Based on Pause Time Comparative Analysis made among Bee-Ant Colony Optimized Routing (BACOR) Vs Existing Routing Protocols for Scalable Mobile Ad Hoc Networks (MANETs)

In this paper based on swarm intelligence a new approach for an on demand ad-hoc routing algorithm is proposed. The foraging behavior of Ant colony optimization and Bee colony optimization, which are the subset of swarm intelligence and considering the ability of simple ants to solve complex problems by cooperation. Several algorithms which are based on ant colony problems were introduced in the literatures to solve different problems, e.g., optimization problems. The proposed algorithm is compared and proven by results that the approach has the potential to become an appropriate routing tactics for mobile ad-hoc networks. The results were presented based on the simulations made with the implementation in ns-2. Keywords:BACOR, Bee Routing, Ant Routing, Bee-Ant Routin

Multiple Feasible Paths in Ant Colony Algorithm for mobile Ad-hoc Networks with Minimum Overhead

Mobile ad-hoc networks are infrastructure-less networks consisting of wireless, possibly mobile nodes which are organized in peer-to-peer and autonomous fashion. The highly dynamic topology, limited bandwidth availability and energy constraints make the routing problem a challenging one. Ant colony optimization (ACO) is a population based meta-heuristic for combinatorial optimization problems such as communication network routing problem. In real life, ants drop some kind of chemical substances to mark the path that they used. Then on their way, back they choose the path with the highest pheromones which becomes the shortest path. But Ant net Algorithms may cause the network congestion and stagnation. Here, multiple optimal paths are proposed with negligible overhead in spite of single optimal path in Ant net routing algorithm, so that the problem of stagnation can be rectified. This paper proposes an improved Multiple Feasible Paths in Ant Colony Algorithm for mobile Ad-hoc Networks with Minimum Overhead

Position based ant colony optimization routing in mobile ad hoc networks

Availability of cheap positioning instruments makes it possible for routing algorithms to use the advantage of knowing the positions of nodes in a mobile ad hoc network. Position based routing algorithms may fail to find a route from a source to a destination or the path that they find may be longer than the shortest path if the network contains nodes with irregular transmission ranges. On the other hand, routing algorithms which are based on ant colony optimization (ACO) find routing paths that are close in length to the shortest paths. The drawback of these algorithms is the large number of messages that needs to be sent or the long delay before the routes are established. In this thesis we propose two position based ACO routing algorithms for mobile ad hoc networks, POSANT and HYBNET. POSANT combines the idea of ant colony optimization with information about the position of nodes. HYBNET is a hybrid routing algorithm for mobile ad hoc networks which adapts itself to different network topologies. Our simulations show in most cases, POSANT and HYBNET perform better than the other routing algorithms

Secure and robust multi-constrained QoS aware routing algorithm for VANETs

Secure QoS routing algorithms are a fundamental part of wireless networks that aim to provide services with QoS and security guarantees. In Vehicular Ad hoc Networks (VANETs), vehicles perform routing functions, and at the same time act as end-systems thus routing control messages are transmitted unprotected over wireless channels. The QoS of the entire network could be degraded by an attack on the routing process, and manipulation of the routing control messages. In this paper, we propose a novel secure and reliable multi-constrained QoS aware routing algorithm for VANETs. We employ the Ant Colony Optimisation (ACO) technique to compute feasible routes in VANETs subject to multiple QoS constraints determined by the data traffic type. Moreover, we extend the VANET-oriented Evolving Graph (VoEG) model to perform plausibility checks on the exchanged routing control messages among vehicles. Simulation results show that the QoS can be guaranteed while applying security mechanisms to ensure a reliable and robust routing service

Solving the MANET Routing Problem using Ant Colony Algorithm

Mobile ad-hoc networks (MANETs) are a collection of mobile nodes communicating wirelessly without a centralized infrastructure. The biggest challenge in MANETs is to find a path between communicating nodes, that is, the MANET routing problem. The considerations of the MANET environment and the nature of the mobile nodes create further complications which results in the need to develop special routing algorithms to meet these challenges. Swarm Intelligence, a bio-inspired technique, which has proven to be very adaptable in other problem domains, has been applied to the MANET routing problem as it forms a good fit to the problem. In this thesis, a study of Ant Colony based routing algorithms is carried out taking into consideration two of the most popular algorithms Ant based algorithms, AntHocNet and the Ant Routing Algorithm (ARA). A thorough analyis of ARA is carried out based on the effect of its individual routing mechanisms on its routing efficacy. The original ARA algorithm, although finds the shortest path between source and destination, is observed to not be competitive against other MANET algorithms such as AODV in performance criteria. Based on the analysis performed, modifications are proposed to the ARA algorithm. Finally, a performance evaluation of the original ARA and the modified ARA is carried out with respect to each other, and with respect to AODV, a state of the art MANET routing algorithm vis-a-vis mobility criteria. The motivation behind the thesis is to realize application of MANETs in real world applications by solving the problem of routing

Modeling and simulation of routing protocol for ad hoc networks combining queuing network analysis and ANT colony algorithms

