Wireless sensor networks (WSNs) are designed to collect information across a large number of sensor nodes with limited batteries. Therefore, it is important to minimize energy consumption of each node, so as to extend the lifetime of the network. This paper proposes the use of an intelligent WSN communication architecture based on a multiagent system (MAS), to ensure optimal data collection. MAS refers to a group of agents that interact and cooperate to achieve a specific goal. To ensure this objective, we propose the integration of a migrating agent into each node to process data and enhance cooperation between neighboring nodes, while mobile agents (MAs) can be used to reduce data transfer between the nodes and send them to the base station (Sink). The collaboration of these agents generates a simple message that summarizes important information to be transmitted by an MA. To reduce the size of MAs, nodes in the network sectors are grouped in such way that, for each MA, an optimal itinerary is established, using a minimum amount of energy with efficient data aggregation within a minimum time. Successive simulations in large-scale sensor networks show the good performance of our proposal in terms of energy consumption and packet delivery rate.
Security is one of the major and important issues surrounding network sensors because of its inherent liabilities, i.e. physical size. Since network sensors have no routers, all nodes involved in the network must share the same routing protocol to assist each other for the transmission of packets. Also, its unguided nature in dynamic topology makes it vulnerable to all kinds of security attack , thereby posing a degree of security challenges. Wormhole is a prominent example of attacks that poses the greatest threat because of its difficulty in detecting and preventing. In this paper, we proposed a wormhole attach detection and prevention mechanism incorporated AODV routing protocol, using neighbour discovery and path verification mechanism. As compared to some pre-existing methods, the proposed approach is effective and promising based on applied performance metrics.
Currently, the majority of research in the area of wireless sensor networks (WSNs) is directed towards optimizing energy use during itinerary planning by mobile agents (MAs). The route taken by the MA when migrating can get a significant effect on energy consumption and the lifespan of the network. Conversely, finding an ideal arrangement of Source Nodes (SNs) for mobile agents to visit could be a problematic issue. It is within this framework that this work focused on solving certain problems related to itinerary planning based on a multimobile agent (MMA) strategy in networks. The objective of our research was to increase the lifespan of sensor networks and to diminish the length of the data collection task. In order to achieve our objective, we proposed a new approach in WSNs, which took into consideration the criterion of an appropriate number of MAs, the criterion of the appropriate grouping of SNs, and finally the criterion of the optimal itinerary followed by each MA to visit all its SNs. Thus, we suggested an approach that may be classified as a centralized planning model where the itinerary schedule is entirely shaped by the base station (sink) which, unlike other approaches, is no longer constrained by energy consumption. A series of simulations to measure the performance of the new planning process was also carried out.
Abstract-Multi mobile agents based on data collection and aggregations have proved their effective in wireless sensor networks (WSN). However, the way in which these agents are deployed must be intelligently planned and should be adapted to the characteristics of wireless sensor networks. While most existing studies are based on the algorithms of itinerary planning for multiple agents i.e. determining the number of mobile agents (MAs) to be deployed, how to group source nodes for each MA, attributing the itinerary of each MA for its source nodes. These algorithms determine the efficiency or effectiveness of aggregation. This paper aims at presenting the drawbacks of these approaches in large-scale network, and proposes a method for grouping network nodes to determine the optimal itinerary based on multi agents using a minimum amount of energy with efficiency of aggregation in a minimum time. Our approach is based on the principle of visiting central location (VCL). The simulation experiments show that our approach is more efficient than other approaches in terms of the amount of energy consumed in relation with the efficiency of aggregation in a minimum time.
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