Signaling game approach to improve the MAC protocol in the underwater wireless sensor networks

Underwater sensor networks (UWSNs) are instructed for critical applications like military surveillance and underwater oil spills that conducted in a very massive three‐dimensional (3‐D) space that needs many underwater nodes (UNs) to cover the target area. Those UNs are not easy to recharge and cannot exploit solar power. MAC protocols deployed for UWSN ought to consider the energy efficiency, so as, to extend the network lifetime with total connectivity and significant throughput. Terrestrial MAC protocols could not be used for UWSN due to long and unpredictable propagation delay. Consequently, the development of a new MAC protocol for the harsh environment as underwater is a challenging task. In this study, we focus on the deployment of TDMA in UWSN for this, two schemes entitled TDMA slot sharing (TSS) and free time slots reallocation (FTSR) are proposed. Received data stored in the buffer waiting for processing and forwarding might lead to an unlimited data transfer latency those results in the buffer overflow. Otherwise, free time slots appearing during the communication process resulting from dead nodes increase uselessly sleep time for the rest of the nodes. Both schemes based on signaling game are proposed to overcome those problems, TSS is used to enable the slot sharing between UNs during the communication process to reduce the buffer overflow. FTSR scheme aims to increase the throughput of UNs by allowing the reuse of free time slots. Numerical results conducted in this work show good improvement in the network performance concerning throughput.     

Lifetime analysis of wireless sensor nodes in different smart grid environments

Wireless sensor networks (WSNs) can help the realization of low-cost power grid automation systems where multi-functional sensor nodes can be used to monitor the critical parameters of smart grid components. The WSN-based smart grid applications include but not limited to load control, power system monitoring and control, fault diagnostics, power fraud detection, demand response, and distribution automation. However, the design and implementation of WSNs are constrained by energy resources. Sensor nodes have limited battery energy supply and accordingly, power aware communication protocols have been developed in order to address the energy consumption and prolong their lifetime. In this paper, the lifetime of wireless sensor nodes has been analyzed under different smart grid radio propagation environments, such as 500 kV substation, main power control room, and underground network transformer vaults. In particular, the effects of smart grid channel characteristics and radio parameters, such as path loss, shadowing, frame length and distance, on a wireless sensor node lifetime have been evaluated. Overall, the main objective of this paper is to help network designers quantifying the impact of the smart grid propagation environment and sensor radio characteristics on node lifetime in harsh smart grid environments.     

Asymptotic uniform data-rate guarantees in large wireless networks

In this paper, we study asymptotic uniform data-rate guarantees in large wireless networks from an information-theoretic viewpoint. We consider the following question: what is the maximum achievable data rate that such a network can support for communication from an arbitrary radio node to its destination under transmission power and network-topology constraints, as the network size goes to infinity? In other words, we study the data-rate guarantee for an arbitrarily chosen source–destination pair assuming all other nodes act as relays. We consider two types of network deployments: (1) a regular deployment with unreliable nodes; and (2) a random deployment. We provide upper and lower bounds on the asymptotic achievable data rate for both linear and planar topologies under the two deployment models.     

Security in wireless sensor networks

Recent advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks that consist of many low-power, low-cost, and small-size sensor nodes. Sensor networks hold the promise of facilitating large-scale and real-time data processing in complex environments. Security is critical for many sensor network applications, such as military target tracking and security monitoring. To provide security and privacy to small sensor nodes is challenging, due to the limited capabilities of sensor nodes in terms of computation, communication, memory/storage, and energy supply. In this article we survey the state of the art in research on sensor network security.     