The field of Mobile Ad hoc Networks (MANETs) has gained an important part of the interest of researchers and become very popular in last few years. MANETs can operate without fixed infrastructure and can survive rapid changes in the network topology. They can be studied formally as graphs in which the set of edges varies in time. The main method for evaluating the performance of MANETs is simulation. Our thesis presents a new adaptive and dynamic routing algorithm for MANETs inspired by the Ant Colony Optimization (ACO) algorithms in combination with network delay analysis. Ant colony optimization algorithms have all been inspired by a specific foraging behavior of ant colonies which are able to find, if not the shortest, at least a very good path connecting the colony’s nest with a source of food. Our evaluation of MANETs is based on the evaluation of the mean End-to-End delay to send a packet from source to destination node through a MANET. We evaluated the mean End-to-End delay as one of the most important performance evaluation metrics in computer networks. Finally, we evaluate our proposed ant algorithm by a comparative study with respect to one of the famous On-Demand (reactive) routing protocols called Ad hoc On-Demand Distance Vector (AODV) protocol. The evaluation shows that, the ant algorithm provides a better performance by reducing the mean End-to-End delay than the AODV algorithm. We investigated various simulation scenarios with different node density and pause times. Our new algorithm gives good results under certain conditions such as, increasing the pause time and decreasing node density. The scenarios that are applied for evaluating our routing algorithm have the following assumptions: 2-D rectangular area, no obstacles, bi-directional links, fixed number of nodes operate for the whole simulation time and nodes movements are performed according to the Random Waypoint Mobility (RWM) or the Boundless Simulation Area Mobility (BSAM) model. KEYWORDS: Ant Colony Optimization (ACO), Mobile Ad hoc Network (MANET), Queuing Network Analysis, Routing Algorithms, Mobility Models, Hybrid Simulation

Performance Analysis of Swarm Intelligence-Based Routing Protocol for Mobile Ad Hoc Network and Wireless Mesh Networks

Ant colonies reside in social insect societies and maintain distributed systems that present a highly structured social organization despite of the simplicity of their individuals. Ants’ algorithm belongs to the Swarm Intelligence (SI), which is proposed to find the shortest path. Among various works inspired by ant colonies, the Ant Colony Optimization (ACO) metaheuristic algorithms are the most successful and popular, e.g., AntNet, Multiple Ant Colony Optimization (MACO) and AntHocNet. But there are several shortcomings including the freezing problem of the optimum path, traffic engineering, and to link failure due to nodes mobility in wireless mobile networks. The metaheuristic and distributed route discovery for data load management in Wireless Mesh Networks (WMNs) and Mobile Ad-hoc Network (MANET) are fundamental targets of this study. Also the main aim of this research is to solve the freezing problem during optimum as well as sub-optimum path discovery process. In this research, Intelligent AntNet based Routing Algorithm (IANRA) is presented for routing in WMNs and MANET to find optimum and near-optimum paths for data packet routing. In IANRA, a source node reactively sets up a path to a destination node at the beginning of each communication. This procedure uses ant-like agents to discover optimum and alternative paths. The fundamental point in IANRA is to find optimum and sub-optimum routes by the capability of breeding of ants. This ability is continuation of route that was produced by the parent ants. The new generations of ants inherit identifier of their family, the generation number, and the routing information that their parents get during their routing procedure. By this procedure, IANRA is able to prevent some of the existing difficulties in AntNet, MACO and Ad hoc On Demand Distance Vector (AODV) routing algorithms. OMNeT++ was used to simulate the IARNA algorithm for WMNs and MANET. The results show that the IANRA routing algorithm improved the data packet delivery ratio for both WMNs and MANET. Besides, it is able to decrease average end-to-end packet delay compared to other algorithms by showing its efficiency. IANRA has decreased average end-to-end packet delay by 31.16%, 58.20% and 48.40% in MANET scenario 52.86%, 64.52% and 62.86% by increasing packet generation rate in WMNs compared to AntHocNet, AODV and B-AntNet routing algorithms respectively with increased network load. On the other hand, IANRA shows the packet delivery ratio of 91.96% and 82.77% in MANET, 97.31% and 92.25% in WMNs for low (1 packet/s) and high (20 packet/s) data load respectively

Analysis Performance and Fairness (using Jain’s Index) of AODV and DSDV based on Ant Colony Optimization (ACO) in MANETs

Mobile Ad Hoc Networks (MANETs) are the collection of mobile nodes which can form randomly and dynamically without need preexisting network infrastructure that nodes can be arbitraly located and can move freely. The challenges research in MANETs routing is topology changes continuously. Its caused paths which initially efficient can quickly become inefficient or even infeasible. AODV and DSDV routing protocols have weaknesses for mobility network, which is often happens to drop a link. It caused source node should build routing again from scratch. So, for conditions simultant delivery of data will caused decreased dropped packets values, and resulting throughput values down. Some weakness in AODV and DSDV routing protocol, can be assisted to take advantage of the characteristics of the ant collony optimization. In this thesis, make a comparing AODV and DSDV fairness and performance using Ant Colony Optimazation in MANETs base on prevoius research. In our simulation result shown modification conventional routing protocols AODV and DSDV with the added Antnet Algorithm can affected to better performance. The throughput values increased about 6,367% - 13,02% for AODV and about 0,68% - 5,47% for DSDV. But mke a change delay time worst about 5.23% - 6,02% for AODV and 60.88% - 65.82% for DSDV. AODV routing protocols performance is still better than DSDV routing protocols even added Antnet Algorithm to them. Index Fairness AODV more fair then DSDV even added Antnet Algorithm. It shown at Index Fairness graphic, distributed Index Fairness about 1.00 for AODV which added Antnet Algorithms. Keyword : mobile ad-hoc networks (MANETs); throughput; delay time; routing overhead; Index Fairnes