Data dissemination based on mobile agent in wireless sensor networks

Recently, mobile agents have been proposed for efficient data dissemination in sensor networks [1-6]. In the traditional client/server-based computing architecture, data at multiple sources is transferred to a destination; whereas, a task-specific executable code traverses the relevant sources to gather data in the mobile-agent based computing paradigm. As described in [1], many inherent advantages (e.g. scalability, extensibility, energy awareness, reliability) of the mobile agent architecture make it more suitable for sensor networks than the client/server architecture. In this paper, a mobile agent is exploited in three levels (e.g. node level, task level, and combined task level) to reduce the information redundancy and communication overhead. 1

A new Itinerary planning approach among multiple mobile agents in wireless sensor networks (WSN) to reduce energy consumption

one of the important challenges in wireless sensors networks (WSN) resides in energy consumption. In order to resolve this limitation, several solutions were proposed. Recently, the exploitation of mobile agent technologies in wireless sensor networks to optimize energy consumption attracts researchers. Despite their advantage as an ambitious solution, the itineraries followed by migrating mobile agents can surcharge the network and so have an impact on energy consumption. Many researches have dealt with itinerary planning in WSNs through the use of a single agent (SIP: Single agent Itinerary Planning) or multiple mobile agents (MIP: Multiple agents Itinerary Planning). However, the use of multi-agents causes the emergence of the data load unbalancing problem among mobile agents, where the geographical distance is the unique factor motivating to plan the itinerary of the agents. The data balancing factor has an important role especially in Wireless sensor networks multimedia that owns a considerable volume of data size. It helps to optimize the tasks duration and thus optimizes the overall answer time of the network.  In this paper, we provide a new MIP solution (GIGM-MIP) which is based not only on geographic information but also on the amount of data provided by each node to reduce the energy consumption of the network. The simulation experiments show that our approach is more efficient than other approaches in terms of task duration and the amount of energy consumption

Genetic machine learning approach for data fusion applications in dense wireless sensor networks

Wireless Sensor Networks (WSN) are being targeted for use in applications like security, resources monitoring and factory automation. However, the reduced available resources raise a lot of technical challenges. Self organization in WSN is a desirable characteristic that can be achieved by means of data fusion techniques when delivering reliable data to users. In this paper it is proposed a genetic machine learning algorithm (GMLA) approach that makes a trade-off between quality of information and communication efficiency. GMLA is based on genetic algorithms and it can adapt itself dynamically to environment modifications. The main target of the proposed approach is to achieve set(organization in a WSN application with data fusion. Simulations demonstrate that the proposed approach can optimize communication efficiency in a dense WSN

A Mobile Agent Routing Protocol for Data Aggregation in Wireless Sensor Networks

Mobile agent data aggregation routing forwards mobile agents in wireless sensor network to collect and aggregate data. The key objective of data aggregation routing is to maximise the number of collected data samples at the same time as minimising network resource consumption and data collection delay. This paper proposes a mobile agent routing protocol, called zone-based mobile agent aggregation. This protocol utilises a bottom-up mobile agent migration scheme in which the mobile agents start their journeys from the centre of the event regions to the sink aiming to reduce the MA itinerary cost and delay and increase data aggregation routing accuracy. In addition, the proposed protocol reduces the impact of network architecture, event source distribution model and/or data heterogeneity on the performance of data aggregation routing

Survey on Mechanisms to detect and mitigate the impact of Sinkhole Attack in Wireless Sensor Networks

Abstract Sinkhole attack is an active attack, launched in a Wireles