Cross‐layer technique for boosting base‐station anonymity in wireless sensor networks

A wireless sensor network (WSN) principally is composed of many sensor nodes and a single in situ base station (BS), which are randomly distributed in a given area of interest. These sensor nodes transmit their measurements to the BS over multihop wireless paths. In addition to collecting and processing the sensed data, the BS performs network management operations. Because of the importance of the BS to the WSN, it is the most attractive target of attacks for an adversary. Basically, the adversary opts to locate the BS and target it with denial‐of‐service attack to temporarily or indefinitely disrupt the WSN operation. The adversary can intercept the data packet transmissions and use traffic analysis techniques such as evidence theory to uncover the routing topology. To counter such an attack, this paper presents a novel technique for boosting the BS anonymity by grouping nodes into clusters and creating multiple mesh‐based routing topologies among the cluster heads (CHs). By applying the closed space‐filling curves such as the Moore curve, for forming a mesh, the CHs are offered a number of choices for disseminating aggregated data to the BS through inter‐CH paths. Then, the BS forwards the aggregated data as well so that it appears as one of the CHs. The simulation results confirm the effectiveness of the proposed technique in boosting the anonymity of the BS.     

Increasing lifetime of wireless sensor networks using controllable mobile cluster heads

In a static wireless sensor network (WSN), sensors close to the base station (BS) run out of energy at a much faster rate than sensors in other parts of the network. This is because the sensor close to the BS always relays the data for other sensors, resulting in an unequal distribution of network residual energy. In this paper, we propose a scheme for enhancing the network lifetime using multiple mobile cluster heads (CHs) that can move in the WSN in a controllable manner. The CH controllably moves toward the energy‐rich sensors or the event area, offering the benefits of maintaining the remaining energy more evenly, or eliminating multihop transmission. Therefore, the proposed scheme increases the network lifetime. We theoretically analyze the energy consumption in our scheme and propose three heuristical mobility strategies. We further study the collaboration among CHs in order to maintain their connectivity to the BS to ensure the delay requirement for real‐time applications. Simulation shows that network lifetime is increased by upto 75% over existing approach by making CHs always move toward a stable equilibrium point. Our connectivity algorithm provides a best case improvement of 40% in transmission delays over existing schemes. Copyright © 2009 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.     

MAX–MIN aggregation in wireless sensor networks: mechanism and modeling

In‐network aggregation is crucial in the design of a wireless sensor network (WSN) due to the potential redundancy in the data collected by sensors. Based on the characteristics of sensor data and the requirements of WSN applications, data can be aggregated by using different functions. MAX—MIN aggregation is one such aggregation function that works to extract the maximum and minimum readings among all the sensors in the network or the sensors in a concerned region. MAX—MIN aggregation is a critical operation in many WSN applications. In this paper, we propose an effective mechanism for MAX—MIN aggregation in a WSN, which is called Sensor MAX—MIN Aggregation (SMMA). SMMA aggregates data in an energy‐efficient manner and outputs the accurate aggregate result. We build an analytical model to analyze the performance of SMMA as well as to optimize its parameter settings. Simulation results are used to validate our models and also evaluate the performance of SMMA. Copyright © 2010 John Wiley & Sons, Ltd.     

Survey on Wireless Sensor Network Applications and Energy Efficient Routing Protocols

Wireless sensor network (WSN) is a group of small power-constrained nodes that sense data and communicate it to the base station (BS). These nodes cover a vast region of interest (ROI) for several purposes according to the application need. The first challenge encountered in WSNs is how to cover the ROI perfectly and send the monitored data to the BS. Although the energy introduced during setup phase and the violation of energy fairness constraint of dynamic routing topologies, they achieve high network performance in terms of coverage and connectivity. In this paper, we categorize the applications of WSN based on different aspects to show the major protocol design issues. Thus, the energy efficiency of the recent proactive routing protocols is studied from different angles. The energy overhead and energy fairness of each protocol were carefully analyzed. The most energy efficient routing protocols for homogeneous proactive networks were studied and compared to highlight the research challenges and existing problems in this area. The results proved that energy overhead and route selection are the most effective aspects of network lifetime and network efficiency.

     

A scalable sensor network using a polar coordinate system

Due to the quick development of chip design and antenna manufacturing techniques, wireless facilities, such as wireless sensors, have become significantly smaller and cheaper than before. Their usage has also consequently been widely enriched, such as in the areas of healthcare and forest monitoring. A wireless sensor network (WSN) is often used to monitor a specific environment for a specific purpose. However, how to effectively utilize the limited resources in a sensor, also in a WSN, is crucial. In a WSN, geographical information is usually employed to locate a node and its surroundings. In this article, we propose a system, named relative position for sensor routing using polar-coordinates (RP²), that deploys a polar coordinate system to identify sensor positions and route network packets. A sensor ID that carries geographical metadata can be helpful in positioning a sensor.     