Deployment of a mobile wireless sensor network with k-coverage constraint: a cellular learning automata approach

Deployment of a wireless sensor network is a challenging problem, especially when the environment of the network does not allow either of the random deployment or the exact placement of sensor nodes. If sensor nodes are mobile, then one approach to overcome this problem is to first deploy sensor nodes randomly in some initial region within the area of the network, and then let the sensor nodes to move around and cooperatively and gradually increase the covered section of the area. Recently, a cellular learning automata-based deployment strategy, called CLA-DS, is introduced in literature which follows this approach and is robust against inaccuracies which may occur in the measurements of sensor positions or in the movements of sensor nodes. Despite its advantages, this deployment strategy covers every point within the area of the network with only one sensor node, which is not enough for applications with k-coverage requirement. In this paper, we extend CLA-DS so that it can address the k-coverage requirement. This extension, referred to as CLA-EDS, is also able to address k-coverage requirement with different values of k in different regions of the network area. Experimental results have shown that the proposed deployment strategy, in addition to the advantages it inherits from CLA-DS, outperforms existing algorithms such as DSSA, IDCA, and DSLE in covering the network area, especially when required degree of coverage differs in different regions of the network.     

Mobile Malicious Node Detection Using Mobile Agent in Cluster-Based Wireless Sensor Networks

Many application domains require that sensor node to be deployed in harsh or hostile environments, such as active volcano area tracking endangered species, etc. making these nodes more prone to failures. The most challenging problem is monitoring the illegal movement within the sensor networks. Attacker prefers mobile malicious node because by making the diversity of path intruder maximize his impact. The emerging technology of sensor network expected Intrusion detection technique for a dynamic environment. In this paper, a defective mechanism based on three-step negotiation is performed for identifying the mobile malicious node using the mobile agent. In many approaches, the multi-mobile agents are used to collect the data from all the sensor nodes after verification. But it is inefficient to verify all the sensor nodes (SNs) in the network, because of mobility, energy consumption, and high delay. In the proposed system this can be solved by grouping sensor nodes into clusters and a single mobile agent performs verification only with all the cluster heads instead of verifying all the SNs. The simulation result shows the proposed system shows a better result than the existing system.

     

A Hybrid Key Predistribution Scheme for Sensor Networks Employing Spatial Retreats to Cope with Jamming Attacks

In order to provide security services in wireless sensor networks, a well-known task is to provide cryptographic keys to sensor nodes prior to deployment. It is difficult to assign secret keys for all pairs of sensor node when the number of nodes is large due to the large numbers of keys required and limited memory resources of sensor nodes. One possible solution is to randomly assign a few keys to sensor nodes and have nodes be able to connect to each other with some probability. This scheme has limitations in terms of the tradeoffs between connectivity and memory requirements. Recently, sensor deployment knowledge has been used to improve the level of connectivity while using lesser amounts of memory space. However, deployment based key predistribution schemes may cause a large number of nodes to be cryptographically isolated if nodes move after key pre-distribution. Mobility may be necessitated for reasons depending on applications or scenarios. In this paper, we consider mobility due to spatial retreat of nodes under jamming attacks as an example. Jamming attacks are easy and efficient means for disruption of the connectivity of sensors and thus the operation of a sensor network. One solution for mobile sensor nodes to overcome the impact of jamming is to perform spatial retreats by moving nodes away from jammed regions. Moved nodes may not be able to reconnect to the network because they do not have any shared secret with new neighbors at new locations if strict deployment knowledge based key predistribution is employed. In this paper, we propose a hybrid key predistribution scheme that supports spatial retreat strategies to cope with jamming attacks. Our scheme combines the properties of random and deployment knowledge based key predistribution schemes. In the presence of jamming attacks, our scheme provides high key connectivity (similar to deployment knowledge based schemes) while reducing the number of isolated nodes. We evaluate the performance of our scheme through simulations and analysis.     

Data aggregation in sensor networks using learning automata

One way to reduce energy consumption in wireless sensor networks is to reduce the number of packets being transmitted in the network. As sensor networks are usually deployed with a number of redundant nodes (to overcome the problem of node failures which is common in such networks), many nodes may have almost the same information which can be aggregated in intermediate nodes, and hence reduce the number of transmitted packets. Aggregation ratio is maximized if data packets of all nodes having almost the same information are aggregated together. For this to occur, each node should forward its packets along a path on which maximum number of nodes with almost the same information as the information of the sending node exist. In many real scenarios, such a path has not been remained the same for the overall network lifetime and is changed from time to time. These changes may result from changes occurred in the environment in which the sensor network resides and usually cannot be predicted beforehand. In this paper, a learning automata-based data aggregation method in sensor networks when the environment’s changes cannot be predicted beforehand will be proposed. In the proposed method, each node in the network is equipped with a learning automaton. These learning automata in the network collectively learn the path of aggregation with maximum aggregation ratio for each node for transmitting its packets toward the sink. To evaluate the performance of the proposed method computer simulations have been conducted and the results are compared with the results of three existing methods. The results have shown that the proposed method outperforms all these methods, especially when the environment is highly dynamic.     

