Abstract
Wireless Sensor Nodes (WSN) has restricted sensing, communication and computational capabilities, in addition, are mainly operated by means of batteries in a bad atmosphere with the non-replenish-able power sources. As Data aggregation (DA) has more significance in solving the chief limitations of utilizing WSNs, say, the restricted battery life of the powered sensors in addition to short-communication gamut of sensors, it becomes an active research domain today. Effectively gathering data has constantly been the principal significance in WSNs. Regarding the static sink, nodes next to the sink would encompass more loads for routing data, and consequently Mobile Agent (MA) has been commenced. At the moment, the MA could move itself to the sensor nodes (SN) for amassing the data. This MA has made the gathering and aggregation of data possible in a means that is suitable for instantaneous applications. This work proposes an effective DA Scheme in WSN that employs manifold MAs for aggregating data in addition to transferring it to the sink centred on Itinerary planning. This could well be attained by grouping the nodes in clusters as well as planning itineraries effectually amongst cluster heads (CHs) alone. In the proposed DA scheme, itinerary planning is performed utilizing Hybrid Ant Colony Optimization-Genetic Algorithm (ACO-GA). Ultimately, the sink sends the MAs for amassing data as of the CH. Simulation outcome confirms clearly that the proposed work shows high-level performance than the other traditional techniques.
Highlights
Data aggregation signifies inspiring and well-researched topics in the wireless sensor network (WSN) [1,2,3,4,5] writings
The performance of the proposed data aggregation scheme using hybrid ACO-GA itinerary planning is contrasted with the prevailing techniques say, dynamic based data aggregation approach (DMA-DA)
The proposed work has a lower network delay contrasted with other existent methods. 4.1.11 Energy consumption for multi-mobile agent-based data aggregation scheme using TS fuzzy model (MDTSF) EC in the proposed MDTSF technique is contrasted with existing LEACH and T-LEACH technique
Summary
Data aggregation signifies inspiring and well-researched topics in the wireless sensor network (WSN) [1,2,3,4,5] writings. Gathering data effectively has always been of primary importance in a wireless sensor network. The mobile agent paradigm [7, 8] has made it possible to collect and aggregate data in a manner that is proper for real-time applications. Along this line, a number of heuristics have been scheduled to achieve effective itinerary planning for MAs [9]
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