Abstract

Wireless sensor networks (WSNs) consist of large number of sensor nodes densely deployed in monitoring area with sensing, wireless communications and computing capabilities. In recent times, wireless sensor networks have used the concept of mobile agent for reducing energy consumption and for effective data collection. The fundamental functionality of WSN is to collect and return data from the sensor nodes. Data aggregation’s main goal is to gather and aggregate data in an efficient manner. In data gathering, finding the optimal itinerary planning for the mobile agent is an important step. However, a single mobile agent itinerary planning approach suffers from two drawbacks, task delay and large size of the mobile agent as the scale of the network is expanded. To overcome these drawbacks, this research work proposes: (i) an efficient data aggregation scheme in wireless sensor network that uses multiple mobile agents for aggregating data and transferring it to the sink based on itinerary planning and (ii) an attack detection using TS fuzzy model on multi-mobile agent-based data aggregation scheme is shortly named as MDTSF model.

Highlights

  • Data aggregation signifies inspiring and well-researched topics in the wireless sensor network (WSN) [1–5] 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

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Summary

Introduction

Data aggregation signifies inspiring and well-researched topics in the wireless sensor network (WSN) [1–5] writings. The energy restrictions of nodes in a sensor network call for fuel-saving data aggregation approaches and encompass the nexus lifecycle. 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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