Solving the MANET Routing Problem using Ant Colony Algorithm

Mobile ad-hoc networks (MANETs) are a collection of mobile nodes communicating wirelessly without a centralized infrastructure. The biggest challenge in MANETs is to find a path between communicating nodes, that is, the MANET routing problem. The considerations of the MANET environment and the nature of the mobile nodes create further complications which results in the need to develop special routing algorithms to meet these challenges. Swarm Intelligence, a bio-inspired technique, which has proven to be very adaptable in other problem domains, has been applied to the MANET routing problem as it forms a good fit to the problem. In this thesis, a study of Ant Colony based routing algorithms is carried out taking into consideration two of the most popular algorithms Ant based algorithms, AntHocNet and the Ant Routing Algorithm (ARA). A thorough analyis of ARA is carried out based on the effect of its individual routing mechanisms on its routing efficacy. The original ARA algorithm, although finds the shortest path between source and destination, is observed to not be competitive against other MANET algorithms such as AODV in performance criteria. Based on the analysis performed, modifications are proposed to the ARA algorithm. Finally, a performance evaluation of the original ARA and the modified ARA is carried out with respect to each other, and with respect to AODV, a state of the art MANET routing algorithm vis-a-vis mobility criteria. The motivation behind the thesis is to realize application of MANETs in real world applications by solving the problem of routing

Monitoring System-Based Flying IoT in Public Health and Sports Using Ant-Enabled Energy-Aware Routing.

In recent decades, the Internet of flying networks has made significant progress. Several aerial vehicles communicate with one another to form flying ad hoc networks. Unmanned aerial vehicles perform a wide range of tasks that make life easier for humans. However, due to the high frequency of mobile flying vehicles, network problems such as packet loss, latency, and perhaps disrupted channel links arise, affecting data delivery. The use of UAV-enabled IoT in sports has changed the dynamics of tracking and working on player safety. WBAN can be merged with aerial vehicles to collect data regarding health and transfer it to a base station. Furthermore, the unbalanced energy usage of flying things will result in earlier mission failure and a rapid decline in network lifespan. This study describes the use of each UAV's residual energy level to ensure a high level of safety using an ant-based routing technique called AntHocNet. In health care, the use of IoT-assisted aerial vehicles would increase operational performance, surveillance, and automation optimization to provide a smart application of flying IoT. Apart from that, aerial vehicles can be used in remote communication for treatment, medical equipment distribution, and telementoring. While comparing routing algorithms, simulation findings indicate that the proposed ant-based routing protocol is optimal

The Application of Ant Colony Optimization

The application of advanced analytics in science and technology is rapidly expanding, and developing optimization technics is critical to this expansion. Instead of relying on dated procedures, researchers can reap greater rewards by utilizing cutting-edge optimization techniques like population-based metaheuristic models, which can quickly generate a solution with acceptable quality. Ant Colony Optimization (ACO) is one the most critical and widely used models among heuristics and meta-heuristics. This book discusses ACO applications in Hybrid Electric Vehicles (HEVs), multi-robot systems, wireless multi-hop networks, and preventive, predictive maintenance

A Review of Various Swarm Intelligence Based Routing Protocols for Iot

The paper provides insight into various swarm intelligence based routing protocols for Internet of Things (IoT), which are currently available for the Mobile Ad-hoc networks (MANETs) and wireless sensor networks (WSNs). There are several issues which are limiting the growth of Internet of Things. These include the reliability, link failures, routing, heterogeneity etc. The MANETs and WSNs routing issues impose almost same requirements for IoT routing mechanism. The recent work of the worldwide researchers is focused on this area. protocols are based on the principles of swarm intelligence. The swarm intelligence is applied to achieve the optimality and the efficiency in solving the complex, multi-hop and dynamic requirements of the wireless networks. The application of the ACO technique tries to provide answers to many routing issues. Using the swarm intelligence and ant colony optimization principles, it has been seen that, the protocols’ efficiency definitely increases and also provides more scope for the development of more robust, reliable and efficient routing protocols for the IoT. As the various standard protocols available for MANETs and WSNs are not reliable enough, the paper finds the need of some efficient routing algorithms for IoT

Effects of Data Replication on Data Exfiltration in Mobile Ad hoc Networks Utilizing Reactive Protocols

A swarm of autonomous UAVs can provide a significant amount of ISR data where current UAV assets may not be feasible or practical. As such, the availability of the data the resides in the swarm is a topic that will benefit from further investigation. This thesis examines the impact of le replication and swarm characteristics such as node mobility, swarm size, and churn rate on data availability utilizing reactive protocols. This document examines the most prominent factors affecting the networking of nodes in a MANET. Factors include network routing protocols and peer-to-peer le protocols. It compares and contrasts several open source network simulator environments. Experiment implementation is documented, covering design considerations, assumptions, and software implementation, as well as detailing constant, response and variable factors. Collected data is presented and the results show that in swarms of sizes of 30, 45, and 60 nodes, le replication improves data availability until network saturation is reached, with the most significant benefit gained after only one copy is made. Mobility, churn rate, and swarm density all influence the replication impact

Application of Ant Colony optimization for MANETS

All networks tend to become more and more complicated. They can be wired, with lots of routers, or wireless, with lots of mobile nodes… The problem remains the same: in order to get the best from the network, there is a need to find the shortest path. The more complicated the network is, the more difficult it is to manage the routes and indicate which one is the best. The Nature gives us a solution to find the shortest path. The ants, in their necessity to find food and brings it back to the nest, manage not only to explore a vast area, but also to indicate to their peers the location of the food while bringing it back to the nest. Thus, they know where their nest is, and also their destination, without having a global view of the ground. Most of the time, they will find the shortest path and adapt to ground changes, hence proving their great efficiency toward this difficult task. The purpose of this project is to provide a clear understanding of the Ants-based algorithm, by giving a formal and comprehensive systematization of the subject. The simulation developed in Java will be a support of a deeper analysis of the factors of the algorithm, its potentialities and its limitations