Hybrid routing and load balancing protocol for wireless sensor network

In wireless sensor network, when the nodes are mobile, the network structure keeps on changing dynamically, that is, new nodes enter the network and old members exit the network. As a result, the path from one node to the other varies from time to time. In addition, if the load on a particular part of the network is high, then the nodes will not be capable of transmitting the data. Thus, data delivery at the destination will be unsuccessful. Moreover, the part of the network involved in transmitting the data should not be overloaded. To overcome these issues, a hybrid routing protocol and load balancing technique is discussed in this paper for the mobile data collectors in which the path from source to destination is ensured before data transmission. The hybrid routing protocol that combines the reactive and proactive approach is used to enhance gradient based routing protocol for low power and lossy networks. This protocol can efficiently handle the movement of multiple sinks. Finally, load balancing is applied over the multiple mobile elements to balance the load of sensor nodes. Simulation results show that this protocol can increase the packet delivery ratio and residual energy with reduced delay and packet drop.     

基于正六边形的无线传感器网络边界部署技术研究

如何有效地部署节点是传感器网络系统设计中首要考虑的问题,它直接影响网络的性能和寿命.目前节点部署环境考虑无限空间或规则区域,但是实际部署环境如战场、森林检测等是有边界且边界形状不一的环境.文中提出了一种低能耗的无线传感器边界节点部署方案,并命名为V-HART方案.一方面方案基于六边形网格的配置策略,减少中心节点数量;另一方面方案将边界节点放置在六边形中垂线处的二维监测区域,节点数量减少,能耗降低.仿真结果显示,相比于凸边形区域节点部署,V-HART使用的节点少,具有能耗小、可靠性高和使用节点少等优点.     

Joint Source–Channel Communication for Distributed Estimation in Sensor Networks

Power and bandwidth are scarce resources in dense wireless sensor networks and it is widely recognized that joint optimization of the operations of sensing, processing and communication can result in significant savings in the use of network resources. In this paper, a distributed joint source-channel communication architecture is proposed for energy-efficient estimation of sensor field data at a distant destination and the corresponding relationships between power, distortion, and latency are analyzed as a function of number of sensor nodes. The approach is applicable to a broad class of sensed signal fields and is based on distributed computation of appropriately chosen projections of sensor data at the destination - phase-coherent transmissions from the sensor nodes enable exploitation of the distributed beamforming gain for energy efficiency. Random projections are used when little or no prior knowledge is available about the signal field. Distinct features of the proposed scheme include: (1) processing and communication are combined into one distributed projection operation; (2) it virtually eliminates the need for in-network processing and communication; (3) given sufficient prior knowledge about the sensed data, consistent estimation is possible with increasing sensor density even with vanishing total network power; and (4) consistent signal estimation is possible with power and latency requirements growing at most sublinearly with the number of sensor nodes even when little or no prior knowledge about the sensed data is assumed at the sensor nodes.     

