Performance analysis of wireless sensor networks using queuing networks

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

Data collection is a fundamental and important issue in wireless sensor networks (WSNs). Recent research has shown that using mobile nodes to collect and carry data in WSNs has many advantages over static multi-hop routing. In this paper, we focus on the problem of data collection in WSNs with the minimum mobile nodes. A mobile node can pick up the data cached in a sensor node via one-hop wireless communications when it passes by a point that R meters away from this stationary sensor node. Since the storage capability of sensor node is limited, each mobile node must visit the sensor nodes, that assigned to it, every t seconds to avoid the overflow of sensor data. In order to reduce the cost of mobile nodes, we try to minimize the number of mobile nodes. We formally prove that the problem of minimizing the number of mobile nodes required by periodical data collection in WSNs is NP hard. We propose a path planning algorithm to minimize the number of mobile nodes. Our simulation results show that our approach can notably reduce the number of required mobile nodes as much as 55.6%.

Wireless Sensor Networks (WSNs) is one of the most rapidly growing research domain.This is because of the development of sensor nodes with extremely low cost and the applications of such sensor nodes are ever growing.WSNs are group of sensor nodes with a set of processors and limited memory unit.Reliable routing of packets from sensor nodes to its base station is the most important task for these networks.Also mobility of the nodes is considered to be one major criterion for WSNs.In this paper, a dynamic routing algorithm called the Mobility Assisted Dynamic Routing (MADR) algorithm has been proposed for the mobile wireless sensor networking system, where both the base station and the sensor nodes are in moving condition.The cluster head selection is based on three parameters: the energy efficiency of the sensor nodes, the mobility of the sensor nodes and the accessibility to the neighboring sensor nodes.The concept of cluster head panel is applied additionally to minimize the re-clustering time.The proposed algorithm is compared with an existing algorithm Low Energy Adaptive Clustering Hierarchy (LEACH).The simulation results show an excellent prolongation in overall network lifetime.

Ultra-wideband (UWB) communications is receiving significant attention recently due to its high data rates and low power, low interference transmission. This paper considers the issue of utilizing these advantages of UWB to design improved Wireless Sensor Networks (WSNs). In particular, we consider data gathering in wireless sensor networks using a mobile node for data collection. We first propose a network architecture where a mobile node equipped with both a UWB transceiver and a narrowband RF transceiver is used to collect data from sensor nodes. The sensor nodes are equipped with a narrowband RF transceiver and only a UWB transmitter (not receiver). This approach is chosen to strike a balance between cost of each sensor node and speed of data transfer, since a UWB transmitter is much less complex and expensive than a UWB receiver. We then propose a mobile Data Gathering (DGR) algorithm to find a minimal set of points in the sensor network, which will serve as data gathering points for the mobile node. We use a Voronoi diagram of the network as a starting point, considering each sensor node in the network as a site in the Voronoi diagram and finnding points in the network where data from multiple sites (sensor nodes) can be collected. We then use a weight function designed to reduce the number of these data collection points, and generate a new smaller set of points, such that the mobile node can collect data from multiple sites from each such point. With the aid of a discrete-event simulation model, we show significant savings in the total time for data collection while providing a high level of network coverage.

Node placement for connected target coverage in wireless sensor networks with dynamic sinks

One important issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is a scarce resource in a sensor node. Many protocols have been proposed for data-gathering between wireless sensor nodes. However, most of these protocols work on static wireless sensor networks. In this paper, we provide clustering-based and time-driven protocols which minimize energy dissipation for data-gathering in wireless mobile sensor networks where the sensor nodes are capable of mobility. We first consider the node mobility when organizing clusters. Our protocols will have a sensor node select a proper cluster-head to join in order to save energy. We then consider how to elect the cluster-heads and provide two algorithms for cluster-head election. Last, we implement all the protocols and perform the experiments for evaluating the protocols.

We present Sensei-UU, a testbed that supports mobile sensor nodes. The design objectives are to provide wireless sensor network (WSN) experiments with repeatable mobility and to be able to use the same testbed at different locations, including the target location. The testbed is inexpensive, expandable, relocatable and it is possible to reproduce it by other researchers. Mobile sensor nodes are carried by robots that use floor markings for navigation and localization. The testbed is typically used to evaluate WSN applications when sensor nodes move in meters rather than millimeters, eg. when human carries a mobile data sink (mobile phone) collecting data while passing fixed sensor nodes. To investigate the repeatability of robot movements, we have measured the achieved precision and timing of the robots. This precision is of importance to ensure the same radio link characteristics from one protocol experiment to another. We find that our robot localization is accurate to ±1 cm and variations in link characteristics are acceptably low to capture fading phenomena in IEEE 802.15.4. In the paper we show repeatable experiment results from three environments, two university corridors and from an anechoic chamber. We conclude that the testbed is relocatable between different environments and that the precision is good enough to capture fading effects in a repeatable way.

