Constructing rings overlay for robust data collection in wireless sensor networks

This paper investigates the construction of rings overlay in wireless sensor networks and presents an enhanced relay scheme for improving the robustness of data collection through the rings overlay. Rings overlay is a class of multi-path routing structure that exploits the broadcast nature of wireless communication to cope with communication failures. In constructing the rings overlay, we propose a distributed approach to allow sensor nodes to benefit from multi-path routing as much as possible. Our proposed approach only requires sensor nodes to have local neighborhood information. In our enhanced relay scheme, sensor nodes in the ring next to the base station benefit from multi-path routing without having to transmit their data multiple times. Experimental results show that compared with a baseline greedy construction approach and the original relay scheme, the proposed techniques of overlay construction and relay enhancement significantly improve the robustness and accuracy of sensor data collection through the rings overlay.     

Design and implementation of monitoring and management system based on wireless sensor network hop estimation with the moving target Kalman prediction and Greedy-Vip

Recent advances in wireless sensor networks (WSNs) technologies and their incorporation with geographic information system (GIS) technologies offer vast opportunities for development and application of environment monitoring data communication. This paper analyzes the method of predicting the location of moving target with the Kalman filter and Greedy-ViP approach to establish WSN flat network routing and the data management system. Simulation results demonstrate that the predicted information collection node locations by the proposed method are consistent with the majority of real ones, the hops tend to straight lines, the hops count is the least, lower repetition rate of the nodes on different hops, and the environment monitoring data can be saved and queried.     

Loss-aware routing algorithm for photonic networks on chip

Photonic network on chip was introduced as an efficient communication platform to overcome the existing challenges in traditional networks on chip. Optical networks provide high bandwidth and low power dissipation infrastructure. Insertion loss is one of the important parameters in photonic networks on chip. In this study, we propose a solution in routing algorithm level in order to reduce insertion loss in photonic network on chip, by passing packets through paths with lower number of optical elements. Simulation results reveal that a novel approach in the routing level decreases insertion loss as much as possible, energy consumption and optical power budget. Our proposed routing has 29.05% less insertion loss under all2all traffic pattern for blocking torus topology, and it has about 12.37% less insertion loss for TorusNX topology in comparison with primary dimension-ordered routing. Proposed routing algorithm increases both the network bandwidth and scalability.     

Geographical Cluster-Based Routing in Sensing-Covered Networks

The relationship between coverage and connectivity in sensor networks has been investigated in recent research treating both network parameters in a unified framework. It is known that networks covering a convex area are connected if the communication range of each node is at least twice a unique sensing range used by each node. Furthermore, geographic greedy routing is a viable and effective approach providing guaranteed delivery for this special network class. In this work, we will show that the result about network connectivity does not suffer from generalizing the concept of sensing coverage to arbitrary network deployment regions. However, dropping the assumption that the monitored area is convex requires the application of greedy recovery strategies like traversing a locally extracted planar subgraph. This work investigates a recently proposed planar graph routing variant and introduces a slight but effective simplification. Both methods perform message forwarding along the edges of a virtual overlay graph instead of using wireless links for planar graph construction directly. In general, there exist connected network configurations where both routing variants may fail. However, we will prove three theoretical bounds which are a sufficient condition for guaranteed delivery of these routing strategies applied in specific classes of sensing covered networks. By simulation results, we show that geographical cluster-based routing outperforms existing related geographical routing variants based on one-hop neighbor information. Furthermore, simulations performed show that geographical cluster-based routing achieves a comparable performance compared to variants based on two-hop neighbor information, while maintaining the routing topology consumes a significantly reduced amount of communication resources.     

A novel Bluetooth low energy based system for spatial exploration in smart cities

Smart Cities are employing information and communication technologies in the quest for sustainable economic development and the fostering of new forms of collective life. They facilitate connections between citizens and organizations that are of paramount importance for their long-term sustainability. As cities become more complex and their communities more dispersed, questions such as ‘where can I find …’ are increasingly pertinent. In this paper, we introduce NomaBlue, a new vision of spatial recognition in smart cities, the proposed system is based on an intelligent nomadic data collection and users' collaboration using smart Bluetooth technology. We demonstrate using two case-studies that our approach is capable of proposing an efficient spatial recognition service while supporting a range of users’ constraints, our system is disconnected from the internet, it can operate in any indoor/outdoor area, it doesn't require pre-defined geographic databases and uses a new concept of nomadic data collection and sharing to speed-up the circulating information in smart cities.     

