PREDICTION OF LINK RELIABILITY IN A WIRELESS MOBILE AD HOC NETWORK
Need help with a related project topic or New topic? Send Us Your Topic
DOWNLOAD THE COMPLETE PROJECT MATERIAL
PREDICTION OF LINK RELIABILITY IN A WIRELESS MOBILE AD HOC NETWORK
Chapter One:
Introduction
1.1 Background
Networks have recently advanced at a rapid speed, linking a vast number of devices ranging from servers to micro-devices implanted in objects (Wazwaz, 2005).
These devices offer services that can support a wide range of applications, including environmental monitoring, medical services, military applications, disaster recovery (fire, flood, earthquake, and so on), law enforcement, and so on.
Many of the networks that serve such applications are mobile wireless networks, with the requisite infrastructure support installed either permanently or ad hoc (Wazwaz, 2005).
For example, MANET is used in cases where setting up an infrastructure-based network is not practical or desired due to coverage constraints, network outages, congestion, and so on. Developers and customers are very interested in and concerned about the reliability of telecommunications systems.
The ultimate goal is to enhance service quality, throughput, cost, and delay (Erickson et al., 1990). The unique feature of MANET, such as self-organizing ability and high mobility of Mobile Nodes (MN), results in a dynamic architecture.
But the robust connecting of each MN inside the coverage region set it apart from other forms of networks. As a result of MANET’s expansion, new scenarios have emerged in which users can benefit from anywhere and at any time.
A node in a MANET may fail for a variety of reasons, including low transmission range, being outside of the coverage region, atmospheric impacts, physical barriers, and having a limited battery life.
In other words, the MN time-to-failure follows a statistical distribution. Links between nodes may fail due to factors such as mobility, interference, dynamic topology, congestion, or exceeding transmission range.
These characteristics make modelling and reliability analysis of such networks a difficult and daunting endeavour. In general, every system can be represented as random graphs or probabilistic graphs, with each user/terminal denoted as a node and the connections between them as edges.
Network reliability for infrastructure-based networks is classified as Two Terminal (TTR), All-Terminal (ATR), K-Terminal (KTR), and All-Operational Terminal (AoTR) Reliabilities based on the number of communicating nodes.
TTR is defined as the likelihood that a specific pair of nodes (the source, s, and sink, r) with known success/failure probabilities of their elements will remain connected by a path generated by the operating nodes and links.
The likelihood that each node in the network can communicate with every other node is known as ATR. Similarly, the chance of at least k designated nodes communicating with one another is KTR. The likelihood that all operational nodes can communicate with one another is known as AoTR.
1.2 Statement of Problem
Transmitting large data speeds is a major issue since network quality degrades fast as the number of hops increases (Paz, 2010). Because real-time systems are sensitive to delays, they demand a high level of reliability and service quality assessments.
Despite substantial work on predicting and analysing the reliability of ad-hoc networks, the networks remain unpredictable. This needs the development of more effective methods for estimating link reliability in a wireless mobile ad hoc network due to path loss effects, such as the Weibull distribution.
The evaluation metrics will include bandwidth, Signal to Interference plus Noise Ratio (SINR), coverage area, transmission range, number of nodes, and communication duration.
3
1.3 Aims and Objectives
This study uses the Weibull distribution to forecast connection dependability in a multi-hop wireless mobile ad-hoc network due to path loss. The objectives are as follows.
1. Create a Matlab Graphic User Interface (GUI)-based algorithm for prediction and simulation.
2. Running a wide range of simulations using the Matlab GUI-based programme to evaluate the impact of changes in network properties on connection dependability.
3. Evaluate and compare the network’s link reliability to existing research work.
1.4 Motivation and Justification.
MANETS’ unexpected dynamic nature causes poor network link reliability. Furthermore, environmental factors that induce link path loss have an impact not only on the network’s effectiveness and efficiency, but also on the links’ reliability.
The motivation of this research is to find solutions to these difficulties. Though many scholars have already worked on these difficulties to increase link reliability, there is still potential for improvement, which warrants this study effort, as evidenced by the contribution made.
1.5 Methodology.
The methods used in conducting this research is as follows:
1. Created a signal propagation model using Free Space (FS) and Two Rays to Ground (TRG) path-loss models;
4.
ii. Network reliability model; iii. Node mobility model based on Random Way Point Mobility (RWPM); iv.
Node reliability model utilising Weibull distribution; v.
TTR link reliability model based on the FS-TRG model.
2. Implementation of the proposed algorithm using Matlab GUI.
3. Simulating various network scenarios using Matlab’s GUI-based script 4. Validation of the generated model’s results using Padmavathy and Chaturvedi (2013).
Need help with a related project topic or New topic? Send Us Your Topic