基于传输距离和Sink移动的扩延网络寿命算法

在无线传感网络WSN(Wireless Sensor Network)中,传感节点通常以多跳方式向信宿Sink传输感测数据.由于邻近信宿Sink的传感节点需要承担数据转发的任务,比其他节点消耗更多的能量,缩短了网络寿命.为此,提出一种扩延网络寿命的新算法,记为NLTA(Network LifeTime Augmentation).NLTA算法采用了节点传输距离自适应调整和信宿Sink移动两个策略.节点依据能量情况,调整传输距离,减少能量消耗,然后根据路径容量值,调整Sink的位置,平衡网内的节点能量消耗,避免信宿Sink的周围节点能量过度消耗.仿真结果表明,提出的NLTA方案能够有效地提高网络寿命.     

Secured routing in wireless sensor networks using fault‐free and trusted nodes

Wireless sensor network (WSN) should be designed such that it is able to identify the faulty nodes, rectify the faults, identify compromised nodes from various security threats, and transmit the sensed data securely to the sink node under faulty conditions. In this paper, we propose an idea of integrating fault tolerance and secured routing mechanism in WSN named as fault tolerant secured routing: an integrated approach (FASRI) that establishes secured routes from source to sink node even under faulty node conditions. Faulty nodes are identified using battery power and interference models. Trustworthy nodes (non‐compromised) among fault‐free nodes are identified by using agent‐based trust model. Finally, the data are securely routed through fault‐free non‐compromised nodes to sink. Performance evaluation through simulation is carried out for packet delivery ratio, hit rate, computation overhead, communication overhead, compromised node detection ratio, end‐to‐end delay, memory overhead, and agent overhead. We compared simulation results of FASRI with three schemes, namely multi‐version multi‐path (MVMP), intrusion/fault tolerant routing protocol (IFRP) in WSN, and active node‐based fault tolerance using battery power and interference model (AFTBI) for various measures and found that there is a performance improvement in FASRI compared with MVMP, IFRP, and AFTBI. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

A Secure Routing Protocol with Trust and Energy Awareness for Wireless Sensor Network

Nodes in most of the deployments of Wireless Sensor Networks (WSNs) remain un-administered and exposed to variety of security attacks. Characterized by constrained resources and dynamically changing behavior of sensor nodes, reliable data delivery in WSNs is nontrivial. To counter node misbehavior attacks, traditional cryptographic and authentication based solutions have proved to be inappropriate due to high cost and incapability factors. Recently, trust based solutions have appeared to be viable solutions to address nodes’ misbehavior attacks. However, the existing trust based solutions incur high cost in trust estimation and network-wide dissemination which significantly increases traffic congestion and undermines network lifetime. This paper presents a Trust and Energy aware Secure Routing Protocol (TESRP) for WSN that exploits a distributed trust model for discovering and isolating misbehaving nodes. TESRP employs a multi-facet routing strategy that takes into consideration the trust level, residual energy, and hop-counts of neighboring nodes while making routing decisions. This strategy not only ensures data dissemination via trusted nodes but also balances out energy consumption among trusted nodes while traversing through shorter paths. Demonstrated by simulation results in NS-2, TESRP achieves improved performance in terms of energy consumption, throughput and network lifetime as compared to existing solutions.     

An efficient cluster-based communication protocol for wireless sensor networks

A wireless sensor network is a network of large numbers of sensor nodes, where each sensor node is a tiny device that is equipped with a processing, sensing subsystem and a communication subsystem. The critical issue in wireless sensor networks is how to gather sensed data in an energy-efficient way, so that the network lifetime can be extended. The design of protocols for such wireless sensor networks has to be energy-aware in order to extend the lifetime of the network because it is difficult to recharge sensor node batteries. We propose a protocol to form clusters, select cluster heads, select cluster senders and determine appropriate routings in order to reduce overall energy consumption and enhance the network lifetime. Our clustering protocol is called an Efficient Cluster-Based Communication Protocol (ECOMP) for Wireless Sensor Networks. In ECOMP, each sensor node consumes a small amount of transmitting energy in order to reach the neighbour sensor node in the bidirectional ring, and the cluster heads do not need to receive any sensed data from member nodes. The simulation results show that ECOMP significantly minimises energy consumption of sensor nodes and extends the network lifetime, compared with existing clustering protocol.     

