An Efficient Method For Multichannel Wireless Mesh Networks With Pulse Coupled Neural Network
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2012, Vol 3, Issue 1
Abstract
Multi cast communication is a key technology for wireless mesh networks. Multicast provides efficient data distribution among a group of nodes, Generally sensor networks and MANETs uses multicast algorithms which are designed to be energy efficient and to achieve optimal route discovery among mobile nodes whereas wireless mesh networks needs to maximize throughput. Here we propose two multicast algorithms: The Level Channel Assignment (LCA) algorithm and the Multi-Channel Multicast (MCM) algorithm to improve the throughput for multichannel sand multi interface mesh networks. The algorithm builds efficient multicast trees by minimizing the number of relay nodes and total hop count distance of the trees. Shortest path computation is a classical combinatorial optimization problem. Neural networks have been used for processing path optimization problem. Pulse Coupled Neural Networks (PCNNS) suffer from high computational cast for very long paths we propose a new PCNN modal called dual source PCNN (DSPCNN) which can improve the computational efficiency two auto waves are produced by DSPCNN one comes from source neuron and other from goal neuron when the auto waves from these two sources meet the DSPCNN stops and then the shortest path is found by backtracking the two auto waves.
Authors and Affiliations
S. Sobana, , S. Krishna Prabha
Customers Churn Prediction using Artificial Neural Networks (ANN) in Telecom Industry
To survive in the fierce competition of telecommunication industry and to retain the existing loyal customers, prediction of potential churn customer has become a crucial task for practitioners and academicians through p...
Evaluating the Quality of UCP-Based Framework using CK Metrics
Software effort estimation is one of the most important concerns in the software industry. It has received much attention since the last 40 years to improve the accuracy of effort estimate at early stages of software dev...
Conditional Text Paraphrasing: A Survey and Taxonomy
This work introduces a survey for the Text Para-phrasing task. The survey covers the different types of tasks around text paraphrasing and mentions the techniques and models that are regularly used when approaching towar...
User based Recommender Systems using Implicative Rating Measure
This paper proposes the implicative rating measure developed on the typicality measure. The paper also proposes a new recommendation model presenting the top N items to the active users. The proposed model is based on th...
Towards an Adaptive Learning System Based on a New Learning Object Granularity Approach
To achieve the adaptability required in ALS, adaptive learning system (ALS) takes advantage of granular and reusable content. The main goal of this paper is to examine the learning object granularity issue which is direc...