In mobility-centric environments, wireless sensor networks are designed to accommodate energy efficiency, dynamic self-organization and mobility. In typical applications of wireless sensor networks, fixed sensor nodes are mixed with mobile sensor nodes in "hot areas". Also, as they move, network topology needs to be reconstructed by reacting upon the mobility of sensor nodes quickly. In this paper we proposed an improved protocol called "LEACH-Mobile" for mobile nodes to declare the membership of a cluster as they move, and to confirm whether a mobile sensor node is able to communicate with a specific cluster head within a time slot allocated in TDMA schedule. The LEACH-Mobile protocol achieved definite improvement in data transfer success rate as mobile nodes increased compared to the non-mobility centric LEACH protocol

Wireless sensor networks (WSN) are considered to be a promising concept for enabling numerous categories of applications for both civil and military applications. This can include dismounted soldiers teams, group of animals or a group of mobile robots, where agents are moving collectively and sharing the same goal (e.g., destination, source of food or location of enemy). In this paper, we investigate the impact of dynamic agents based on a flock mobility model on the efficiency of wireless communications. We consider N mobile sensor agents capable of sensing and sending data packets periodically towards a base station (leader agent) directly or via intermediate nodes (relay nodes). At each time period, a sensor node can verify if an event is sensed based on a probability approach and then generates a data packet that is to be sent towards the destination, or else a sensor node can act as a relay node to forward data packets from other nodes. We evaluate the performance of the sensor nodes network under varying levels of perturbation of the collective motion of agents. The performance metrics observed are the residual energy, the number of sensors nodes still alive, the average normalized velocity, the packet delivery ratio, the end-to-end delay, and the average number of hops. Simulation results confirm that the dynamic agents have a significant impact on both the sensor network lifetime and the reachability of communications.

Pattern transformation-invariant schemes for wireless sensor networks based on an edge detection gradient-based mechanism

Data collection is a fundamental and important issue in wireless sensor networks. Recent research has shown that using mobile nodes to collect and carry data in WSNs has many advantages over static multi-hop routing. In this paper, we focus on the problem of reducing the number of mobile nodes require by data collection in WSNs. Each mobile node visits the sensor nodes, that assigned to it, every t seconds to pick up the cached data. The data gathered by mobile nodes far away from the base station are transferred to the base station through mobile nodes closer to the base station. We formally prove that the problem of data collection in WSNs with the minimum mobile nodes is NP hard. In order to reduce the number of mobile nodes, We propose two algorithms. One tries to reduce the number of mobile nodes and optimize their travel paths, and the other one carefully schedules the movement of all mobile nodes to make sure that they can cooperate with each other to transfer all gathered data to the base station. Our simulation results show that our approach can notably reduce the number of required mobile nodes as much as 46%.

Wireless sensor networks (WSNs) provide acceptable low cost and efficient deployable solutions to execute the target tracking, checking and identification of substantial measures. The primary step necessary for WSN is to organize all the sensor nodes in their positions to build up an effective network. In the sensor deployment model, Target COVerage (TCOV) and Network CONnectivity (NCON) are the basic issues in WSNs that have obtained significant consideration in sensor deployment. This paper intends to develop an intelligent context awareness algorithm for sensor deployment process in WSN. Accordingly, the process is divided into two phases. In the first phase, the TCOV process is performed, whereas the second phase of the algorithm establishes NCON among the sensors. An objective model to meet both TCOV and NCON is formulated as a minimization problem. The problem is solved using FireFly (FF) optimization to determine the optimal locations for sensors. It leads to an intelligent sensor deployment model that can determine the optimal locations for the sensors in the WSN. Further, the proposed FF-TCOV and FF-NCON models are compared against the conventional algorithms, namely, genetic algorithm, particle swarm optimization, artificial bee colony, differential evolution and evolutionary algorithm-based TCOV and NCON models. The results achieved from the simulation show the improved performance of the proposed technique.