Energy Efficient Model for Recovery from Multiple Nodes Failure in Wireless Sensor Networks

Wireless Personal Communications - Connectivity among deployed sensor nodes in wireless sensor network (WSN) is essential for collection and transmission of sensed data. In harsh environmental...     

Fish bone structure based data aggregation and routing in wireless sensor network: multi-agent based approach

Wireless sensor networks (WSNs) are constrained by limited node (device) energy, low network bandwidth, high communication overhead and latency. Data aggregation alleviates the constraints of WSN. In this paper, we propose a multi-agent based homogeneous temporal data aggregation and routing scheme based on fish bone structure of WSN nodes by employing a set of static and mobile agents. The primary components of fishbone structure are backbone and ribs connected to both sides of a backbone. A backbone connects a sink node and one of the sensor nodes on the boundary of WSN through intermediate sensor nodes. Our aggregation scheme operates in the following steps. (1) Backbone creation and identifying master centers (or nodes) on it by using a mobile agent based on parameters such as Euclidean distance, residual energy, backbone angle and connectivity. (2) Selection of local centers (or nodes) along the rib of a backbone connecting a master center by using a mobile agent. (3) Local aggregation process at local centers by considering nodes along and besides the rib, and delivering to a connected master center. (4) Master aggregation process along the backbone from boundary sensor node to the sink node by using a mobile agent generated by a boundary sensor node. The mobile agent aggregates data at visited master centers and delivers to the sink node. (5) Maintenance of fish bone structure of WSN nodes. The performance of the scheme is simulated in various WSN scenarios to evaluate the effectiveness of the approach by analyzing the performance parameters such as master center selection time, local center selection time, aggregation time, aggregation ratio, number of local and master centers involved in the aggregation process, number of isolated nodes, network lifetime and aggregation energy. We observed that our scheme outperforms zonal based aggregation scheme.     

D3: distributed approach for the detection of dumb nodes in wireless sensor networks

In this work, we propose D3—a distributed approach for the detection of ‘dumb’ nodes in a wireless sensor network (WSN). A dumb node can sense its surroundings, but is unable to transmit these sensed data to any other node, due to the sudden onset of adverse environmental effects. However, such a node resumes its normal operations with the resumption of favorable environmental conditions. Due to the presence of dumb nodes, the network is unable to provide the expected services. Therefore, it is prudent to re‐establish connectivity between dumb and other nodes, so that sensed data can be reliably transmitted to the sink. Before the re‐establishment of connectivity, a node needs to confirm its actual state of being dumb. Dumb behavior is dynamic in nature, and is, thus, distinct from the traditional node isolation problem considered in stationary WSNs. Therefore, the existing schemes for the detection of other misbehaviors are not applicable for detecting a dumb node in a WSN. Considering this temporal behavior of a dumb node, we propose an approach, D3, for the detection of dumb nodes. In the propose scheme, we uses cumulative sum test, which helps in detecting the dumb behavior. The simulation results show that there is 56% degradation in detection percentage with the increment in the detection threshold, whereas energy consumption and the message overhead increase by 40% with the increment in detection threshold.     

ProTru: a provenance‐based trust architecture for wireless sensor networks

Trust is an important component of wireless sensor networks for believability of the produced data, and trust history is a crucial asset in deciding trust of the data. In this paper, we show how provenance can be used for registering previous trust records and other information such as node type, data type, and node location. Our aim is to design a distributed trust‐enhancing architecture using only local provenance during sensor fusion with a low communication overhead. Our network is cognitive in the sense that our system reacts automatically upon detecting low trust. Copyright © 2016 John Wiley & Sons, Ltd.     

A data transmission protocol for reliable and energy-efficient data transmission in a wireless sensor-actuator network

In a wireless sensor-actuator network, sensor nodes gather information on the physical world and can deliver messages with sensed values to only nearby nodes due to weak radio. Thus, messages sent by nodes might be lost due to not only collision but also noise. Messages are forwarded by sensor nodes to an actuator node. In the redundant data transmission (RT) protocol, a sensor node sends a message with not only its sensed value but also sensed values received from other sensor nodes. Even if a message with a sensed value v is lost, an actuator node can receive the value v from a message sent by another sensor node. In addition, we have to reduce the energy consumption of a sensor node. A sensor node mainly consumes the energy to send and receive messages. Even if an event occurs, only some number of sensor nodes sensing the event send the sensed values to reduce the total energy consumption. We discuss an energy-efficient data transmission protocol. We evaluate the RT protocol compared with the CSMA protocol in terms of how much sensing data a node can receive in presence of messages loss. We evaluate the RT protocol in terms of how many number of sensed values an actuator node can receive in presence of message loss. We show that about 72% of sensed values can be delivered to an actuator node even if 95% of messages are lost due to noise and collision.     

