A Wireless Sensor Network consists of several tiny devices which have the capability to sense and compute the environmental phenomenon. These sensor nodes are deployed in remote areas without any physical protections. A Wireless Sensor Network can have various types of anomalies due to some random deployment of nodes, obstruction and physical destructions. These anomalies can diminish the sensi...

This paper presents an approach for deploying a team of mobile sensor nodes to form a sensor network in indoor environments. The challenge in this work is that the mobile sensor nodes have no ability for localization or obstacle avoidance. Thus, our approach entails the use of more capable “helper” robots that “herd” the mobile sensor nodes into their deployment positions. To extensively explor...

In this paper, we define a mobile self-localization (MSL) problem for sparse and/or mobile robotic sensor networks, and propose an algorithm, MA-MDS-MAP(P), based on MultiDimensional Scaling (MDS) for solving the problem. For sparse robotic sensor networks, all the existing localization algorithms fail to work properly due to the lack of distance or connectivity data to uniquely calculate the g...

Optimizing sensor networks involves addressing a wide range of issues steaming from limited energy reserves, computation power, communication capabilities, and self-managing sensor nodes. The ns-2 simulation environment is a flexible tool for network engineers to investigate how various protocols perform with different configurations and topologies. This paper describes how we extended the ns-2...

The ability to automatically locate sensor nodes is essential in many Wireless Sensor Network (WSN) applications. To reduce the number of beacons, many mobile-assisted approaches have been proposed. Current mobile-assisted approaches for localization require special hardware or belong to centralized localization algorithms involving some deterministic approaches due to the fact that they explic...

Recently, mobile agents have been proposed for efficient data dissemination in sensor networks. In the traditional client/server-based computing architecture, data at multiple sources are transferred to a destination; whereas in the mobile-agent based computing paradigm, a taskspecific executable code traverses the relevant sources to gather data. Mobile agents can be used to greatly reduce the...

In this work we present a dead reckoning approach called Sensor-Assisted Monte Carlo Localization (SA-MCL) to account for low seed density situations in localization for mobile sensor networks. Our approach is based on using additional sensor information from a standard IMU device. It is evaluated in a mobile sensor network testbed based on radiocontrolled cars. The demo complements our full pa...

This paper considers the problem of deploying a mobile sensor network in an unknown environment using distributed sensing and computation. A mobile sensor network is composed of a distributed collection of nodes, each of which has sensing, computation, communication and locomotion capabilities. Such networks are capable of self-deployment; i.e., starting from some compact initial configuration,...

A key problem in the deployment of sensor networks is that of determining the location of each sensor such that subsequent data gathered can be registered. We would also like the network to provide localization for mobile entities, allowing them to navigate and explore the environment. In this paper, we present a thorough evaluation of our algorithm for localizing and mapping the mobile and sta...

Usefulness of sensor network applications in human life is increasing day by day and the concept of wireless connection promises new application areas. Sensor network can be very beneficial in saving human life from terrorist attacks causing explosion in certain areas leading to casualties. But realization of the sensor network application in explosive detection requires high scalability of the...