks to achieve data aggregation and reduce the number of nodes transmitting the data to the sink. This paper proposes a novel dual head static clustering algorithm (DHSCA) to equalise energy consumption by the sensor nodes and increase the wireless sensor network lifetime. Nodes are divided into static clusters based on their location to avoid the overhead of cluster re-formation in dynamic clustering. Two nodes in each cluster, selected on the basis of the their residual energy and their distance from the sink and other nodes in the cluster, are designated as cluster heads, one for data aggregation and the other for data transmission. This reduces energy consumption during intra-cluster and inter-cluster communication. A multi-hop technique avoiding the hot-spot problem is used to transmit the data to the sink. Experiments to observe the energy consumption patterns of the nodes and the fraction of packets successfully delivered using the DHSCA suggest improvements in energy consumption equalisation, which, in turn, enhances the lifetime of the network. The algorithm is shown to outperform all the other static clustering algorithms, while being comparable with the performance of the best dynamic algorithm.     

An energy efficient and QoS aware routing protocol for wireless sensor and actuator networks

Wireless sensor and actuator networks are composed of sensor and actuator nodes interconnected via wireless links. The actuators are responsible for taking prompt decisions and react accordingly to the data gathered by sensor nodes. In order to ensure efficient actions in such networks, we propose a new routing protocol that provides QoS in terms of delay and energy consumption. The network is organized in clusters supervised by CHs (Cluster-Heads), elected according to important metrics, namely the energy capability, the riches of connectivity, which is used to select the CH with high node density, and the accessibility degree regarding all the actuators. The latter metric is the distance in number of hops of sensor nodes relative to the actuator nodes. This metric enhances more the network reliability by reducing the communication delay when alerting the actuator nodes, and hence, reducing the energy consumption. To reach efficiently the actuator nodes, we design a delay and energy sensitive routing protocol based on-demand routing approach. Our protocol incurs less delay and is energy efficient. We perform an evaluation of our approach through simulations. The obtained results show out performance of our approach while providing effective gain in terms of communication delay and energy consumption.     

一种基于预约的无线传感器网络MAC协议

无线传感器网络要求的能量高效,低延时,使得MAC协议的设计充满挑战。近来已经提出了很多基于簇的MAC协议,为减少冲突在簇内部采用TDMA方式来协调簇内各个节点的传输。提出了一种在采用簇结构的基础上,使用预约方式来发送数据的R-MAC（Reservation-MAC）协议。当争用节点少的时候,采用随机争用方式来预约数据的发送;在争用节点多的时候,采用时隙争用方式来预约数据的发送。分析表明,R-MAC能够有效地降低能耗和减少延迟。