An efficient weighted trust‐based malicious node detection scheme for wireless sensor networks

The aim of wireless sensor networks (WSNs) is to gather sensor data from a monitored environment. However, the collected or reported information might be falsified by faults or malicious nodes. Hence, identifying malicious nodes in an effective and timely manner is essential for the network to function properly and reliably. Maliciously behaving nodes are usually detected and isolated by reputation and trust‐based schemes before they can damage the network. In this paper, we propose an efficient weighted trust‐based malicious node detection (WT‐MND) scheme that can detect malicious nodes in a clustered WSN. The node behaviors are realistically treated by accounting for false‐positive and false‐negative instances. The simulation results confirm the timely identification and isolation of maliciously behaving nodes by the WT‐MND scheme. The effectiveness of the proposed scheme is afforded by the adaptive trust‐update process, which implicitly performs trust recovery of temporarily malfunctioning nodes and computes a different trust‐update factor for each node depending on its behavior. The proposed scheme is more effective and scalable than the related schemes in the literature, as evidenced by its higher detection ratio (DR) and lower misdetection ratio (MDR), which only slightly vary with the network's size. Moreover, the scheme sustains its efficient characteristics without significant power consumption overheads.     

Communication Coverage in Wireless Passive Sensor Networks

System lifetime of wireless sensor networks (WSN) is inversely proportional to the energy consumed by critically energy-constrained sensor nodes during RF transmission. In that regard, modulated backscattering (MB) is a promising design choice, in which sensor nodes send their data just by switching their antenna impedance and reflecting the incident signal coming from an RF source. Hence, wireless passive sensor networks (WPSN) designed to operate using MB do not have the lifetime constraints of conventional WSN. However, the communication performance of WPSN is directly related to the RF coverage provided over the field the passive sensor nodes are deployed. In this letter, RF communication coverage in WPSN is analytically investigated. The required number of RF sources to obtain interference-free communication connectivity with the WPSN nodes is determined and analyzed in terms of output power and the transmission frequency of RF sources, network size, RF source and WPSN node characteristics.     

Cluster head selection for energy efficient and delay-less routing in wireless sensor network

Wireless sensor network (WSN) is comprised of tiny, cheap and power-efficient sensor nodes which effectively transmit data to the base station. The main challenge of WSN is the distance, energy and time delay. The power resource of the sensor node is a non-rechargeable battery. Here the greater the distance between the nodes, higher the energy consumption. For having the effective transmission of data with less energy, the cluster-head approach is used. It is well known that the time delay is directly proportional to the distance between the nodes and the base station. The cluster head is selected in such a way that it is spatially closer enough to the base station as well as the sensor nodes. So, the time delay can be substantially reduced. This, in turn, the transmission speed of the data packets can be increased. Firefly algorithm is developed for maximizing the energy efficiency of network and lifetime of nodes by selecting the cluster head optimally. In this paper firefly with cyclic randomization is proposed for selecting the best cluster head. The network performance is increased in this method when compared to the other conventional algorithms.

     

Wireless Sensor Network Path Optimization Using Sensor Node Coverage Area Calculation Approach

The proposed work is based on the path optimization approach for wireless sensor network (WSN). Path optimization is achieved by using the NSG 2.1 Tool, TCL Script file and NS2 simulator to improve the quality of service (QoS). Path optimization approach finds best suitable path between sensor nodes of WSN. The routing approach is not only the solution to improve the quality but also improves the WSN performance. The node cardinally is taken under consideration using the ad-hoc on demand distance vector routing protocol mechanism. Ad hoc approach emphasize on sensor nodes coverage area performance along with simulation time. NSG 2.1 Tool calculates the sensor node packet data delivery speed which can facilitate inter-node communication successfully. An experimental result verified that the proposed design is the best possible method which can escape from slow network response while covering maximum sensor nodes. It achieves coverage support in sensor node deployment. The result outcomes show best path for transferring packet from one sensor node to another node. The coverage area of sensor node gives the percentage of average coverage ratio of each node with respect to the simulation time.

