Energy Efficient Routing Algorithm in Wireless Sensor Networks

This Wireless sensor network (WSN) is widely considered as one of the most important technologies for the twenty-first century, it provides the availability of small and low-cost sensor nodes with the ability of sensing different types of physical and environmental conditions, data processing, and wireless communication. Sensor nodes have a limited transmission range, and their processing and storage capabilities as well as their energy resources are also limited. Thus, optimized routing algorithms for wireless sensor networks should be utilized in order to maintain the routes in the network and to ensure reliable multi-hop communication under these conditions. Keywords: Wireless Sensor Networks, Energy Efficiency, Routing Protocols, Solar Sensors, Mobile Agent

Using Multi-agent System for Solving Coverage Problem in Wireless Sensor Network

Wireless sensor network (WSN) is one of the most important paradigms in computer networks because of the widespread applications. Coverage problem is a fundamental issue in sensor networks that reflects how the network is controlled by the sensors, this problem appears when any node becomes failure or out of the range, in this case the area will be disconnected and the data will not send to the destination. We present a new approach which uses a multi-agent system to solve this problem and perform an easy and secure network. In order to do that we implement sensor network by four phases: first construct a virtual network by matlab, second we use k-means clustering to cluster nodes in k-groups, third put the intelligent sensor in each cluster to be as a head for its group, fourth we divide the network to four regions and the closet agent to the sink will be the delegate to send the aggregated data from its region to the destination. Therefore, we tried to minimize the power consumption in WSN, we save the energy by keeping it sleep until it has a task to do , at this case the node changes its status to be in active mode and when it finishes it will be idle

A Trilaminar Data Fusion Localization Algorithm Supported by Sensor Network

In order to overcome some problems, such as its low accuracy and failure in evaluating its performance, this paper use the weighted trilaminar data fusion of LS-RSSI to improve the incipient localization estimate values by analyze and study the lease square (LS) and Received Signal Strength Indication (RSSI) algorithm. As a result, we obtain a trilaminar data fusion localization algorithm of LS-RSSI, which has a better optimized localization estimate value. This algorithm has the advantages of limited numbers of calculation and is able to reduce the localization errors. As shown in the simulation, we are able to get a much more accuracy and stable localization estimate value with the trilaminar data fusion technology

Organizations of Agents in Information Fusion Environments

Information fusion in a context-aware system is understood as a process that assembles assessments of the environment based on its goals. Advantages of intelligent approaches such as Multi-Agent Systems (MAS) and the use of Wireless Sensor Networks (WSN) within the information fusion process are emerging, especially in context-aware scenarios. However, it has become critical to propose improved and efficient ways to handle the enormous quantity of data provided by these approaches. Agents are a suitable option because they can represent autonomous entities by modeling their capabilities, expertise and intentions. In this sense, virtual organizations of agents are an interesting option/possibility because they can provide the necessary capacity to handle open and heterogeneous systems such as those normally found in the information fusion process. This paper presents a new framework that defines a method for creating a virtual organization of software and hardware agents. This approach facilitates the inclusion of context-aware capabilities when developing intelligent and adaptable systems, where functionalities can communicate in a distributed and collaborative way. Several tests have been performed to evaluate this framework and preliminary results and conclusions are presented

Towards the evaluation of the performance of an integration model of intelligent agents & WSN through metrics

Las Redes de Sensores Inalámbricas o WSN (por su acrónimo en inglés Wireless Sensor Networks), en general, son redes inalámbricas que se componen de centenares o miles de dispositivos autónomos y compactos llamados nodos sensores. Las WSN son un área emergente de los sistemas embebidos que involucran aplicaciones de gran escala, incluyendo monitoreo, conservación ambiental y control industrial. Sin embargo, aún existen muchas limitaciones en éstas, tales como el consumo de energía, la organización de los nodos en la red, la reprogramación de la red de sensores, la confiabilidad en la transmisión de los datos, la optimización de recursos (memoria y procesamiento), etc., que requieren de investigación por parte de la comunidad científica. Investigaciones actuales incluyen el uso de técnicas de Inteligencia Artificial Distribuida (IAD), específicamente de agentes inteligentes, para hacer frente a los desafíos y limitaciones que éstas traen consigo. De esta forma, se requiere evaluar el desempeño de este modelo integrado (IAD + WSN) a través del uso de métricas. El propósito de este artículo es plantear las principales métricas que serán consideradas para evaluar el desempeño de la integración de agentes inteligentes y WSN.Wireless Sensor Networks or WSN (by its acronym in English Wireless Sensor Networks), in general, are wireless networks that are made up of hundreds or thousands of compact, self-contained devices called sensor nodes. WSNs are an emerging area of systems embedded systems that involve large-scale applications, including monitoring, environmental conservation and industrial control. However, there are still many limitations in these, such as energy consumption, the organization of the nodes in the network, the reprogramming of the sensor network, the reliability in the data transmission, optimization of resources (memory and processing), etc., that require investigation by the community scientific. Current research includes the use of Intelligence techniques Distributed Artificial Intelligence (IAD), specifically of intelligent agents, to face the challenges and limitations that they bring with them. This form, it is necessary to evaluate the performance of this integrated model (IAD + WSN) through the use of metrics. The purpose of this article is to raise the main metrics that will be considered to evaluate the performance of the integration of intelligent agents and WSN