基于WSNs的大型楼宇空气质量监测系统设计

针对大型楼宇环境信息监控特点,基于低功耗Zig Bee无线通信技术设计一种空气质量监控系统。运用无线传感器智能信息处理技术,全面提升系统的自动化与监测水平。采用星型拓扑结构组网,通过在监测区域部署网络节点,将监测数据汇集到嵌入式监测系统,实现统一的数据管理和Zig Bee网络的路由监测功能。由无线传感器网络实时采集CO,甲醛,SO2和苯等环境数据,并进行处理,将其发送到接收端,在接收端对数据进行存储和显示,实时监测楼宇环境空气质量。实验证明:该系统性能稳定,数据传输可靠性高,使用灵活,可广泛应用于各领域的环境参数自动监测。     

Opportunistic sampling-based query processing in wireless sensor networks

High resolution sampling of physical phenomenon is a prime application of large scale wireless sensor networks (WSNs). With hundreds of nodes deployed over vast tracts of land, monitoring data can now be generated at unprecedented spatio-temporal scales. However, the limited battery life of individual nodes in the network mandates smart ways of collecting this data by maximizing localized processing of information at the node level. In this paper, we propose a WSN query processing method that enhances localized information processing by harnessing the two inherent aspects of WSN communication, i.e., multihop and multipath data transmission. In an active WSN where data collection queries are regularly processed, multihop and multipath routing leads to a situation where a significant proportion of nodes relay and overhear data generated by other nodes in the network. We propose that nodes opportunistically sample this data as they communicate. We model the data communication process in a WSN and show that opportunistic sampling during data communication leads to surprisingly accurate global knowledge at each node. We present an opportunistic query processing system that uses the accumulated global knowledge to limit the data collection requirements for future queries while ensuring temporal freshness of the results.     

基于北斗通信的RTU远程监控系统

以某导弹发射装备信息采集记录装置改进项目为背景,本文针对远程控制中心对装备状态信息监控和评估的实际需求,设计了一种基于北斗卫星通信RTU(Remote Terminal Unit)远程监控系统。该系统可以实时采集到装备的状态信息并对采集的数据进行高速处理,通过北斗通信终端定时向控制中心发送采集状态数据,同时控制中心也可以发送指令随时调取状态数据。经测试结果表明,该系统具有良好的稳定性、实时性、可靠性和低能耗的特点,可实现远程监控和数据采集以满足装备的远程管理需要。     

Efficient solution techniques for the integrated coverage, sink location and routing problem in wireless sensor networks

Sensors are tiny electronic devices having limited battery energy and capability for sensing, data processing and communicating. They can collectively behave to provide an effective wireless network that monitors a region and transmits the collected information to gateway nodes called sinks. Most of the applications require the operation of the network for long periods of times, which makes the efficient management of the available energy resources an important concern. There are three major issues in the design of sensor networks: sensor deployment or the coverage of the sensing area, sink location, and data routing. In this work, we consider these three design problems within a unified framework and develop two mixed-integer linear programming formulations. They are difficult to solve exactly. However, it is possible to compute good feasible solutions of the sink location and routing problems easily, when the sensors are deployed and their locations in the sensor field become known. Therefore, we propose a tabu search heuristic that tries to identify the best sensor locations satisfying the coverage requirements. The objective value corresponding to each set of sensor locations is calculated by solving the sink location and routing problem. Computational tests carried out on randomly generated test instances indicate that the proposed hybrid approach is both accurate and efficient.     

无线传感器网络中改进的HeeD路由协议

在无线传感器网络的路由技术中,基于簇的路由算法在拓扑管理、能耗利用、数据融合等方面都有较强的优势。在分析HeeD协议的基础上,提出了HeeD算法存在的问题,并相应地修改了成簇算法,增强了算法的健壮性。同时通过反应式的广播各节点的通信代价,而不是周期性的在每轮初始化阶段广播,大大降低了节点间广播通信代价的次数,节省了网络的整体能耗。仿真结果也证明了改进后的A-HeeD协议相对于HeeD提高了网络的生命周期。     

Dynamic sensor activation and decision-level fusion in wireless acoustic sensor networks for classification of domestic activities

For the past decades there has been a rising interest for wireless sensor networks to obtain information about an environment. One interesting modality is that of audio, as it is highly informative for numerous applications including speech recognition, urban scene classification, city monitoring, machine listening and classifying domestic activities. However, as they operate at prohibitively high energy consumption, commercialisation of battery-powered wireless acoustic sensor networks has been limited. To increase the network’s lifetime, this paper explores the joint use of decision-level fusion and dynamic sensor activation. Hereby adopting a topology where processing – including feature extraction and classification – is performed on a dynamic set of sensor nodes that communicate classification outputs which are fused centrally. The main contribution of this paper is the comparison of decision-level fusion with different dynamic sensor activation strategies on the use case of automatically classifying domestic activities. Results indicate that using vector quantisation to encode the classification output, computed at each sensor node, can reduce the communication per classification output to 8 bit without loss of significant performance. As the cost for communication is reduced, local processing tends to dominate the overall energy budget. It is indicated that dynamic sensor activation, using a centralised approach, can reduce the average time a sensor node is active up to 20% by leveraging redundant information in the network. In terms of energy consumption, this resulted in an energy reduction of up to 80% as the cost for computation dominates the overall energy budget.     