Cluster Based Routing Protocol for Mobile Nodes in Wireless Sensor Network

Mobility of sensor nodes in wireless sensor network (WSN) has posed new challenges particularly in packet delivery ratio and energy consumption. Some real applications impose combined environments of fixed and mobile sensor nodes in the same network, while others demand a complete mobile sensors environment. Packet loss that occurs due to mobility of the sensor nodes is one of the main challenges which comes in parallel with energy consumption. In this paper, we use cross layer design between medium access control (MAC) and network layers to overcome these challenges. Thus, a cluster based routing protocol for mobile sensor nodes (CBR-Mobile) is proposed. The CBR-Mobile is mobility and traffic adaptive protocol. The timeslots assigned to the mobile sensor nodes that had moved out of the cluster or have not data to send will be reassigned to incoming sensor nodes within the cluster region. The protocol introduces two simple databases to achieve the mobility and traffic adaptively. The proposed protocol sends data to cluster heads in an efficient manner based on received signal strength. In CBR-Mobile protocol, cluster based routing collaborates with hybrid MAC protocol to support mobility of sensor nodes. Schedule timeslots are used to send the data message while the contention timeslots are used to send join registration messages. The performance of proposed CBR-Mobile protocol is evaluated using MATLAB and was observed that the proposed protocol improves the packet delivery ratio, energy consumption, delay and fairness in mobility environment compared to LEACH-Mobile and AODV protocols.     

Combinatorial Design of Key Distribution Mechanisms for Wireless Sensor Networks

Secure communications in wireless sensor networks operating under adversarial conditions require providing pairwise (symmetric) keys to sensor nodes. In large scale deployment scenarios, there is no priory knowledge of post deployment network configuration since nodes may be randomly scattered over a hostile territory. Thus, shared keys must be distributed before deployment to provide each node a key-chain. For large sensor networks it is infeasible to store a unique key for all other nodes in the key-chain of a sensor node. Consequently, for secure communication either two nodes have a key in common in their key-chains and they have a wireless link between them, or there is a path, called key-path, among these two nodes where each pair of neighboring nodes on this path have a key in common. Length of the key-path is the key factor for efficiency of the design. This paper presents novel deterministic and hybrid approaches based on Combinatorial Design for deciding how many and which keys to assign to each key-chain before the sensor network deployment. In particular, Balanced Incomplete Block Designs (BIBD) and Generalized Quadrangles (GQ) are mapped to obtain efficient key distribution schemes. Performance and security properties of the proposed schemes are studied both analytically and computationally. Comparison to related work shows that the combinatorial approach produces better connectivity with smaller key-chain sizes     

温室无线测控网络信息采集分系统设计研究

把无线传感器网络技术应用于温室无线测控网络信息采集分系统的设计.通过在温室大棚部署具有自组网传输能力的无线传感器网络,结合温室智能控制系统和农业信息专家系统,实现了温室信息采集的自动部署、自组织传输和温室环境的精细化控制.其中基于PC机的优化控制站点完成温室环境控制的智能决策及温室传感信息的海量存储、实时查询、统计分析和图形化显示,系统通过集成GPRS和以太网接口,实现了温室信息的远程访问.     

Three-dimensional and two-dimensional deployment analysis for underwater acoustic sensor networks

Underwater sensor networks find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, and tactical surveillance. In this paper, deployment strategies for two-dimensional and three-dimensional communication architectures for underwater acoustic sensor networks are proposed, and a mathematical deployment analysis for both architectures is provided. The objective is to determine the minimum number of sensors to be deployed to achieve optimal sensing and communication coverage, which are dictated by application requirements; provide guidelines on how to choose the optimal deployment surface area, given a target body of water; study the robustness of the sensor network to node failures, and provide an estimate of the number of redundant sensor nodes to be deployed to compensate for potential failures.     

Energy-Efficient Route Selection Strategies for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) facilitate monitoring and controlling of physical environments from remote locations with the best possible accuracy. Sensor networks are wireless networks consisting of groups of small, inexpensive nodes, which collect and disseminate critical data. Also, sensor nodes have various energy and computational constraints due to their inexpensive nature and ad hoc method of deployment. Considerable research has been focused on overcoming these deficiencies through low-energy consumption schemes. Among other factors, the route selection strategy may have an impact on the sensors lifetime, and following on the network lifetime. In this paper, we study various route selection strategies that aim at prolonging the lifetime of WSNs. Also, a new route selection scheme is proposed, that increases further the network lifetime. The performance of these schemes is analyzed through simulation.     

