Wireless sensor networks comprise of vast numbers of sensor nodes deployed to monitor a particular event (fire, intrusion, etc.) or measure a parameter (like temperature, pressure) value representative of the physical condition of the ambient environment. There is a growing need of using energy-efficient data gathering algorithms that can effectively aggregate the monitored/measured data from t...

Data gathering is a very important functionality in sensor networks. Most of current data gathering researches have been emphasized on issues such as energy efficiency and network lifetime maximization; and the technique of data aggregation is usually used to reduce the number of radio transmissions. However, there are many emerging sensor network applications with different requirements and co...

wireless sensor networks attracting a great deal of research interest. accurate localization of sensor nodes is a strong requirement in a wide area of applications. in recent years, several techniques have been proposed for localization in wireless sensor networks. in this paper we present a localization scheme with using only one mobile anchor station and received signal strength indicator tec...

As more and more servers appearing in the wireless environment provide accesses to mobile users, more and more demand and expectation is required by mobile users toward the available services. Mobile users are no longer satisfied with obtaining data only from one server, but require data from multiple servers either at the same or different locations. This eventually leads to the need for infor...

This paper focuses on active sensing of nonholonomic wheeled mobile robots (WMRs). Active sensing solves the following problem: given a current knowledge about the robot state and the environment, how to select the next sensing action or sequence of actions. A vehicle is moving autonomously through a static environment gathering information from sensors. The sensor data are used to generate the...

While Wireless Sensor Networks are versatile tools to monitor the environment in scenarios usually not accessible via wired infrastructure, deployments of such networks are challenging even for experts, particularly in remote areas. In this work, we present a smartphone based system that supports such deployments by keeping track of exact sensor locations and providing unique debugging tools, t...

Reinforcement Learning (RL) has emerged as a promising approach for improving the performance of Wireless Sensor Networks (WSNs). The Q-learning technique is one RL in which algorithm continuously learns by interacting with environment, gathering information to take certain actions. It maximizes determining optimal result from that environment. In this paper, we propose data based on named Boun...

The proliferation of the diverse information in the Internet makes the information gathering via a single mobile agent difficult. In addition, the limitations of the traditionally sequential task restrain the single agent to be applied to large, complicate applications. As a result, the applicable scope of a single mobile agent is limited. The advent of the collaborating multi-agents infrastruc...

Vehicular sensor networks are an emerging network paradigm, suitable for various applications in vehicular environment making use of vehicles’ sensors as data sources and Inter-Vehicle Communication systems for the transmissions. We present a solution, based on vehicular sensor networks, for gathering data from a certain geographic area while satisfying with a specific delay bound. The method l...

In Wireless Sensor Network (WSN), sensor nodes have limitations of energy, so the lifetime of the network is directly proportional to energy factor. All kinds of obstacles exist in the sensing field. Hence the challenge is to determine the obstacle avoiding shortest path with energy efficient clustering. EECP (Energy Efficient Clustering using PEGASIS) presents energy efficient routing by reduc...