Abstract: This project explores the architecture of mobile ad hoc networks in the context of computer science engineering.

Mobile Ad Hoc Network Architecture CSE Project Abstract

Introduction

Mobile Ad Hoc Networks (MANETs) have gained significant attention in recent years due to their ability to provide communication in dynamic environments without the need for pre-existing infrastructure. The self-configuring nature of MANETs allows nodes to join or leave the network at any time, making them suitable for applications such as emergency response, military communications, and vehicular networks.

Problem Statement

Despite the advantages of MANETs, there are several challenges that need to be addressed. One of the key issues is the design of a robust and efficient network architecture that can support the dynamic nature of mobile nodes and varying network conditions. The existing systems often lack scalability, reliability, and efficient routing mechanisms, leading to degraded network performance and poor user experience.

Existing System

The current MANET architectures primarily rely on protocols such as AODV (Ad-hoc On Demand Distance Vector) and DSR (Dynamic Source Routing) for routing data packets between nodes. While these protocols work well in small-scale networks with low mobility, they face scalability issues and high overhead in large-scale networks with high node density and frequent topology changes.

Disadvantages

Some of the key disadvantages of the existing MANET architectures include:

1. Limited scalability: The current protocols struggle to handle large networks with a high number of nodes efficiently.
2. High overhead: The routing protocols generate a significant amount of control traffic, leading to increased bandwidth consumption and latency.
3. Lack of reliability: The existing systems are prone to frequent route failures and packet losses, affecting the overall network performance.

Proposed System

To address the limitations of the existing MANET architectures, we propose a novel network architecture that leverages machine learning algorithms for adaptive routing and network management. The proposed system will dynamically adapt to changing network conditions and node movement, ensuring efficient data delivery and improved network performance.

Advantages

Some of the key advantages of the proposed system include:

1. Scalability: The use of machine learning algorithms will enable the network to scale effectively with an increasing number of nodes.
2. Improved reliability: By learning from past network behaviors, the system can make informed decisions to avoid route failures and packet losses.
3. Reduced overhead: The adaptive routing mechanisms will optimize the use of network resources, minimizing control traffic and latency.

Features

The proposed MANET architecture will incorporate the following features:

1. Machine learning-based routing: The system will use reinforcement learning algorithms to dynamically adjust routing paths based on network conditions and traffic patterns.
2. Adaptive network management: The architecture will reconfigure network parameters in real-time to adapt to node mobility and topology changes.
3. Quality of Service (QoS) support: The system will prioritize traffic based on application requirements, ensuring timely delivery of critical data packets.

Conclusion

In conclusion, the proposed mobile ad hoc network architecture offers a promising solution to the challenges faced by existing MANET systems. By leveraging machine learning algorithms for adaptive routing and network management, the new architecture aims to enhance scalability, reliability, and performance in dynamic network environments. Further research and experimentation are needed to validate the effectiveness of the proposed system and optimize its implementation in real-world scenarios.