     

Statistical Multipath Queue-Wise Preemption Routing for ZigBee-Based WSN

Nowadays, wireless sensor network (WSN) is an important component in IoT environment, which enables efficient data collection and transmission. Since WSN consists of a large number of sensor nodes, network congestion can easily occur which significantly degrades the performance of entire network. In this paper a novel scheme called SMQP (Statistical Multipath Queue-wise Preemption) routing is proposed to balance the load and avoid the congestion for ZigBee-based WSN. This is achieved by employing statistical path scheduling and queue-wise preemption with multiple paths between any source and destination node. NS2 simulation reveals that the proposed scheme significantly improves the QoS in terms of delivery ratio, end-to-end delay, and packet delivery ratio compared to the representative routing schemes for WSN such as ad hoc on-demand distance vector and ad hoc on-demand multipath distance vector scheme.     

FBDR-Fuzzy Based DDoS Attack Detection and Recovery Mechanism for Wireless Sensor Networks

Wireless sensor networks (WSN) is considered as one of the exploring technology for its deployment of the massive number of dedicated sensor nodes which sense the environment and collect the data. The collected data are sent to the sink node through the intermediate nodes. Since the sensors node data are exposed to the internet, there is a possibility of vulnerability in the WSN. The common attack that affects most of the sensor nodes is the Distributed Denial of Services (DDoS) attack. This paper aims to identify the DDoS (Flooding) attack quickly and to recover the data of sensor nodes using the fuzzy logic mechanism. Fuzzy based DDoS attack Detection and Recovery mechanism (FBDR) uses type 1 fuzzy logic to detect the occurrence of DDoS attack in a node. Similarly fuzzy- type 2 is used for the recovery of data from the DDoS attack. Both the type 1 fuzzy-based rule and type 2 fuzzy-based rule perform well in terms of identifying the DDoS attack and recover the data under attack. It also helps to reduce the energy consumption of each node and improves the lifetime of the network. The proposed FBDR scheme is also compared with other related existing schemes. The proposed method saves energy usage by up to 20% compared with the related schemes. The experimental results represent that the FBDR method works better than other similar schemes.

     

A Three Layered Peer-to-Peer Energy Efficient Protocol for Reliable and Secure Data Transmission in EAACK MANETs

The wireless body sensor network (WBSN) an extensive of WSN is in charge for the detection of patient’s health concerned data. This monitored health data are essential to be routed to the sink (base station) in an effective way by approaching the routing technique. Routing of tremendous sensed data to the base station minimizes the life time of the network due to heavy traffic occurrence. The major concern of this work is to increase the lifespan of the network which is considered as a serious problem in the wireless network functionalities. In order to recover this issue, we propose an optimal trust aware cluster based routing technique in WBSN. The human body enforced for the detection of health status is assembled with sensor nodes. In this paper, three novel schemes namely, improved evolutionary particle swarm optimization (IEPSO), fuzzy based trust inference model, and self-adaptive greedy buffer allocation and scheduling algorithm (SGBAS) are proposed for the secured transmission of data. The sensor nodes are gathered to form a cluster and from the cluster, it is necessary to select the cluster head (CH) for the effective transmission of data to nearby nodes without accumulation. The CH is chosen by considering IEPSO algorithm. For securable routing, we exhibit fuzzy based trust inference model to select the trusted path. Finally, to reduce traffic occurrence in the network, we introduce SGBAS algorithm. Experimental results demonstrate that our proposed method attains better results when compared with conventional clustering protocols and in terms of some distinctive QoS determinant parameters.     

An Approach to Place Sink Node in a Wireless Sensor Network (WSN)

Wireless Personal Communications - In wireless sensor network (WSN), the data collected from the different sensor nodes are collectively forwarded to the special node called sink node. The...     

基于Beta分布的无线传感器网络分簇路由信任管理机制研究

信任管理机制为保障无线传感器网络安全提供了一种有效方案,通过对节点的行为进行评价,建立整个网络的信任管理机制,对判断的恶意节点采用相应的限制措施来保障安全。文章以Beta概率密度分布函数的期望值作为信任值,优化网络分簇路由协议,可在保障网络能量高效利用的同时,有效提升整个网络的安全性。