A Comparative Analysis of OLSR Routing Protocol based on PSO and Cuckoo Search Optimization (CSO) in Manets

New developments in wireless communication have enabled the use of highly efficient and inexpensive wireless receivers in a variety of portable applications. Each node in a mobile network is a mobile device that independently organizes its own connection to the others and manages its own data transmissions. The adaptability, scalability, and cost reduction of mobile networks have attracted considerable attention. Because mobile networks are constantly changing, problems with routing and power usage are common. High error rates, energy limitations, and inadequate bandwidth are just a few of the issues plaguing mobile ad hoc networks. The relevance of routing protocols in dynamic multi-hop networks like Mobile Ad hoc Networks (MANET) has drawn the attention of many scholars. In this paper, we focus on  implementing an OLSR(Optimised Link State  Routing) protocol and evaluates its performance using two optmisation algorithm: Particle Swarm Optimization(OLSR) and Cuckoo Search Optimization (CSO). The simulation result suggests that PSO is superior to both CSO and the conventional OLSR routing technique. We implemented using NS-2 simulator for simulation and NAM for network animation

A Review of Wireless Sensor Networks with Cognitive Radio Techniques and Applications

The advent of Wireless Sensor Networks (WSNs) has inspired various sciences and telecommunication with its applications, there is a growing demand for robust methodologies that can ensure extended lifetime. Sensor nodes are small equipment which may hold less electrical energy and preserve it until they reach the destination of the network. The main concern is supposed to carry out sensor routing process along with transferring information. Choosing the best route for transmission in a sensor node is necessary to reach the destination and conserve energy. Clustering in the network is considered to be an effective method for gathering of data and routing through the nodes in wireless sensor networks. The primary requirement is to extend network lifetime by minimizing the consumption of energy. Further integrating cognitive radio technique into sensor networks, that can make smart choices based on knowledge acquisition, reasoning, and information sharing may support the network's complete purposes amid the presence of several limitations and optimal targets. This examination focuses on routing and clustering using metaheuristic techniques and machine learning because these characteristics have a detrimental impact on cognitive radio wireless sensor node lifetime

Optimal resource allocation for route selection in ad-hoc networks

Nowadays, the selection of the optimum path in mobile ad hoc networks (MANETS) is being an important issue that should be solved smartly. In this paper, an optimal path selection method is proposed for MANET using the Lagrange multiplier approach. The optimization problem considers the objective function of maximizing bit rate, under the constraints of minimizing the packet loss, and latency. The obtained simulation results show that the proposed Lagrange optimization of rate, delay, and packet loss algorithm (LORDP) improves the selection of optimal path in comparison to ad-hoc on-demand distance vector protocol (AODV). We increased the performance of the system by 10.6 Mbps for bit rate and 0.133 ms for latency

SSOPS based Solution to Improve QoS in VANET

Vehicular Ad-hoc Networks (VANETs) is an emerging network technology derived from ad-hoc networks. This paper provides the state-of-the-art of VANETs and provides optimum proposal by improving Quality of Service (QoS.) Today, wireless systems are preferred over wired systems and these are gaining popularity as it provides wireless connectivity to the users irrespective of their geographic position, VANET is one of them. VANETs are installed to minimize the risk of road accidents and to improve passenger comfort by permitting the vehicles to exchange various types of data. In this paper, the Signal Strength based Optimum Path Selection (SSOPS) based solution on how to mitigate the QoS issues that exists while using the existing methods are discussed. Moreover, the solution has been tested using NS2 software using various parameters

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

A critical review of Optimization MANET routing protocols

The main challenges in routing protocols are node mobility, resource constraints, error-prone channel states, and problems with hidden and unprotected terminals. This article provides an overview of the main protocols, their problems, and ways to improve them. The cell phone allows communication between two moving units via mobile stations (MS), mobile units, and landing units. The term "mobile ad hoc network" (MANET) refers to a group of devices connecting and communicating. The military, law enforcement, and emergency services have quickly become interested in MANETS because they provide a high quality of service. Path loss (PL), one of the biggest problems in wireless communications, can be caused by multiple reflections from an obstacle or by the source of the signal being far from the destination on the network. Multipath propagation, path loss, and interference reduce the network's quality of service (QoS). The best route is added to a router's routing table using a dynamic routing protocol, and an alternate path is chosen when the primary route is unavailable

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

Ant Algorithms for Routing in Wireless Multi-Hop Networks

Wireless Multi-Hop Networks (such as Mobile Ad hoc Networks, Wireless Sensor Networks, and Wireless Mesh Networks) promise improved flexibility, reliability, and performance compared to conventional Wireless Local Area Networks (WLAN) or sensor installations. They can be deployed quickly to provide network connectivity in areas without existing backbone/back-haul infrastructure, such as disaster areas, impassable terrain, or underserved communities. Due to their distributed nature, routing algorithms for these types of networks have to be self-organized. Ant routing is a bio-inspired self-organized method for routing, which is a promising approach for routing in such Wireless Multi-Hop Networks. This chapter provides an introduction to Wireless Multi-Hop Networks, their specific challenges, and an overview of the ant algorithms available for routing in such networks

Optimization of routing-based clustering approaches in wireless sensor network: Review and open research issues

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. In today’s sensor network research, numerous technologies are used for the enhancement of earlier studies that focused on cost-effectiveness in addition to time-saving and novel approaches. This survey presents complete details about those earlier models and their research gaps. In general, clustering is focused on managing the energy factors in wireless sensor networks (WSNs). In this study, we primarily concentrated on multihop routing in a clustering environment. Our study was classified according to cluster-related parameters and properties and is subdivided into three approach categories: (1) parameter-based, (2) optimization-based, and (3) methodology-based. In the entire category, several techniques were identified, and the concept, parameters, advantages, and disadvantages are elaborated. Based on this attempt, we provide useful information to the audience to be used while they investigate their research ideas and to develop a novel model in order to overcome the drawbacks that are present in the WSN-based clustering models