Existing work on placing additional relay nodes in wireless sensor networks to improve network connectivity typically assumes homogeneous wireless sensor nodes with an identical transmission radius. In contrast, this paper addresses the problem of deploying relay nodes to provide fault-tolerance with higher network connectivity in heterogeneous wireless sensor networks, where sensor nodes possess different transmission radii. Depending on the level of desired fault-tolerance, such problems can be categorized as: (1) full fault-tolerance relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k ges 1) vertex-disjoint paths between every pair of sensor and/or relay nodes; (2) partial fault-tolerance relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k ges 1) vertex-disjoint paths only between every pair of sensor nodes. Due to the different transmission radii of sensor nodes, these problems are further complicated by the existence of two different kinds of communication paths in heterogeneous wireless sensor networks, namely two-way paths, along which wireless communications exist in both directions; and one-way paths, along which wireless communications exist in only one direction. Assuming that sensor nodes have different transmission radii, while relay nodes use the same transmission radius, this paper comprehensively analyzes the range of problems introduced by the different levels of fault-tolerance (full or partial) coupled with the different types of path (one-way or two-way). Since each of these problems is NP-hard, we develop O(sigmak <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> )-approximation algorithms for both one-way and two-way partial fault-tolerance relay node placement, as well as O(sigmak <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> )-approximation algorithms for both one-way and two-way full fault-tolerance relay node placement (sigma is the best performance ratio of existing approximation algorithms for finding a minimum k-vertex connected spanning graph). To facilitate the applications in higher dimensions, we also extend these algorithms and derive their performance ratios in d-dimensional heterogeneous wireless sensor networks (d ges 3). Finally, heuristic implementations of these algorithms are evaluated via simulations.

A Wireless Sensor network (WSN) consists of large number of low cost low power sensor nodes. The nature of wireless sensor networks makes them very attractive to attackers. One of the most popular and serious attacks in wireless sensor networks is sink hole attack and most existing protocols to defend against this attack used cryptographic methods with keys. In sink hole attack a sensor node will have a lot of false neighbors. Wireless Sensor Network has a dynamic topology, intermittent connectivity, and resource constrained device nodes. Researchers over the past years have encouraged the use of mobile agent to overcome these challenges. The proposed scheme is to defend against sink hole attacks using mobile agents. Mobile agent is a program segment which is self controlling. They navigate from node to node not only transmitting data but also doing computation. They are an effective paradigm for distributed applications, and especially attractive in a dynamic network environment. A routing algorithm with multiple constraints is proposed based on mobile agents. It uses mobile agents to collect information of all mobile sensor nodes to make every node aware of the entire network so that a valid node will not listen the cheating information from malicious or compromised node which leads to sink hole attack. The significant feature of the proposed mechanism is that it does not need any encryption or decryption mechanism to detect the sink hole attack. This mechanism does not require more energy than normal routing protocols like AODV. Here we implement a simulation-based model of our solution to recover from a Sinkhole attack in a Wireless Sensor Network. The mobile agents were developed using the Aglet.

Various communication services have been provided. They include environmental monitoring and/or control, ad-hoc communication between mobile nodes, and inter-vehicle communication in intelligent transport systems. As a means of facilitating the above advanced communication services, autonomous decentralized networks, such as wireless sensor networks (Akyildiz et al., 2002; Rajagopalan & Varshney, 2006), mobile ad-hoc networks (Perkins & Royer, 1999; Johnson et al., 2003; Clausen & Jaquet, 2003; Ogier et al., 2003), and wireless mesh networks (Yamamoto et al., 2009), have been intensively researched with great interests. Especially, a wireless sensor network, which is a key network to construct ubiquitous information environments, has great potential as a means of realizing a wide range of applications, such as natural environmental monitoring, environmental control in residential spaces or plants, object tracking, and precision agriculture (Akyildiz et al., 2002). Recently, there is growing expectation for a new network service by a wireless sensor network consisting of a lot of static sensor nodes arranged in a service area and a few mobile robots as a result of the strong desire for the development of advanced systems that can flexibly function in dynamically changing environments (Matsumoto et al., 2009). In this chapter, a large scale and dense wireless sensor network made up of many static sensor nodes with global positioning system, which is a representative network to actualize the above-mentioned sensor applications, is assumed. In a large scale and dense wireless sensor network, generally, hundreds or thousands of static sensor nodes limited resources, which are compact and inexpensive, are placed in a service area, and sensing data of each node is gathered to a sink node by inter-node wireless multi-hop communication. Each sensor node consists of a sensing function to measure the status (temperature, humidity, motion, etc.) of an observation point or object, a limited function of information processing, and a simplified wireless communication function, and it generally operates on a resource with a limited power-supply capacity such as a battery. Therefore, a data gathering scheme and/or a routing protocol capable of meeting the following requirements is mainly needed to prolong the lifetime of a large scale and dense wireless sensor network composed of hundreds or thousands of static sensor nodes limited resources. 1. Efficiency of data gathering 2. Balance of communication load among sensor nodes 3. Adaptability to network topology changes