无线传感器网络——概念、应用及其对抗研究

无线传感器网络的问世和潜在应用前景，大有引发一场新技术革命的势头。由于具有节点数量巨大、分布密集、布设灵活以及自组织组网等特点，无线传感器网络充分体现了网络中心战的概念，在未来电子战／信息战领域有着广阔的应用前景。文章描述了无线传感器网络的基本组成及其在电子战／信息战领域的可能应用，分析研究了这种网络的薄弱环节及对抗的可行途径，并据此建议，在发展无线传感器网络技术的同时，应积极开展其军事应用和关键对抗技术的研究。     

Improving lifetime and network connections of 3D wireless sensor networks based on fuzzy clustering and particle swarm optimization

3D wireless sensor network (3D-WSN) has attracted significant interests in recent years due to its applications in various disciplinary fields such as target detection, object tracking, and security surveillance. An important problem in 3D WSN is the sensor energy optimization which determines a topology of sensors to prolong the network lifetime and energy expenditure. The existing methods for dealing with this matter namely low energy adaptive clustering hierarchy, LEACH-centralized, K-Means, single hop clustering and energy efficient protocol, hybrid-LEACH and fuzzy C-means organize the networks into clusters where non-cluster head nodes mainly carry out sensing tasks and send the information to the cluster head, while cluster head collect data from other nodes and send to the base station (BS). Although these algorithms reduce the total energy consumption of the network, they also create a large number of network disconnect which refers to the number of sensors that cannot connect to its cluster head and the number of cluster heads that cannot connect to the BS. In this paper, we propose a method based on fuzzy clustering and particle swarm optimization to handle this problem. Experimental validation on real 3D datasets indicates that the proposed method is better than the existing methods.     

Lightweight distributed geographical: a lightweight distributed protocol for virtual clustering in geographical forwarding cognitive radio sensor networks

Recent literature characterizes future wireless sensor networks (WSN) with dynamic spectrum capabilities. When cognitive radio is introduced as a main component of a network, a network management protocol is needed to ensure network connectivity and stability especially in highly dynamic environments. Implementing such protocols in WSN opens more challenges because of the resource constraints in sensor networks. We propose a distributed lightweight solution that fulfills this need for WSN. With this protocol, a node in a multichannel environment is quickly able to establish a control channel with neighboring nodes. Lightweight distributed geographical either increases or reduces the coverage area of the control channel based on perceived interference and adequately takes care of intersecting nodes with minimal overhead. By identifying local minima nodes, it also has the potentiality of reducing route failure by 70% further reducing the time and energy overhead incurred by switching to angle routing or maximum power transmission schemes usually used to solve the local minima issue. The work shows best operating values in terms of duty cycle and signal to noise ratio threshold frequencies and the lightweight nature of lightweight distributed geographical in terms of energy and communication overhead, which suits network management protocols for cognitive radio sensor networks. Copyright © 2013 John Wiley & Sons, Ltd.     

无线传感器网络节点定位算法研究

作为一种全新的信息获取和处理技术,拥有十分广泛的应用前景,其中,节点定位是重要的核心技术之一,同时也是无线传感器网络技术及应用的最核心的技术基础。目前已有的定位方法主要是按照基于测距和非基于测距进行分类总结。在研究大量相关文献的基础上,用一种全新的视角对目前现有的定位方法进行重新分类,介绍了WSN无线信号衰减模型,提出一种基于RSSI校验的加权质心节点定位算法,且与相关定位算法进行了比较分析和仿真实验得出结论。     

An effective graph‐theoretic approach towards simultaneous detection of fault(s) and cut(s) in wireless sensor networks

A failed sensor node partitions a wireless sensor network (WSN) into 2 or more disjoint components, which is called as a cut in the network. The cut detection has been considered as a very challenging problem in the WSN research. In this paper, we propose a graph‐theoretic distributed protocol to detect simultaneously the faults and cuts in the WSN. The proposed approach could be accomplished mainly in 3 phases, such that initialization phase, fault detection phase, and a cut detection phase. The protocol is an iterative method where at every time iteration, the node updates its state to calculate the potential factor. We introduced 2 terminologies such as a safe zone or cut zone of the network. The proposed method has been evaluated regarding various performance evaluation measures by implementing the same in the network simulator NS–2.35. The obtained results show that the proposed graph‐theoretic approach is simple yet very powerful for the intended tasks.     

