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.     

Energy equalizing routing for fast data gathering in wireless sensor networks

Energy saving and fast responding of data gathering are two crucial factors for the performance of wireless sensor networks. A dynamic tree based energy equalizing routing scheme (DTEER) was proposed to make an effort to gather data along with low energy consumption and low time delay. DTEER introduces a dynamic multi-hop route selecting scheme based on weight-value and height-value to form a dynamic tree and a mechanism similar to token passing to elect the root of the tree. DTEER can simply and rapidly organize all the nodes with low overhead and is robust enough to the topology changes. When compared with power-efficient gathering in sensor information systems (PEGASIS) and the hybrid, energy- efficient, distributed clustering approach (HEED), the simulation results show that DTEER achieves its intention of consuming less energy, equalizing the energy consumption of all the nodes, alleviating the data gathering delay, as well as extending the network lifetime perfectly.     

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.     

在传感器网络中构造延迟限定的最大化生命周期树

在一些对延迟敏感的持续性监视应用中,无线传感器网络中的数据收集需要构造延迟限定的最大化生命周期树,这属于NP完全问题。提出一个新的算法MILD,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。实验表明,与目前已有的协议相比,MILD能有效地限定延迟并延长树的生命周期。     

一种基于树的无线传感器网络数据收集方法

该文提出一种基于树的无线传感器网络数据收集方法,它将查询请求的传递与数据回传结构的建立有机结合起来,通过使用一种洪泛避免的方法传递查询请求,建立起一棵以sink节点为根的、包含最少中间节点的查询转发树,作为数据回传结构。理论分析和仿真试验表明,该方法不会降低无线传感器网络的连通性,可以有效节省能量。     

Resilient data gathering and communication algorithms for?emergency scenarios

A typical application field of Wireless Sensor Networks (WSNs) is the collection of environmental data, which is sent to a base station. Routing protocols are needed to efficiently direct the information flows to the base station. Since sensor nodes have strict energy constraints, data gathering and communication schemes for WSNs need to be designed for an efficient utilization of the available resources. An emergency management scenario is investigated, where a sensor network is deployed as virtual lifeline for fire fighters entering a building. Besides of supporting their navigation, the virtual lifeline is also used for two further purposes. First it enables the exchange of short voice messages between fire fighter and command post. For this, a fast and reliable routing protocol (EMRO) has been developed based on a broadcasting scheme. Second, measuring data, like temperature and gas, in the environment and informing fire fighters and command post about it, is of high importance. For this purpose a network coding based data gathering algorithm has been designed. The feasibility of simultaneously using the virtual lifeline for data gathering and communication and thus the coexistence of a classical routing protocol with a network coding scheme is studied in this paper by means of simulation and real experiments. The resilience to packet loss and node failure, as well as the transmission delay are investigated by means of short voice messages for the communication part and temperature readings for data gathering.     

Minimum spanning tree–based delay‐aware mobile sink traversal in wireless sensor networks

Energy efficient data collection in a delay‐bound application is a challenging issue for mobile sink–based wireless sensor networks. Many researchers have proposed the concept of rendezvous points (RPs) to design the path for the mobile sink. Rendezvous points are the locations in the network where the mobile sink halts and collects data from the nearby sensor nodes. However, the selection of RPs for the design of path has a significant impact on timely data collection from the network. In this paper, we propose an efficient algorithm for selection of the RPs for efficient design of mobile sink trajectory in delay‐bound applications of wireless sensor networks. The algorithm is based on a virtual path and minimum spanning tree and shown to maximize network lifetime. We perform extensive simulations on the proposed algorithm and compare results with the existing algorithms to demonstrate the efficiency of the proposed algorithm of various performance metrics.     

低能耗节点位置未知无线传感器网络控制方案

介绍了一种低能耗节点位置未知的网络控制方案,根据不同的网络运行轮数设定网络节点的通信半径,使网络具有良好的能量有效性.网络中基站经过构建阶段的启动过程、节点信息收集过程和节点信息上报过程,获得了整个网络节点的相对位置分布,然后整合节点-节点信息支路,得到具有回路链接的簇首节点集,其他节点根据自己邻居信息选择簇首节点,实现网络近似最小能耗拓扑的构建.通过仿真与同类典型算法LEACH-C、MCLB进行比较,结果显示该方案应用于网络运行时具有更长的网络生命周期、更少的信息总数和更低的网络构建代价.     

