International Journal of Computer Networks and Applications

S. Venkatasubramanian ¹, A. Suhasini ², C. Vennila ³

Affiliations
1 Department Computer Science and Engineering, Saranathan College of Engineering, Trichy, Tamil Nadu, IN
2 Department Computer Science and Engineering, Annamalai University, Tamil Nadu, IN
3 Department of Electronics and Communications Engineering, Saranathan College of Engineering, Trichy, Tamil Nadu, IN

Abstract

Mobile ad hoc networks (MANETs) is an infrastructure-less network, which is self-organizing, self-configuring and dynamic. The traditional routing protocol is not efficient against the routing challenges. The traditional MANET routing mechanisms involve overhearing, retransmission, and idle listening, which consume high energy. The main obstacles for MANET are end-to-end delay, energy consumption, and packet collision problems. The enhancement of network lifetime and communication performance is still a challenging task. This paper proposes a Ticket-ID zone manager routing protocol (TID-ZMGR) with sleep scheduling for MANETS. The proposed system consists of a zone routing system that is effective in load balancing and energy-efficient. In the proposed approach, nodes in the network are grouped as zones with a zone leader (ZL). The ZL is the node with higher efficiency in terms of energy, link quality, connectivity, and distances. The TID-ZMGR follows a multipath mechanism for balancing the load, and traffic is controlled by distributing the path from source to destination. The implementation of an adaptive sleep duty cycling approach ensures error-free communication around the network. Additionally, the adaptive sleep duty cycling approach increases the overall accuracy by saving the power on border nodes. The efficiency of the proposed work is proved by the comparison work carried out between Ticket-ID Based Routing management system (TID-BRM) Zone-based Routing with Parallel Collision Guided Broadcasting Protocol (ZCG) and Distance aware Zone Routing Protocol (DZRP) with TID-ZMGR. Experimental work evaluation metrics are zonal leader changes, energy consumptions, and network lifetime. Simulation result shows proposed mechanism achieves minimum energy consumption with improved output on throughput and packet delivery ratio.

Keywords

MANET, ZL, ZCG, DZRP, TID-ZMGR.

Full Text

   

S. Venkatasubramanian ¹, A. Suhasini ², S. Hariprasath ³

Affiliations
1 Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University, Chidambaram, Tamil Nadu, India., IN
2 Department of Computer Science and Engineering, Annamalai University, Chidambaram, Tamil Nadu, India, IN
3 Electronics and Communication Department, Saranathan College of Engineering, Trichy, Tamil Nadu,, IN

Abstract

.The newest example of wireless networks, known as mobile ad hoc networks (MANETs), offers some qualities, including a topology that can change dynamically, a baseless network, a range of transmission, a routing procedure, and reliability. In a black hole attack on a computer network, packets are deleted as opposed to being forwarded through a router. This often happens when a router has been corrupted by several circumstances. A routing attack called a "black hole" has the power to bring down an entire network. One of the most common types of assaults on MANETs is the Grey Hole Attack, in which a hostile node allows routing but prevents data transmission. MANET security is a top priority because they are far more susceptible to assaults than wired infrastructure. This study focused on detecting black and grey-hole attacks in MANET by using deep learning techniques. The forwarding ratio metric is used in the individual attack detection phase to distinguish between the defective and normal nodes. The encounter records are manipulated by malicious nodes in the collusion attack detection phase for escaping the detection process. The attacks are detected by using different deep learning techniques like Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM) network. The parameter tuning operation is carried out by using the Hybrid Cat-Particle Swarm Optimization (HCPSO). The simulation results shown in our proposed system detect with better accuracy.

Keywords

Black Hole Attack, Convolutional Neural Network, Mobile Ad-Hoc Networks, Long Short-Term Memory, Hybrid Cat-Particle Swarm Optimization, Grey Hole Attacks.

Full Text