An ACO Algorithm for Effective Cluster Head Selection

This paper presents an effective algorithm for selecting cluster heads in mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc network consists of a cluster head and cluster members which are at one hop away from the cluster head. The cluster head allocates the resources to its cluster members. Clustering in MANET is done to reduce the communication overhead and thereby increase the network performance. A MANET can have many clusters in it. This paper presents an algorithm which is a combination of the four main clustering schemes- the ID based clustering, connectivity based, probability based and the weighted approach. An Ant colony optimization based approach is used to minimize the number of clusters in MANET. This can also be considered as a minimum dominating set problem in graph theory. The algorithm considers various parameters like the number of nodes, the transmission range etc. Experimental results show that the proposed algorithm is an effective methodology for finding out the minimum number of cluster heads.Comment: 7 pages, 5 figures, International Journal of Advances in Information Technology (JAIT); ISSN: 1798-2340; Academy Publishers, Finlan

An Overview of Mobile Ad Hoc Networks for the Existing Protocols and Applications

Mobile Ad Hoc Network (MANET) is a collection of two or more devices or nodes or terminals with wireless communications and networking capability that communicate with each other without the aid of any centralized administrator also the wireless nodes that can dynamically form a network to exchange information without using any existing fixed network infrastructure. And it's an autonomous system in which mobile hosts connected by wireless links are free to be dynamically and some time act as routers at the same time, and we discuss in this paper the distinct characteristics of traditional wired networks, including network configuration may change at any time, there is no direction or limit the movement and so on, and thus needed a new optional path Agreement (Routing Protocol) to identify nodes for these actions communicate with each other path, An ideal choice way the agreement should not only be able to find the right path, and the Ad Hoc Network must be able to adapt to changing network of this type at any time. and we talk in details in this paper all the information of Mobile Ad Hoc Network which include the History of ad hoc, wireless ad hoc, wireless mobile approaches and types of mobile ad Hoc networks, and then we present more than 13 types of the routing Ad Hoc Networks protocols have been proposed. In this paper, the more representative of routing protocols, analysis of individual characteristics and advantages and disadvantages to collate and compare, and present the all applications or the Possible Service of Ad Hoc Networks.Comment: 24 Pages, JGraph-Hoc Journa

F3TM: flooding factor based trust management framework for secure data transmission in MANETs

Due to the absence of infrastructure support, secure data dissemination is a challenging task in scalable mobile ad hoc networks (MANETs) environment. In most of the traditional routing techniques for MANETs, either security has not been taken into account or only one aspect of security concern has been addressed without optimizing the routing performance. This paper proposes Flooding Factor based Framework for Trust Management (F3TM) in MANETs. True flooding approach is utilized to identify attacker nodes based on the calculation of trust value. Route Discovery Algorithm is developed to discover an efficient and secure path for data forwarding using Experimental Grey Wolf algorithm for validating network nodes. Enhanced Multi-Swarm Optimization is used to optimize the identified delivery path. Simulations are carried out in ns2 to assess and compare the performance of F3TM with the state-of-the-art frameworks: CORMAN and PRIME considering the metrics including delay, packet delivery ration, overhead and throughput. The performance assessment attests the reliable security of F3TM compared to the state-of-the-art frameworks

Self-stabilizing cluster routing in Manet using link-cluster architecture

We design a self-stabilizing cluster routing algorithm based on the link-cluster architecture of wireless ad hoc networks. The network is divided into clusters. Each cluster has a single special node, called a clusterhead that contains the routing information about inter and intra-cluster communication. A cluster is comprised of all nodes that choose the corresponding clusterhead as their leader. The algorithm consists of two main tasks. First, the set of special nodes (clusterheads) is elected such that it models the link-cluster architecture: any node belongs to a single cluster, it is within two hops of the clusterhead, it knows the direct neighbor on the shortest path towards the clusterhead, and there exist no two adjacent clusterheads. Second, the routing tables are maintained by the clusterheads to store information about nodes both within and outside the cluster. There are two advantages of maintaining routing tables only in the clusterheads. First, as no two neighboring nodes are clusterheads (as per the link-cluster architecture), there is no need to check the consistency of the routing tables. Second, since all other nodes have significantly less work (they only forward messages), they use much less power than the clusterheads. Therefore, if a clusterhead runs out of power, a neighboring node (that is not a clusterhead) can accept the role of a clusterhead. (Abstract shortened by UMI.)

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

A Neighbor Coverage-Based Probabilistic Rebroadcast for Reducing Routing Overhead in Mobile Ad Hoc Networks Using Cluster Scheme

Due to high mobility of nodes in mobile ad hoc networks (MANETs), there exist frequent link breakages which lead to frequent path failures and route discoveries. The overhead of a route discovery cannot be neglected. In a route discovery, broadcasting is a fundamental and effective data dissemination mechanism, where a mobile node blindly rebroadcasts the first received route request packets unless it has a route to the destination, and thus it causes the broadcast storm problem. In this paper, we propose a neighbor coverage-based probabilistic rebroadcast protocol for reducing routing overhead in MANETs. In order to effectively exploit the neighbor coverage knowledge, we propose a novel rebroadcast delay to determine the rebroadcast order, and then we can obtain the more accurate additional coverage ratio by sensing neighbor coverage knowledge. We also define a connectivity factor to provide the node density adaptation. By combining the additional coverage ratio and connectivity factor, we set a reasonable rebroadcast probability. Our approach combines the advantages of the neighbor coverage knowledge and the probabilistic mechanism, which can significantly decrease the number of retransmissions so as to reduce the routing overhead, and can also improve the routing performance