Energy-aware and quality of service-based routing in wireless sensor networks and vehicular ad hoc networks

Wireless Sensor Networks (WSNs) have increasingly been used for remote monitoring tasks. Limited capabilities of sensor nodes in terms of communication, computation, and storage, present challenges to protocols designed for WSNs. Due to the severe energy constraint of sensor nodes, among the major concerns is the problem of designing efficient energy-aware routing protocols. Numerous routing protocols have been proposed in the literature. Cluster-based routing protocols for large-scale WSNs have some advantages as compared to a flat network topology. Clustering results in a reduced number of messages that propagate through the network in order to accomplish a sensing task. It also offers improved power control. Quality of Service (QoS) is becoming an important feature of data routing in WSNs. QoS is required for real-time data transmission when the result of a sensing task is dependent not only on the correct sensing of the environment but also on the timely delivery of the event notification to the monitoring center, the Sink. The emergency preparedness and response class of applications, for instance, impose delay requirements on the delivery of event notification messages. Transmitting video and imaging data poses certain bandwidth, delay, and jitter requirements on the routing protocols. Vehicular Ad Hoc Networks (VANETs) are envisioned to improve intervehicle coordination and become a part of intelligent transport systems with an ultimate goal of increasing safety on the roads and improving travel comfort. VANETs may include WSNs that are placed along the sides of roads and provide monitoring of road conditions. Routing protocols for VANETs also aim at satisfying end-to-end QoS requirements. This paper first discusses energy-efficient clustering routing protocols for WSNs, followed by approaches aimed at satisfying QoS in WSNs and VANETS. Lastly, a discussion and comparison of features of the selected routing protocols and QoS-based approaches is presented.     

Online Data Gathering for Maximizing Network Lifetime in Sensor Networks

Energy-constrained sensor networks have been deployed widely for monitoring and surveillance purposes. Data gathering in such networks is often a prevalent operation. Since sensors have significant power constraints (battery life), energy efficient methods must be employed for data gathering to prolong network lifetime. We consider an online data gathering problem in sensor networks, which is stated as follows: assume that there is a sequence of data gathering queries, which arrive one by one. To respond to each query as it arrives, the system builds a routing tree for it. Within the tree, the volume of the data transmitted by each internal node depends on not only the volume of sensed data by the node itself, but also the volume of data received from its children. The objective is to maximize the network lifetime without any knowledge of future query arrivals and generation rates. In other words, the objective is to maximize the number of data gathering queries answered until the first node in the network fails. For the problem of concern, in this paper, we first present a generic cost model of energy consumption for data gathering queries if a routing tree is used for the query evaluation. We then show the problem to be NP-complete and propose several heuristic algorithms for it. We finally conduct experiments by simulation to evaluate the performance of the proposed algorithms in terms of network lifetime delivered. The experimental results show that, among the proposed algorithms, one algorithm that takes into account both the residual energy and the volume of data at each sensor node significantly outperforms the others     

A novel real-time scheme for (m,k)-firm streams in wireless sensor networks

The multimedia transmission based real-time applications have posed a big challenge to wireless sensor networks (WSNs) where both reliability and timeliness need to be guaranteed at the same time, to support an acceptable Quality of Service (QoS). The existing real-time routing protocols, however, are not able to meet the QoS requirements of realtime applications because of the inherent resource constraint of sensor nodes and instability of wireless communication. Therefore, we propose a real-time scheme in this paper, including a QoS-aware routing protocol and a set of fault recovery mechanisms, for (m,k)-firm based real-time applications over WSNs. A local status indicator which is specially devised for (m,k)-firm stream, is used for intermediate nodes to monitor and evaluate their local conditions. The proposed routing protocol takes into account of packet deadline, node condition and remaining energy of next hop, to make optimal forwarding decision. Additionally, according to the stream QoS and node condition, the proposed fault recovery mechanisms are utilized for nodes to handle the congestion, link failure and void problems occurred during transmission and remain the desired reliability and timeliness requirements. The proposed scheme has been well studied and verified through simulations. The results have proved the efficiency of the proposed scheme in terms of high successful transmission ratio, small end-to-end delay and long lifetime of network.     

DEED:一种无线传感器网络中高效节能的数据通信协议

无线传感器网络由许多具有低功率无线收发装置的传感器节点组成,能够有效地从不同环境监测收集周边环境信息并传送到远处的基站进行处理.由于传感器节点的电池能量极为有限,因此节点的通信应有效的利用能量,以延长网络的生命周期.LEACH^[4]协议是一种典型的能有效延长网络生命周期的节能通信协议.本文提出了一种分布的、高效节能的通信协议DEED,DEED利用了数据聚合技术,以聚类的方式组织节点,聚类首领在网络中均匀分布并组织成路由树,由根节点与基站直接通信.实验结果显示DEED性能远好于LEACH.     

A stable energy efficient clustering protocol for wireless sensor networks

Sensor networks comprise of sensor nodes with limited battery power that are deployed at different geographical locations to monitor physical events. Information gathering is a typical but an important operation in many applications of wireless sensor networks (WSNs). It is necessary to operate the sensor network for longer period of time in an energy efficient manner for gathering information. One of the popular WSN protocol, named low energy adaptive clustering hierarchy (LEACH) and its variants, aim to prolong the network lifetime using energy efficient clustering approach. These protocols increase the network lifetime at the expense of reduced stability period (the time span before the first node dies). The reduction in stability period is because of the high energy variance of nodes. Stability period is an essential aspect to preserve coverage properties of the network. Higher is the stability period, more reliable is the network. Higher energy variance of nodes leads to load unbalancing among nodes and therefore lowers the stability period. Hence, it is perpetually attractive to design clustering algorithms that provides higher stability, lower energy variance and are energy efficient. In this paper to overcome the shortcomings of existing clustering protocols, a protocol named stable energy efficient clustering protocol is proposed. It balances the load among nodes using energy-aware heuristics and hence ensures higher stability period. The results demonstrate that the proposed protocol significantly outperforms LEACH and its variants in terms of energy variance and stability period.     

