# Intelligent Communication in Wireless Sensor Networks
## 1 Introduction  
Advances in wireless technologies and technologies in micro manufacturing and microprocessor integration have created a new generation of wireless sensor networks (WSN) for a wide range of applications. A wireless sensor network consists of a set of sensors capable of collecting information from a monitored environment and transmitting it to a base station (sink) via the wireless medium. WSNs are often characterized by dense, large-scale deployment in resource-constrained environments. The limits imposed are reduced processing capacity, storage and especially energy because they are usually powered by batteries. The constraint of the size of a source node (SN) forces designers to limit the size of its battery and, therefore, the amount of energy available. Replacing a battery is rarely possible, either for cost reasons or for environmental constraints. This causes a problem related to energy consumption during operation of the various sensors of the network. WSNs have given rise to many research issues in order to improve network performance, including maximizing its lifespan. As a result, unlike traditional networks that are concerned with ensuring a good quality of service, research in WSNs must give primary importance to energy conservation. It is, therefore, widely recognized that energy limitation is a key issue in the design of the WSN because of the strict constraints it imposes on the operation of the network. Generally,experimental measurements have shown that data transmission is very costly in terms of energy consumption, while data processing consumes much less [1]. The cost of the information bit transmission in terms of energy is approximately the same as that required for processing a thousand operations in a typical SN [2]. The lifespan of a sensor network can be extended by the application of different techniques of energy consumption. One of these techniques consists in partitioning the network into sectors, as in our previous work [3]. For the past ten years, multi-agent systems (MAS) have grown rapidly and are applied to a wide variety of fields, such as the field of simulation and artificial life, robotics, and image processing. It is integrated in the WSN because of their intelligence and adaptation to different fields. Ant colonies, spiders, etc., are examples of MAS, which are applied to the WSN to process captured data, routing, detection of shorter itinerary, etc. The integration of mobile agent (MA) into the WSN solves several problems that can harm the wireless sensor network. Indeed, it can be used to reduce the cost of communication significantly, in particular the elimination of redundancies, by moving the processed data by an agent introduced into each sensor instead of bringing them to the raw state at the sink by the sensor itself. In this work, we will construct a system capable of simulating a network of wireless sensors in an environment, in order to minimize energy dissipation. The multi-agent system principle of operation is used for the intelligent processing of the data captured by the sensors, in terms of reduction of redundancy, evaluation of their importance, elimination of non-useful information, and cooperation between the neighboring SN. The main purpose of this technique is to group the data by a mobile agent and send them simultaneously to minimize transmission, instead of each sensor sending data through intermediate sensors. It also incorporates the principle of multi-agent system operation for the intelligent processing of the data captured by the sensors, in terms of the reduction of redundancy, the evaluation of their importance, and the elimination of non-useful information. A mobile agent activated by the sink has been proposed and sent to the sector. This agent will circulate in the sector nodes in a specified itinerary schema, to gather the captured and processed data by the agents (nodes).