Ant Colony Optimization ACO Based Autonomous Secure Routing Protocol for Mobile Surveillance Systems

Abstract

Sensing plays a vital role in enabling smart cities. The mobile surveillance of different sectors, the retransmission of radio signals, and package delivery are the main applications conducted by unmanned vehicles in smart cities. Multiple unmanned vehicles or miniaturized real-time flying machines with onboard sensors, whether land- or air-based, communicate with each other to form a flying sensor network. Almost all of these machines are battery-operated. Therefore, power preservation is an extremely important factor to be taken into consideration. This paper proposes a power-aware biologically inspired secure autonomous routing protocol (P-BIOSARP) that depends on enhanced ant colony optimization (eACO). eACO autonomously and securely routes the data packet, and the power awareness maintains the power consumption of the flying sensor network. The novel intelligent power-aware routing protocol was implemented in network simulator 2 to perform a number of experiments with different scenarios. The scenarios included varying numbers of total nodes and mobile nodes, different packet rates, mobile source nodes, multiple mobile routing nodes, and, on the side of security, the injection of malicious nodes. The proposed protocol is compared with BIOSARP, E-BIOSARP, and SRTLD in terms of energy consumption, the delivery ratio, and traffic overhead. The analysis shows that the P-BIOSARP remarkably reduces energy consumption compared to other well-known protocols implemented on real testbeds.

Secure IoT Routing through Manifold Criterion Trust Evaluation using Ant Colony Optimization

“…Ramaswamy and Norman [38] introduced a trust model targeting network longevity and internal attacks in IoT. The exploration of bioinspired methods for secure IoT routing has seen algorithms like ACO applied in secured routing (Wang [39], Saleem & Ahmad [40]), decentralized traffic management (Nguyen and Jung [41]), electric vehicle selection (Ajinappa and Prabhakar [42]), and malware detection (El-Ghamry et al [43]). While ACO's adaptive nature is commendable, it may struggle with large-scale, dynamic IoT environments due to its iterative nature.…”

Enhancing Packet Reliability in Wireless Multimedia Sensor Networks using a Proposed Distributed Dynamic Cooperative Protocol (DDCP) Routing Algorithm

“…Simulation results demonstrate the superiority of the proposed mechanism in broader heterogeneous IoT networks with diverse nodes. This approach addresses the need for flexibility and efficiency in routing protocols for IoT networks comprising different types of nodes [16].…”