Title: EFF-FAS: enhanced fruit fly optimisation based search and tracking by flying ad hoc swarm

Authors: Vishal Sharma; Roberto Sabatini; Subramanian Ramasamy; Kathiravan Srinivasan; Rajesh Kumar

Addresses: Department of Information Security Engineering, Soonchunhyang University, Asan-si 31538, South Korea ' School of Engineering, Aerospace Engineering and Aviation Discipline, RMIT University, Melbourne, VIC 3001, Australia ' School of Engineering, Aerospace Engineering and Aviation Discipline, RMIT University, Melbourne, VIC 3001, Australia ' School of Information Technology and Engineering, Vellore Institute of Technology (VIT), Vellore – 632 014, Tamil Nadu, India ' Computer Science and Engineering Department, Thapar University, Patiala, Punjab, 147004, India

Abstract: Flying ad hoc swarms are networks formed by autonomously operated aerial nodes. These nodes can be simple high altitude platforms or specifically configured unmanned aircraft (UA). Such networks are autonomous, temporary and mission dependent. One of the major applications of this ad hoc swarm formations is the efficient search and tracking of an area without any redundancy and overlapping. Non-redundant cell tracking is a computationally expensive task, which requires optimisation strategies to be adopted during a search process. Incorporating fruit fly optimisation (FOA) algorithm to a strategic search and track operation simplifies the complexity of the overall system. In this paper, FOA is extended in terms of its applicability by modifying the procedures of the algorithm to allow its applicability to an aerial swarm for non-redundant search over a predefined area with lower complexity. Network simulations demonstrate the effectiveness of the proposed approach towards search and track operations.

Keywords: ad hoc swarms; unmanned aircraft; searching; tracking; data acquisition; FOA; fruit fly optimisation.

DOI: 10.1504/IJAHUC.2019.098462

International Journal of Ad Hoc and Ubiquitous Computing, 2019 Vol.30 No.3, pp.161 - 172

Received: 17 Oct 2016
Accepted: 13 Mar 2017
Published online: 25 Mar 2019 *

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