Implementing and Evaluating the Performance Metrics Using Energy Consumption Protocols in Manets Using Multi-Path Routing- Fitness Function

The energy consumption plays a key role in Mobile Adhoc Networks in a day to day life. Mobile Ad Hoc Network (MANET) structure is a temporary network organized dynamically with a possible family of wireless mobiles independent of any extra infrastructural facilities and central administration requirements. Also, it provides solutions to overcome the minimal energy consumption issues. Nodes are battery operated temporarily does not operate on permanent batteries, so energy consumed by a battery depends on the lifetime of the battery, and its energy utilization dynamically decreases as the nodes change their position in MANETs. Multi-path routing algorithm in MANETs provides the best optimal; the solution to transmit the information in multiple paths to minimize the end to end delay, increases energy efficiency, and moderately enhances the life time of a network. The research mainly focused on minimum energy consumption techniques in MANET is of a great challenge in industries. In this paper, the author highlights a novel algorithmic approach Adhoc on Demand Multipath Distance Vector (AOMDV) routing protocol that increases the energy efficiency in MANET by incorporating the demand multipath distance and fitness function. The Adhoc on Demand Multipath Distance Vector-Fitness Function (AOMDV-FF) routing protocol short out minimum distance path that consumes minimum energy and the simulation performance is evaluated using network simulator-2 (NS2) tool. Two protocols are proposed in this work AOMDV and AOMDV-FF and compared some of the performance parameters like energy efficiency, network life time and routing overhead in terms of data transfer rate, data packet size and simulation time, etc. The overall simulation results of the proposed AOMDV-FF method is to be considered as a network with 49 nodesand the network performance factor-end to end delay 14.4358msec, energy consumption 18.3673 joules, packet delivery ratio 0.9911 and routing overhead ratio 4.68 are evaluated. The results show an enriched performance as compared to AOMDV and AOMR-LM methods

Mutation Based Hybrid Routing Algorithm for Mobile Ad-hoc Networks

Mobile Adhoc NETworks (MANETs) usually present challenges such as a highly dynamic topology due to node mobility, route rediscovery process, and packet loss. This leads to low throughput, a lot of energy consumption, delay and low packet delivery ratio. In order to ensure that the route is not rediscovered over and over, multipath routing protocols such as Adhoc Multipath Distance Vector (AOMDV) is used in order to utilize the alternate routes. However, nodes that have low residual energy can die and add to the problem of disconnection of network and route rediscovery. This paper proposes a multipath routing algorithm based on AOMDV and genetic mutation. It takes into account residual energy, hop count, congestion and received signal strength for primary route selection. For secondary path selection it uses residual energy, hop count, congestion and received signal strength together with mutation. The simulation results show that the proposed algorithm gives better performance results compared to AOMDV by 11% for residual energy, 45% throughput, 3% packet delivery ratio, and 63% less delay

Cooperative Self-Scheduling Secure Routing Protocol for Efficient Communication in MANET

In wireless transmission, a Mobile Ad-hoc Network (MANET) contains many mobile nodes that can communicate without needing base stations. Due to the highly dynamic nature of wireless, MANETs face several issues, like malicious nodes making packet loss, high energy consumption, and security. Key challenges include efficient clustering and routing with optimal energy efficiency for Quality of Service (QoS) performance. To combat these issues, this novel presents Cooperative Self-Scheduling Secure Routing Protocol (CoS3RP) for efficient scheduling for proficient packet transmission in MANET. Initially, we used Elite Sparrow Search Algorithm (ESSA) for identifies the Cluster Head (CH) and form clusters. The Multipath Optimal Distance Selection (MODS) technique is used to find the multiple routes for data transmission. Afterward, the proposed CoS3RP transmits the packets based on each node authentication. The proposed method for evaluating and selecting efficient routing and data transfer paths is implemented using the Network simulator (NS2) tool, and the results are compared with other methods. Furthermore, the proposed well performs in routing performance, security, latency and throughput

An Effective Wireless Sensor Network Routing Protocol Based on Particle Swarm Optimization Algorithm

