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Journal articles
A new Itinerary Planning Approach Among Multiple Mobile Agents in Wireless Sensor Networks (WSN) to Reduce Energy Consumption
Abstract : 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.
https://hal.archives-ouvertes.fr/hal-01935612
Contributor : Sylvie Servigne <>
Submitted on : Monday, November 26, 2018 - 6:59:32 PM
Last modification on : Thursday, November 21, 2019 - 2:31:51 AM
Document(s) archivé(s) le : Wednesday, February 27, 2019 - 3:31:15 PM
Contributor : Sylvie Servigne <>
Submitted on : Monday, November 26, 2018 - 6:59:32 PM
Last modification on : Thursday, November 21, 2019 - 2:31:51 AM
Document(s) archivé(s) le : Wednesday, February 27, 2019 - 3:31:15 PM
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