Multi-hop communications on wireless network-on-chip using optimized phased-array antennas

Network-on-Chip (NoC) as a promising design approach for on-chip interconnect fabrics could overcome the energy as well as synchronization challenges of the conventional interconnects in the gigascale System-on-Chips (SoC). The advantages of communication performance of traditional wired NoC will no longer be continued by the future technology scaling. Packets that travel between distant nodes of a large scale wired on-chip network significantly suffer from energy dissipation and latency due to the routing overhead at each hop. According to the International Technology Roadmap for Semiconductors annual report, the RFCMOS characteristics will be steadily improved by technology scaling. As the operating frequency of RF devices increases, the size of Si integrated antenna will decrease and it is feasible to employ them as a revolutionary interconnect for intra-chip wireless communications. In this paper, we focus on physical requirements and design challenges of wireless NoC. It is demonstrated that employing an optimum-radiation phased array antenna and multihop communications will increase the reliability of on-chip wireless links by several orders of magnitude using a limited power budget less than 0.1 pJ/bit.     

Sensor-centric energy-constrained reliable query routing for wireless sensor networks

Standard wireless sensor network models emphasize energy efficiency and distributed decision-making by considering untethered and unattended sensors. To this we add two constraints—the possibility of sensor failure and the fact that each sensor must tradeoff its own resource consumption with overall network objectives. In this paper, we develop an analytical model of energy-constrained, reliable, data-centric information routing in sensor networks under all the above constraints. Unlike existing techniques, we use game theory to model intelligent sensors thereby making our approach sensor-centric. Sensors behave as rational players in an N-player routing game, where they tradeoff individual communication and other costs with network wide benefits. The outcome of the sensor behavior is a sequence of communication link establishments, resulting in routing paths from reporting to querying sensors. We show that the optimal routing architecture is the Nash equilibrium of the N-player routing game and that computing the optimal paths (which maximizes payoffs of the individual sensors) is NP-Hard with and without data-aggregation. We develop a game-theoretic metric called path weakness to measure the qualitative performance of different routing mechanisms. This sensor-centric concept which is based on the contribution of individual sensors to the overall routing objective is used to define the quality of routing (QoR) paths. Analytical results on computing paths of bounded weakness are derived and game-theoretic heuristics for finding approximately optimal paths are presented. Simulation results are used to compare the QoR of different routing paths derived using various energy-constrained routing algorithms.     

Proportional Fairness Based Energy Efficient Routing in Wireless Sensor Network

Wireless Sensor Network (WSN) is an independent device that comprises a discrete collection of Sensor Nodes (SN) to sense environmental positions, device monitoring, and collection of information. Due to limited energy resources available at SN, the primary issue is to present an energy-efficient framework and conserve the energy while constructing a route path along with each sensor node. However, many energy-efficient techniques focused drastically on energy harvesting and reduced energy consumption but failed to support energy-efficient routing with minimal energy consumption in WSN. This paper presents an energy-efficient routing system called Energy-aware Proportional Fairness Multi-user Routing (EPFMR) framework in WSN. EPFMR is deployed in the WSN environment using the instance time. The request time sent for the route discovery is the foremost step designed in the EPFMR framework to reduce the energy consumption rate. The proportional fairness routing in WSN selects the best route path for the packet flow based on the relationship between the periods of requests between different SN. Route path discovered for packet flow also measure energy on multi-user route path using the Greedy Instance Fair Method (GIFM). The GIFM in EPFMR develops node dependent energy-efficient localized route path, improving the throughput. The energy-aware framework maximizes the throughput rate and performs experimental evaluation on factors such as energy consumption rate during routing, Throughput, RST, node density and average energy per packet in WSN. The Route Searching Time (RST) is reduced using the Boltzmann Distribution (BD), and as a result, the energy is minimized on multi-user WSN. Finally, GIFM applies an instance time difference-based route searching on WSN to attain an optimal energy minimization system. Experimental analysis shows that the EPFMR framework can reduce the RST by 23.47% and improve the throughput by 6.79% compared with the state-of-the-art works.     