Improving wireless communication and artificial intelligence technologies by using Internet of Things (Itoh) paradigm has been contributed in developing a wide range of different applications. However, the exponential growth of smart phones and Internet of Things (IoT) devices in wireless sensor networks (WSNs) is becoming an emerging challenge that adds some limitations on Quality of Service (QoS) requirements. End-to-end latency, energy consumption, and packet loss during transmission are the main QoS requirements that could be affected by increasing the number of IoT applications connected through WSNs. To address these limitations, an effective routing protocol needs to be designed for boosting the performance of WSNs and QoS metrics. In this paper, an optimization approach using Particle Swarm Optimization (PSO) algorithm is proposed to develop a multipath protocol, called a Particle Swarm Optimization Routing Protocol (MPSORP). The MPSORP is used for WSN-based IoT applications with a large volume of traffic loads and unfairness in network flow. For evaluating the developed protocol, an experiment is conducted using NS-2 simulator with different configurations and parameters. Furthermore, the performance of MPSORP is compared with AODV and DSDV routing protocols. The experimental results of this comparison demonstrated that the proposed approach achieves several advantages such as saving energy, low end-to-end delay, high packet delivery ratio, high throughput, and low normalization load.publishedVersio

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

Safe Routing Approach by Identifying and Subsequently Eliminating the Attacks in MANET

Wireless networks that are decentralized and communicate without using existing infrastructure are known as mobile ad-hoc networks. The most common sorts of threats and attacks can affect MANETs. Therefore, it is advised to utilize intrusion detection, which controls the system to detect additional security issues. Monitoring is essential to avoid attacks and provide extra protection against unauthorized access. Although the current solutions have been designed to defeat the attack nodes, they still require additional hardware, have considerable delivery delays, do not offer high throughput or packet delivery ratios, or do not do so without using more energy. The capability of a mobile node to forward packets, which is dependent on the platform's life quality, may be impacted by the absence of the network node power source. We developed the Safe Routing Approach (SRA), which uses behaviour analysis to track and monitor attackers who discard packets during the route discovery process. The attacking node recognition system is made for irregular routing node detection to protect the controller network's usual properties from becoming recognized as an attack node. The suggested method examines the nearby attack nodes and conceals the trusted node in the routing pathway. The path is instantly assigned after the initial discovery of trust nodes based on each node's strength value. It extends the network's life span and reduces packet loss. In terms of Packet Delivery Ratio (PDR), energy consumption, network performance, and detection of attack nodes, the suggested approach is contrasted with AIS, ZIDS, and Improved AODV. The findings demonstrate that the recommended strategy performs superior in terms of PDR, residual energy, and network throughput

Secure Energy Aware Optimal Routing using Reinforcement Learning-based Decision-Making with a Hybrid Optimization Algorithm in MANET

Mobile ad hoc networks (MANETs) are wireless networks that are perfect for applications such as special outdoor events, communications in areas without wireless infrastructure, crises and natural disasters, and military activities because they do not require any preexisting network infrastructure and can be deployed quickly. Mobile ad hoc networks can be made to last longer through the use of clustering, which is one of the most effective uses of energy. Security is a key issue in the development of ad hoc networks. Many studies have been conducted on how to reduce the energy expenditure of the nodes in this network. The majority of these approaches might conserve energy and extend the life of the nodes. The major goal of this research is to develop an energy-aware, secure mechanism for MANETs. Secure Energy Aware Reinforcement Learning based Decision Making with Hybrid Optimization Algorithm (RL-DMHOA) is proposed for detecting the malicious node in the network. With the assistance of the optimization algorithm, data can be transferred more efficiently by choosing aggregation points that allow individual nodes to conserve power The optimum path is chosen by combining the Particle Swarm Optimization (PSO) and the Bat Algorithm (BA) to create a fitness function that maximizes across-cluster distance, delay, and node energy. Three state-of-the-art methods are compared to the suggested method on a variety of metrics. Throughput of 94.8 percent, average latency of 28.1 percent, malicious detection rate of 91.4 percent, packet delivery ratio of 92.4 percent, and network lifetime of 85.2 percent are all attained with the suggested RL-DMHOA approach