ETPS-MAC: Energy Traffic Priority Scheduling-based QoS-aware MAC protocol for hierarchical WSNs

The evolution of the wireless sensor network (WSN) in recent years has reached its greatest heights and applications are increasing day by day, one such application is Smart Monitoring Systems (SMSs) which is in vision of implementation in every urban and rural areas. The implementation of WSN architecture in SMS needs an intelligent scheduling mechanism that efficiently handles the dynamic traffic load without sacrificing the energy efficiency of network. This paper presents a centralized TDMA scheduling based medium access control (MAC) protocol, called Energy Traffic Priority Scheduling MAC (ETPS-MAC) that accommodates variable traffic load while maintaining Quality-of-Service (QoS) assurance in hierarchical WSNs. The ETPS-MAC protocol employs priority scheduling algorithm which considers two factors for assigning priority, the energy factor and the traffic load factor to avoid packet buffering and maintains minimum data packet delay in case of high traffic load. Moreover, a novel rank-based clustering mechanism in FPS-QMAC protocol prolongs the network lifetime by minimizing the distance between the cluster head (CH) and the base station (BS). Both analytical and simulation models demonstrate the superiority of the ETPS-MAC protocol in terms of energy consumption, transmission delay, data throughput and message complexity when compared with the existing TDMA based MAC protocols.     

Energy efficient clustering algorithms for wireless sensor networks: novel chemical reaction optimization approach

Clustering has been accepted as one of the most efficient techniques for conserving energy of wireless sensor networks (WSNs). However, in a two-tiered cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving data from their member sensor nodes, aggregating them and transmitting that data to the base station (BS). Therefore, proper selection of CHs and optimal formation of clusters play a crucial role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient CH selection and energy balanced cluster formation algorithms, which are based on novel chemical reaction optimization technique (nCRO), we jointly called these algorithms as novel CRO based energy efficient clustering algorithms (nCRO-ECA). These algorithms are developed with efficient schemes of molecular structure encoding and potential energy functions. For the energy efficiency, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes in the CH selection phase. In the cluster formation phase, we consider various distance and energy parameters. The algorithm is tested extensively on various scenarios of WSNs by varying number of sensor nodes and CHs. The results are compared with original CRO based algorithm, namely CRO-ECA and some existing algorithms to demonstrate the superiority of the proposed algorithm in terms of energy consumption, network lifetime, packets received by the BS and convergence rate.     

Influence of Clamor on the Transmission of Worms in Remote Sensor Network

Wireless Sensor Network (WSN) with remote sensing capability is gaining popularity in many of the real time applications such as military, healthcare, environment, home and other commercial applications.WSN is typically composed of various components such as sensor node, relay node, cluster head, gateway, base station. Such a critical network is vulnerable to most dangerous threats caused by worms towards the integrity and confidentiality of information passed through it. The study of the influence of clamor in propagation of potential of worm in WSN is of more significance. In this paper, a logical model is proposed that is reliant on pandemic theory. It is an improvement of the SIRS, SEIS and models. We propose an altered SEIRS (Susceptible-Exposed-Infectious-Recovered-Susceptible) model with the added substance background noise that overcomes the drawbacks of the existing models. The close by adequacy of the model has been affirmed using Lyapunov’s work. We similarly address the effect of node fluctuations in the model through numerical simulations that is carried out to prove that our proposed system is mean square stable and resistance against fluctuations with respect to the spread of worms.

     

Load balancing techniques for lifetime maximizing in wireless sensor networks

Energy consumption has been the focus of many studies on Wireless Sensor Networks (WSN). It is well recognized that energy is a strictly limited resource in WSNs. This limitation constrains the operation of the sensor nodes and somehow compromises the long term network performance as well as network activities. Indeed, the purpose of all application scenarios is to have sensor nodes deployed, unattended, for several months or years.This paper presents the lifetime maximization problem in “many-to-one” and “mostly-off” wireless sensor networks. In such network pattern, all sensor nodes generate and send packets to a single sink via multi-hop transmissions. We noticed, in our previous experimental studies, that since the entire sensor data has to be forwarded to a base station via multi-hop routing, the traffic pattern is highly non-uniform, putting a high burden on the sensor nodes close to the base station.In this paper, we propose some strategies that balance the energy consumption of these nodes and ensure maximum network lifetime by balancing the traffic load as equally as possible. First, we formalize the network lifetime maximization problem then we derive an optimal load balancing solution. Subsequently, we propose a heuristic to approximate the optimal solution and we compare both optimal and heuristic solutions with most common strategies such as shortest-path and equiproportional routing. We conclude that through the results of this work, combining load balancing with transmission power control outperforms the traditional routing schemes in terms of network lifetime maximization.     