Bi-LCQ: A low-weight clustering-based Q-learning approach for NoCs

Network congestion has a negative impact on the performance of on-chip networks due to the increased packet latency. Many congestion-aware routing algorithms have been developed to alleviate traffic congestion over the network. In this paper, we propose a congestion-aware routing algorithm based on the Q-learning approach for avoiding congested areas in the network. By using the learning method, local and global congestion information of the network is provided for each switch. This information can be dynamically updated, when a switch receives a packet. However, Q-learning approach suffers from high area overhead in NoCs due to the need for a large routing table in each switch. In order to reduce the area overhead, we also present a clustering approach that decreases the number of routing tables by the factor of 4. Results show that the proposed approach achieves a significant performance improvement over the traditional Q-learning, C-routing, DBAR and Dynamic XY algorithms.     

一种新的基于粒子群优化的双簇头分簇路由算法*

针对无线传感器网络分簇路由算法中簇头节点负载过重,簇头能量利用率不高,提出了一种基于粒子群优化的双簇头多跳路由算法。该算法根据簇头任务的不同,利用节点的能量、距离汇聚节点的距离以及节点的位置关系分别构建适应值函数,选择出最优主簇头完成数据采集和融合任务,以及与其协作的最优副簇头完成簇间数据转发任务,最终实现采集能耗和传输能耗最小化。仿真实验结果表明,与其他路由算法相比,该算法可以有效减轻簇头节点负载,减小簇头能量消耗,均衡整个网络能耗,延长了网络的生存周期。     

基于互联网+的高校能源管理信息系统设计与开发

为了实现高校能源管理的信息共享,提高对高校能源信息管理的智能水平,提出一种基于互联网+的高校能源管理信息系统开发设计方案。系统采用感知层、网络层和应用层的三层结构,采用RFID、 条形码、蓝牙、红外等数据信息感知技术进行高校能源信息的原始采集,在网络层通过ZigBee 和无线通信技术进行信息融合传输,在控制设备中导入原始数据,在互联网+环境下建立数据处理中心,根据能源管理系统的现实需求进行信息融合和数据存储管理,设计嵌入式控制器对串口、并口、USB端口、以太网口及GPIB接口进行集成控制,在Linux内核下实现高校能源管理信息系统应用程序开发。系统测试结果表明,采用该系统进行高校能源管理,具有较好的信息存储、信息调度和信息检索能力。     

一种基于节点位置和密度的非均匀分簇路由算法

分析了现有分簇路由算法,提出了基于节点位置和密度的非均匀分簇路由算法。簇头选举阶段,考虑了节点的剩余能量,并引入竞争机制进行簇头选择;成簇阶段,综合考虑节点与基站的距离、节点密度以进行非均匀分簇,达到节点能耗均衡的效果,同时解决路由热区问题;簇间路由阶段,通过设立通信簇头节点,使簇间数据转发任务从簇头中分离,簇头节点只负责簇内的数据收集和融合,而通信簇头节点负责簇间数据传输,减少了簇头的能量消耗。实验结果表明,改进后的路由算法能够有效地均衡网络负载,并显著地延长网络的生命周期。     

Promoting Heterogeneity, Mobility, and Energy-Aware Voronoi Diagram in Wireless Sensor Networks

We prove that the energy sink-hole problem can be solved provided that sensors adjust their communication ranges so they can send data over distances less than the radii of their nominal communication range. This solution, however, imposes a severe restriction on the size of a monitored field. To overcome this limitation, we propose a sensor deployment strategy based on energy heterogeneity with a goal that all sensors deplete their energy simultaneously. Our simulation results show that such a sensor deployment strategy helps all sensors deplete their initial energy at the same time. To solve the energy sink-hole problem for homogeneous WSNs, however, where all sensors have the same initial energy, we propose a localized energy-aware Voronoi diagram-based data forwarding (EVEN) protocol. EVEN combines sink mobility with a new concept, called energy-aware Voronoi diagram whose virtual sites (i.e., virtual sensors' locations) are computed based on the remaining energy of the corresponding sensors. Through simulations, we show that EVEN outperforms similar greedy geographical data forwarding protocols and has performance that is comparable to that of an existing data collection protocol that uses a joint mobility and routing strategy. Precisely, we find that EVEN yields an improvement of more than in terms of network lifetime.     

Using central nodes for efficient data collection in wireless sensor networks

We study the problem of data collection in Wireless Sensor Networks (WSN). A typical WSN is composed of wireless sensor nodes that periodically sense data and forward it to the base station in a multi-hop fashion. We are interested in designing an efficient data collection tree routing, focusing on three optimization objectives: energy efficiency, transport capacity, and hop-diameter (delay).In this paper we develop single- and multi-hop data collection, which are based on the definition of node centrality: centroid nodes. We provide theoretical performance analysis for our approach, present its distributed implementation and discuss the different aspects of using it. Most of our results are for two-dimensional WSNs, however we also show that the centroid-based approach is asymptotically optimal in three-dimensional random node deployments. In addition, we present new construction for arbitrary network deployment based on central nodes selection. We also present extensive simulation results that support our theoretical findings.