Vehicular adhoc networks are special form of Mobile adhoc networks which have more dynamic topology than MANETs but the nodes move in a preordered fashion. Due to the high mobility and complex dynamics in real vehiclular traffic flow, reliable streaming of data over Vehicular adhoc networks is a challenging task as compared to the other general mobile adhoc networks. This paper gives an overvie...

Mobile Adhoc Networks (MANET) is decentralized, self configuring, wireless network of mobile devices without using any infrastructure. MANET required dynamic routing to respond to the topological changes as nodes are dynamic in nature. Dynamic routing protocol such as Adhoc on demand distance vector routing (AODV) with Expanding Ring Search (ERS) is widely used technique to reduce energy consum...

Autoconfiguration of mobile nodes is an important issue on self-organizing mobile adhoc network. Autoconfiguration is needed to identify mobile nodes in the network uniquely. This is a critical problem to assign unique IP addresses to the mobile nodes when two or more than two independent adhoc networks merges to form a single network. Because when two independent mobile adhoc networks are merg...

In this paper, we present a new data mining algorithm which involves Data mining for multi moving nodes in a adhoc computing environment and quest the mining results to develop multichannel data allocation schemes so as to improve the overall performance of a adhoc system. First, we propose an algorithm to capture the frequent multichannel user moving nodes from a set of log data in a mobile(ad...

A number of experiments conducted within the framework of the TREC-6 conference and using a completely re-engineered version of the PArallel Document Retrieval Engine (PADRE97) are reported. Passage-based pseudo relevance feedback combined with a variant of City University's Okapi BM25 scoring function achieved best average precision, best recall and best precision@20 in the Long-topic Automati...

This paper introduces ADHOC, a tool that integrates statistical methods and machine learning techniques to perform effective feature selection. Feature selection plays a central role in the data analysis process since redundant and irrelevant features often degrade the performance of induction algorithms, both in speed and predictive accuracy. ADHOC combines the advantages of both filter and fe...