无线传感器网络中一种能量均衡的基于连通支配集的数据收集算法

采用连通支配集来构建虚拟骨干可以减轻无线传感器网络的广播风暴问题.目前已有大量工作通过构造最小连通支配集形成网络虚拟骨干来进行高效数据收集.然而,最小连通支配集并不能有效均衡节点的能量耗费,导致网络生命周期较短.提出了一种能量均衡的基于连通支配集的分布式算法EBCDS来进行数据收集,通过选择能量水平和度均比较大的节点组成连通支配集,支配集中的节点组成一个规模不大但具有较高能量水平的网络骨干.网络中的所有数据沿骨干在较小的寻路空间中转发,能够节省节点能量,使骨干节点不会因为能量不足而过早死亡.理论分析表明,EBCDS能以O(nlogn)的消息复杂度构造连通支配集,仿真实验表明,EBCDS能有效节省节点能耗并延长网络生命周期.     

Integrated Energy and Trust-Based Semi-Markov Prediction for Lifetime Maximization in Wireless Sensor Networks

Many of today’s computing and communication models are distributed systems that are composed of autonomous computational entities that communicate with each other, usually by passing messages. Distributed systems encompass a variety of applications and wireless sensor networks (WSN) is an important application of it. The tiny, multiple functionality and low power sensor nodes are considered to be interconnected in the WSN for efficient process of aggregating and transmitting the data to the base station. The clustering-based schemes of sensor networks are capable of organizing the network through the utilization of a specifically designated node termed as the cluster head for the objective of energy conservation and data aggregation. Further, the cluster head is responsible for conveying potential information collected by the cluster member nodes and aggregate them before transmitting it to the base station. In this paper, a Reliable Cluster Head Selection Technique using Integrated Energy and Trust-based Semi-Markov Prediction (RCHST-IETSMP) is proposed with the view to extend the lifetime of sensor networks. This proposed RCHST-IETSMP incorporated two significant parameters associated with energy and trust for effective selection of cluster head facilitated through the merits of Semi-Markoc prediction integrated with the Hyper Erlang distribution process. The simulation results of the proposed RCHST-IETSMP scheme is proving to be efficient in upholding the residual energy of the network and the throughput to a maximum level of 23% and 19% predominant to the trust and energy-based clustering schemes considered for investigation.

     

DR-NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Internet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or time-series/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR-NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)-based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR-NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA-based clustered routing and clustering scheme using Canada Geese Migration Principle (CS-CGMP) for routing, respectively.     

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.     

A novel approach for designing delay efficient path for mobile sink in wireless sensor networks

In the recent years, the use of mobile sink has drawn enormous attention for data collection in wireless sensor networks (WSNs). Mobile sink is well known for solving hotspot or sinkhole problem. However, the design of an efficient path for mobile sink has tremendous impact on network lifetime and coverage in data collection process of WSNs. This is particularly an important issue for many critical applications of WSNs where data collection requires to be carried out in delay bound manner. In this paper, we propose a novel scheme for delay efficient trajectory design of a mobile sink in a cluster based WSN so that it can be used for critical applications without compromising the complete coverage of the target area. Given a set of gateways (cluster heads), our scheme determines a set of rendezvous points for designing path of the mobile sink for critical applications. The scheme is based on the Voronoi diagram. We also propose an efficient method for recovery of the orphan sensor nodes generated due to the failure of one or more cluster heads during data collection. We perform extensive simulations over the proposed algorithm and compare its results with existing algorithms to demonstrate the efficiency of the proposed algorithm in terms of network lifetime, path length, average waiting time, fault tolerance and adaptability etc. For the fault tolerance, we simulate the schemes using Weibull distribution and analyze their performances.     

Cooperative data collection in ad hoc networks

This paper studies the problem of data gathering in multi-hop wireless ad hoc networks. In this scenario, a set of wireless devices constantly sample their surroundings and initiate report messages addressed to the base station. The messages are forwarded in a multi-hop fashion, where the wireless devices act both as senders and relays. We consider data gathering without aggregation, i.e. the nodes are required to forward all the messages initiated by other nodes (in addition to their own) to the base station. This is in contrast to the well studied problem of data gathering with aggregation, which is significantly simpler. As some nodes experience a larger load of forward requests, these nodes will have their battery charges depleted much faster than the other nodes—which can rapidly break the connectivity of the network. We focus on maximizing the network lifetime through efficient balancing of the consumed transmission energy. We show that the problem is NP-hard for two network types and develop various approximation schemes. Our results are validated through extensive simulations.