Simulation study of routing protocols in wireless sensor networks

Wireless sensor networks, a distributed network of sensor nodes perform critical tasks in many application areas such as target tracking in military applications, detection of catastrophic events, environment monitoring, health applications etc. The routing protocols developed for these distributed sensor networks need to be energy efficient and scalable. To create a better understanding of the performance of various routing protocols proposed it is very important to perform a detailed analysis of them. Network simulators enable us to study the performance and behavior of these protocols on various network topologies. Many Sensor Network frameworks were developed to explore both the networking issues and the distributed computing aspects of wireless sensor networks. The current work of simulation study of routing protocols is done on SensorSimulator, a discrete event simulation framework developed at Sensor Networks Research Laboratory, LSU and on a popular event driven network simulator ns2 developed at UC Berkeley. SensorSimulator is a discrete event simulation framework for sensor networks built over OMNeT++ (Objective Modular Network Test-bed in C++). This framework allows the user to debug and test software for distributed sensor networks. SensorSimulator allows developers and researchers in the area of Sensor Networks to investigate topological, phenomenological, networking, robustness and scaling issues, to explore arbitrary algorithms for distributed sensors, and to defeat those algorithms through simulated failure. The framework has modules for all the layers of a Sensor Network Protocol stack. This thesis is focused on the simulation and performance evaluation of various routing protocols on SensorSimulator and ns2. The performance of the simulator is validated with a comparative study of Directed Diffusion Routing Protocol on both ns2 and SensorSimulator. Then the simulations are done to evaluate the performance of Optimized Broadcast Protocols for Sensor Networks, Efficient Coordination Protocol for Wireless Sensor Networks on SensorSimulator. Also a performance study of Random Asynchronous Wakeup protocol for Sensor Networks is done on ns2

Improving Performance of WSN Based On Hybrid Range Based Approach

Improving the performance of WSN supported hybrid range based approach. WSN is self-possessed minimization error of nodes prepared with limited resources, limited memory and computational abilities. WSNs reliably work in unidentified hubs and numerous situations, it's difficult to trade sensor hubs after deployment, and therefore a fundamental objective is to optimize the sensor nodes' lifetime. A WSN may be a set of a large number of resource-constrained sensor nodes which have abilities for information detection, processing, and short-range radio communication, Analysis localization error minimization based several applications of wireless sensor networks (WSN) need data regarding the geographical location of each detector node. Self-organization and localization capabilities are one in every of the foremost necessary needs in detector networks. It provides a summary of centralized distance-based algorithms for estimating the positions of nodes during very sensing nodes. Secure localization of unknown nodes during a very wireless detector network (WSN) may be a vital analysis subject wireless sensor networks (WSN), a component of enveloping computing, are presently getting used on a large scale to look at period environmental standing, Be that as it may, these sensors work underneath extraordinary vitality imperatives and are planned by remembering an application. Proposed approaches are sensing node location and challenging task, involve assessing sort of various parameters needed by the target application. In study realize drawback not sense positioning of nodes .but proposed approach formula recognizes the optimal location of nodes supported minimize error and best answer in WSN. Localization algorithms mentioned with their benefits and disadvantages. Lastly, a comparative study of localization algorithms supported the performance in WSN. This was often done primarily to offer a summary of the proposed approach known today for reliable data and minimizing the energy consumption in wireless sensor networks

Stationary and Mobile Target Detection using Mobile Wireless Sensor Networks

In this work, we study the target detection and tracking problem in mobile sensor networks, where the performance metrics of interest are probability of detection and tracking coverage, when the target can be stationary or mobile and its duration is finite. We propose a physical coverage-based mobility model, where the mobile sensor nodes move such that the overlap between the covered areas by different mobile nodes is small. It is shown that for stationary target scenario the proposed mobility model can achieve a desired detection probability with a significantly lower number of mobile nodes especially when the detection requirements are highly stringent. Similarly, when the target is mobile the coverage-based mobility model produces a consistently higher detection probability compared to other models under investigation.Comment: 7 pages, 12 figures, appeared in INFOCOM 201

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

An objective based classification of aggregation techniques for wireless sensor networks

Wireless Sensor Networks have gained immense popularity in recent years due to their ever increasing capabilities and wide range of critical applications. A huge body of research efforts has been dedicated to find ways to utilize limited resources of these sensor nodes in an efficient manner. One of the common ways to minimize energy consumption has been aggregation of input data. We note that every aggregation technique has an improvement objective to achieve with respect to the output it produces. Each technique is designed to achieve some target e.g. reduce data size, minimize transmission energy, enhance accuracy etc. This paper presents a comprehensive survey of aggregation techniques that can be used in distributed manner to improve lifetime and energy conservation of wireless sensor networks. Main contribution of this work is proposal of a novel classification of such techniques based on the type of improvement they offer when applied to WSNs. Due to the existence of a myriad of definitions of aggregation, we first review the meaning of term aggregation that can be applied to WSN. The concept is then associated with the proposed classes. Each class of techniques is divided into a number of subclasses and a brief literature review of related work in WSN for each of these is also presented