Predicting and Recovering Link Failure Localization Using Competitive Swarm Optimization for DSR Protocol in MANET

Portable impromptu organization is a self-putting together, major construction-less, independent remote versatile hub that exists without even a trace of a determined base station or government association. MANET requires no extraordinary foundation as the organization is unique. Multicasting is an urgent issue in correspondence organizations. Multicast is one of the effective methods in MANET. In multicasting, information parcels from one hub are communicated to a bunch of recipient hubs all at once, at a similar time. In this research work, Failure Node Detection and Efficient Node Localization in a MANET situation are proposed. Localization in MANET is a main area that attracts significant research interest. Localization is a method to determine the nodes’ location in the communication network. A novel routing algorithm, which is used for Predicting and Recovering Link Failure Localization using a Genetic Algorithm with Competitive Swarm Optimization (PRLFL-GACSO) Algorithm is proposed in this study to calculate and recover link failure in MANET. The process of link failure detection is accomplished using mathematical modelling of the genetic algorithm and the routing is attained using the Competitive Swarm optimization technique. The result proposed MANET method makes use of the CSO algorithm, which facilitates a well-organized packet transfer from the source node to the destination node and enhances DSR routing performance. Based on node movement, link value, and endwise delay, the optimal route is found. The main benefit of the PRLFL-GACSO Algorithm is it achieves multiple optimal solutions over global information. Further, premature convergence is avoided using Competitive Swarm Optimization (CSO). The suggested work is measured based on the Ns simulator. The presentation metrix are PDR, endwise delay, power consumption, hit ratio, etc. The presentation of the proposed method is almost 4% and 5% greater than the present TEA-MDRP, RSTA-AOMDV, and RMQS-ua methods. After, the suggested method attains greater performance for detecting and recovering link failure. In future work, the hybrid multiway routing protocols are presented to provide link failure and route breakages and liability tolerance at the time of node failure, and it also increases the worth of service aspects, respectively

Topology Control, Routing Protocols and Performance Evaluation for Mobile Wireless Ad Hoc Networks

A mobile ad-hoc network (MANET) is a collection of wireless mobile nodes forming a temporary network without the support of any established infrastructure or centralized administration. There are many potential applications based the techniques of MANETs, such as disaster rescue, personal area networking, wireless conference, military applications, etc. MANETs face a number of challenges for designing a scalable routing protocol due to their natural characteristics. Guaranteeing delivery and the capability to handle dynamic connectivity are the most important issues for routing protocols in MANETs. In this dissertation, we will propose four algorithms that address different aspects of routing problems in MANETs. Firstly, in position based routing protocols to design a scalable location management scheme is inherently difficult. Enhanced Scalable Location management Service (EnSLS) is proposed to improve the scalability of existing location management services, and a mathematical model is proposed to compare the performance of the classical location service, GLS, and our protocol, EnSLS. The analytical model shows that EnSLS has better scalability compared with that of GLS. Secondly, virtual backbone routing can reduce communication overhead and speedup the routing process compared with many existing on-demand routing protocols for routing detection. In many studies, Minimum Connected Dominating Set (MCDS) is used to approximate virtual backbones in a unit-disk graph. However finding a MCDS is an NP-hard problem. In the dissertation, we develop two new pure localized protocols for calculating the CDS. One emphasizes forming a small size initial near-optimal CDS via marking process, and the other uses an iterative synchronized method to avoid illegal simultaneously removal of dominating nodes. Our new protocols largely reduce the number of nodes in CDS compared with existing methods. We show the efficiency of our approach through both theoretical analysis and simulation experiments. Finally, using multiple redundant paths for routing is a promising solution. However, selecting an optimal path set is an NP hard problem. We propose the Genetic Fuzzy Multi-path Routing Protocol (GFMRP), which is a multi-path routing protocol based on fuzzy set theory and evolutionary computing