A New Dynamic Energy Efficient Latency Improving Protocol for Wireless Sensor Networks

In delay sensitive applications of wireless sensor network, it is required to monitor the situation continuously with the sensors. The continuous operation and processing delay, may contribute latency in data communication. This results in more energy consumption of the sensor nodes. It is difficult to replace the battery of a sensor node, after the deployment in the network. The efficient energy management and low latency are the important issues in delay sensitive applications as they affect the life of network. There are some limitations in existing routing protocols as they are particularly designed either for energy efficiency or minimum latency. This paper presents the new protocol to overcome some drawbacks of the existing protocols. A concept of distance metric based routing is explored for shortest routing path selection. This helps to reduce the overhead of the network traffic, which results in improvement of energy efficiency and latency. The simulation results are compared with standard ‘AODV’ routing protocol. It is observed that, this ‘Dynamic Energy Efficient and Latency Improving Protocol’ will be very much suitable for wireless sensor networks in industrial control applications.     

Development of Energy Efficient Image/Video Sensor Networks

Image/Video Sensor Networks are emerging applications for sensor network technologies. The relatively high energy consuming image capturing process and the large size of the data collected by image/video sensors presents new challenges for the sensor network in terms of energy consumption and network capacity. We propose to address these issues through the use of a high density network deployment. A high density network allows network nodes to conserve power by reducing their transmission power and simultaneously increases the potential for spatially concurrent transmissions within the network, resulting in improved network throughput. Furthermore, with the use of additional relay nodes, we allow a communication density that differs from the sensing density. A higher communication density has the potential to further increase the spatially concurrent transmission. Moreover, this reduces the relay burden of the sensor node, thus conserving sensor energy. In this work, we show analytically how a high density network design effectively improves energy consumption and network capacity. Furthermore, we discuss the constraints placed on a high density sensor network deployment due to application latency requirements, sensor coverage requirements, connectivity requirements, and node costs.     

Spatial and Temporal Multi-Aggregation for State-Based Sensor Data in Wireless Sensor Networks

Sensor nodes are thrown to remote environments for deployment and constitute a multi-hop sensor network over a wide range of area. Users hardly have global information on the distribution of sensor nodes. Hence, when users request state-based sensor readings such as temperature and humidity in an arbitrary area, networks may suffer unpredictable heavy traffic. This problem needs data aggregation to comply with user requirements and manage overlapped aggregation trees of multiple users efficiently. In this paper, spatial and temporal multiple aggregation (STMA) is proposed to minimize energy consumption and traffic load when a single or multiple users gather state-based sensor data from varions subareas through multi-hop paths. Spatial aggregation builds the aggregation tree with an optimal intermediary between a target area and a sink. The broadcast nature of wireless communication is exploited to build the aggregation tree in the confined area. Temporal aggregation uses the interval so that users obtain an appropriate amount of data they need without suffering excess traffic. The performance of STMA is evaluated in terras of energy consumption and area-to-sink delay in the simulation based on real parameters of Berkeley's MICA motes.     

Relay Node Deployment Strategies in Heterogeneous Wireless Sensor Networks

In a heterogeneous wireless sensor network (WSN), relay nodes (RNs) are adopted to relay data packets from sensor nodes (SNs) to the base station (BS). The deployment of the RNs can have a significant impact on connectivity and lifetime of a WSN system. This paper studies the effects of random deployment strategies. We first discuss the biased energy consumption rate problem associated with uniform random deployment. This problem leads to insufficient energy utilization and shortened network lifetime. To overcome this problem, we propose two new random deployment strategies, namely, the lifetime-oriented deployment and hybrid deployment. The former solely aims at balancing the energy consumption rates of RNs across the network, thus extending the system lifetime. However, this deployment scheme may not provide sufficient connectivity to SNs when the given number of RNs is relatively small. The latter reconciles the concerns of connectivity and lifetime extension. Both single-hop and multihop communication models are considered in this paper. With a combination of theoretical analysis and simulated evaluation, this study explores the trade-off between connectivity and lifetime extension in the problem of RN deployment. It also provides a guideline for efficient deployment of RNs in a large-scale heterogeneous WSN.