A delay-bounded event-monitoring and adversary-identification protocol in resource-constraint sensor networks

Event monitoring is a common application in wireless sensor networks. For event monitoring, a number of sensor nodes are deployed to monitor certain phenomenon. When an event is detected, the sensor nodes report it to a base station (BS), where a network operator can take appropriate action based on the event report. In this paper, we are interested in scenarios where the event must be reported within a time bound to the BS possibly over multiple hops. However, such event reports can be hampered by compromised nodes in the middle that drop, modify, or delay the event report.To defend against such an attack, we propose Sem, a Secure Event Monitoring protocol against arbitrary malicious attacks by Byzantine adversary nodes. Sem provides the following provable security guarantees. As long as the compromised nodes want to stay undetected, a legitimate sensor node can report an event to the BS within a bounded time. If the compromised nodes prevent the event from being reported to the BS within the bounded time, the BS can identify a pair of nodes that is guaranteSchool of Electrical and Computer Engineeringed to contain at least one compromised node. To the best of our knowledge, no prior work in the literature can provide such guarantees.Sem is designed to use the minimum level of asymmetric cryptography during normal operation when there is no attack, and use cryptographic primitives more liberally when an attack is detected. This design has the advantage that the overall Sem protocol is lightweight in terms of the computational resources and the network traffic required by the cryptographic operations. We also show an operational example of Sem using TOSSIM simulations.     

BSLPSDN: Base station location privacy via software-defined networking (SDN) in wireless sensor networks

Base station's location privacy in a wireless sensor network (WSN) is critical for information security and operational availability of the network. A key part of securing the base station from potential compromise is to secure the information about its physical location. This paper proposes a technique called base station location privacy via software-defined networking (SDN) in wireless sensor networks (BSLPSDN). The inspiration comes from the architecture of SDN, where the control plane is separated from the data plane, and where control plane decides the policy for the data plane. BSLPSDN uses three categories of nodes, namely, a main controller to instruct the overall operations, a dedicated node to buffer and forward data, and lastly, a common node to sense and forward the packet. We employ three kinds of nodes to collaborate and achieve stealth for the base station and thus protecting it against the traffic-analysis attacks. Different traits of the WSN including energy status and traffic density can actively be monitored by BSLPSDN, which positively affects the energy goals, expected life of the network, load on common nodes, and the possibility of creating diversion in the wake of an attack on the base station. We incorporated multiple experiments to analyze and evaluate the performance of our proposed algorithm. We use single controller with multiple sensor nodes and multiple controllers with multiple sensor nodes to show the level of anonymity of BS. Experiments show that providing BS anonymity via multiple controllers is the best method both in terms of energy and privacy.     

Cross-layer traffic analysis countermeasures against adaptive attackers of wireless sensor networks

Wireless Networks - In most Wireless Sensor Network (WSN) applications the sensor nodes forward their measurements to a central base station (BS). The unique role of the BS makes it a natural...     

Application modeling for performance evaluation on event-triggered wireless sensor networks

This paper presents an approach for event-triggered wireless sensor network (WSN) application modeling, aiming to evaluate the performance of WSN configurations with regards to metrics that are meaningful to specific application domains and respective end-users. It combines application, environment-generated workload and computing/communication infrastructure within a high-level modeling simulation framework, and includes modeling primitives to represent different kind of events based on different probabilities distributions. Such primitives help end-users to characterize their application workload to capture realistic scenarios. This characterization allows the performance evaluation of specific WSN configurations, including dynamic management techniques as load balancing. Extensive experimental work shows that the proposed approach is effective in verifying whether a given WSN configuration can fulfill non-functional application requirements, such as identifying the application behavior that can lead a WSN to a break point after which it cannot further maintain these requirements. Furthermore, through these experiments, we discuss the impact of different distribution probabilities to model temporal and spatial aspects of the workload on WSNs performance, considering the adoption of dynamic and decentralized load balancing approaches.     

基于P2P的无线传感器网络应用架构研究

通过基础网络互联多个传感器网络，为用户提供大规模、大范围、多样化的信息服务成为未来无线传感器网络的应用模式之一。据此，提出了一种基于P2P（Peer-to—Peer）技术的无线传感器网络应用架构。采用P2P技术，解决了大数据量的通信瓶颈，传感器网络亦可自由加入、变更或退出，方便部署，网络可扩展性好．同时屏蔽底层网络差异及多种接入方式．为用户提供多个访问入口。