Node Disjoint Multipath Routing Approach for Controlling Congestion in MANETs

Mobile Ad hoc Networks are highly dynamic networks. Quality of Service (QoS) routing in such networks is usually limited by the network breakage due to either node mobility or energy depletion of the mobile nodes. Nodedisjoint routing becomes inessential technique in communication of packets among various nodes in networks. Meanwhile AODV (Ad Hoc On-demand Multipath Distance Vector) creates single-path route between a pair of source and destination nodes. Some researches has done so far to make multipath node-disjoint routing based on AODV protocol. But however their overhead and end-to-end delay are relatively high, while the detail of their code is not available too. In an ad hoc network, identification of all node-disjoint paths between a given pair of nodes is a challenging task. The phenomena that a protocol is not able to identify all node-disjoint paths that exist between a given pair of nodes is called path diminution. In this paper, we discuss that path diminution is unavoidable when a protocol discovers multiple node-disjoint paths in a single route discovery and working of node disjoint multipath protocol

An Improvement in Congestion Control Using Multipath Routing in Manet

The ad hoc connections, which opens many opportunities for MANET applications. In ad hoc network nodes are movable and there is no centralised management. Routing is an important factor in mobile ad hoc network which not only works well with a small network, but also it can also work well if network get expanded dynamically. Routing in Manets is a main factor considered among all the issues. Mobile nodes in Manet have limited transmission capacity, they intercommunicate by multi hop relay. Multi hop routing have many challenges such as limited wireless bandwidth, low device power, dynamically changing network topology, and high vulnerability to Failure. To answer those challenges, many routing algorithms in Manets were proposed. But one of the problems in routing algorithm is congestion which decreases the overall performance of the network so in this paper we are trying to identify the best routing algorithm which will improve the congestion control mechanism among all the Multipath routing protocols

An Efficient Technique for mining Association rules using Enhanced Apriori Algorithm A Literature survey

At present Data mining has a lot of e-Commerce applications. The key problem in this is how to find useful hidden patterns for better business applications in the retail sector. For the solution of those problems, The Apriori algorithm is the most popular data mining approach for finding frequent item sets from a transaction dataset and derives association rules. Association Rules are the discovered knowledge from the data base. Finding frequent item set (item sets with frequency larger than or equal to a user specified minimum support) is not trivial because of its combinatorial explosion. Once item sets are obtained, it is straightforward approach to generate association rules with confidence value larger than or equal to a user specified minimum confidence value. Apriori uses bottom up strategy. It is the most famous and classical algorithm for mining frequent patterns. Apriori algorithm works on categorical attributes. Apriori uses breadth first searc

An Efficient Technique for mining Association rules using Enhanced Apriori Algorithm

There are Various mining algorithms of association rules. One of the most popular algorithm is Apriori that extracts frequent itemset from large database and getting the association rule for discovering the knowledge. this paper pitfalls the limitation of the original Apriori algorithm for wasting time for scanning the whole database searching on to the frequent itemsets, and presents an technique on Apriori by reducing that wasted time depending on scanning only some transactions whose support value is bigger than 25% of minimum Support is taken as frequent item set and is added to the frequent item sets and then rules are formed. An enhanced Apriori algorithm may find the tendency of a customer on the basis of frequently purchased item-sets The proposed algorithm is useful as a frequent item sets predictor with lower number of scans. DOI: 10.17762/ijritcc2321-8169.15063