Asian Himalayas International Conference on Internet 

About: Asian Himalayas International Conference on Internet is an academic conference. The conference publishes majorly in the area(s): Routing protocol & Quality of service. Over the lifetime, 170 publications have been published by the conference receiving 1334 citations.

Performance analysis of EXP/PF and M-LWDF in downlink 3GPP LTE system

Abstract: This paper investigates the performance of exponential/proportional fair (EXP/PF) and maximum-largest weighted delay first (M-LWDF) scheduling algorithms in the third generation partnership project long term evolution (3GPP LTE) providing packet-switched multimedia services It, then, identifies a suitable packet scheduling algorithm on a basis of their performance evaluation The performance evaluation is conducted in terms of system throughput, average real time (RT) and non-real time (NRT) throughput, packet loss for RT service and fairness for NRT service A video streaming traffic is used to model the RT service, while a web-browsing traffic is modelled for NRT service Simulation results show that at lower load M-LWDF algorithm provides better performance than EXP/PF while as the load increases the EXP/PF gives better performance

Emergence of payment systems in the age of electronic commerce: The state of art

Abstract: The emergence of e-commerce has created new financial needs that in many cases cannot be effectively fulfilled by the traditional payment systems. Recognizing this, virtually all interested parties are exploring various types of electronic payment system and issues surrounding electronic payment system and digital currency. Broadly electronic payment systems can be classified into four categories: Online Credit Card Payment System, Online Electronic Cash System, Electronic Cheque System and Smart Cards based Electronic Payment System. Each payment system has its advantages and disadvantages for the customers and merchants. These payment systems have numbers of requirements: e.g. security, acceptability, convenience, cost, anonymity, control, and traceability. Therefore, instead of focusing on the technological specifications of various electronic payment systems, the researcher have distinguished electronic payment systems based on what is being transmitted over the network; and analyze the difference of each electronic payment system by evaluating their requirements, characteristics and assess the applicability of each system.

Combat with Black hole attack in AODV routing protocol in MANET

Abstract: A mobile ad hoc network (MANET) is an autonomous network that consists of mobile nodes that communicate with each other over wireless links. In the absence of a fixed infrastructure, nodes have to cooperate in order to provide the necessary network functionality. One of the principal routing protocols used in Ad hoc networks is AODV (Ad hoc on demand Distance Vector) protocol. The security of the AODV protocol is threaded by a particular type of attack called ‘Black Hole’ attack. In this attack a malicious node advertises itself as having the shortest path to the destination node. To combat with black hole attack, it is proposed to wait and check the replies from all the neighboring nodes to find a safe route but this approach suffers from high delay. In this paper, an approach is proposed to combat the Black hole attack by using negotiation with neighbors who claim to have a route to destination. the Simulation's results show that the proposed protocol provides better security and also better performance in terms of packet delivery than the conventional AODV in the presence of Black holes with minimal additional delay and Overhead.

An efficient k-means algorithm integrated with Jaccard distance measure for document clustering

Abstract: Document Clustering is a widely studied problem in Text Categorization. It is the process of partitioning or grouping a given set of documents into disjoint clusters where documents in the same cluster are similar. K-means, one of the simplest unsupervised learning algorithms, solves the well known clustering problem following a simple and easy way to classify a given data set through a certain number of clusters (assume k clusters) fixed a priori. The main idea is to define k centroids, one for each cluster. This clustering algorithm uses an iterative procedure which converges to one of numerous local minima. We have found that these iterative techniques are especially sensitive to initial starting conditions of the centroid of each cluster and the more the distance among the cluster centroid the better the clustering performance. In simple K-means algorithm the way to initialize the centroid is not specified and one popular way to start is to randomly choose k points of the samples as k centroids but this process does not guarantee to choose the maximum dissimilar documents as the centroid point for k-cluster. In this paper we proposed a modified k-means algorithm which uses Jaccard distance measure for computing the most dissimilar k documents as centroids for k clusters. Our experimental results demonstrate that our proposed K-means algorithm with Jaccard distance measure for computing the centroid improves the clustering performance of the simple K-means algorithm.

Anomaly detection using Support Vector Machine classification with k-Medoids clustering

Abstract: Anomaly based Intrusion Detection System, in the recent years, has become more dependent on learning methods — specially on classifications schemes. To make the classification more accurate and effective, hybrid approaches of combining with clustering techniques are often introduced. In this paper, a better combination is proposed to address problems of the previously proposed hybrid approach of combining k-Means/k-Medoids clustering technique with Naive Bayes classification. In this new approach, the need of large samples by the previous approach is reduced by using Support Vector Machine while maintaining the high quality clustering of k-Medoids. Simulations have been carried out by using Kyoto2006+ data sets in order to evaluate performance, accuracy, detection rate and false positive rate of the classification scheme. Experiments and analyses show that the new approach is better in increasing the detection rate as well as in decreasing the false positive rate.