ECARDM: Energy Consumption Aware Route Discovery for Multicasting in Mobile Ad hoc Networks

Consideration of energy consumption in the case of wireless ad hoc networks leads to effective reduction of energy consumption by the nodes and increases the lifetime of the batteries for nodes. It is imperative from the existing models that there is significant scope for improvement in the energy-consumption based route discovery models. A model of Fuzzy based marginal energy disbursed multicast route discovery model for MANETs can support in reducing the power consumption has been proposed in our earlier research paper. In the present paper, a contemporary solution termed 201C;Energy Consumption Aware Route Discovery for Multicasting for MANETs201D; has been proposed, which is profoundly a fuzzy reasoning and genetic algorithm based model that focus on both the energy consumption and also the element of end-to-end delay whilst discovering the route. The experimental study of the model in comparison to BWDCMR and GAEEQMR models depicted that the proposed algorithm is very effective and can certainly be result oriented

An efficient Particle Swarm Optimization technique for identification of shortest path in Distributed Network

No Abstrac

Fast Converging Evolutionary Strategy for Multi-Constraint QoS Routing in Computer Networks Using New Decoding Mechanism

In recent years, real-time multimedia applications' demands such as Voice-on-IP (VoIP) and video conference are extremely increased which require QoS routing. This type of routing has been considered as an NP-Complete problem since it requires satisfying multiple constraints. Many solutions have been proposed to solve it, but most of them are complex and time consuming. In this paper, a novel multi-constraints QoS routing algorithm is proposed based on Evolutionary Strategies (ES). The algorithm preserves simplicity and offers a feasible solution in a few numbers of generations. This is due to a novel gene decoding mechanism that is used in the algorithm; and consequently more simple evolutionary operators can be applied. The simulation results show that our method outperforms previous algorithms in terms of speed and performance, so that it is 2.6 and 11.3 times faster, and its success ratio is also better

A Hybrid Algorithm for Improving the Quality of Service in MANET

A mobile ad-hoc network (MANET) exhibits a dynamic topology with flexible infrastructure. The MANET nodes may serve as both host and router functionalities. The routing feature of the MANET is a stand-alone multi-hop mobile network that can be utilized in many real-time applications. Therefore, identifying paths that ensure high Quality of Service (QoS), such as their topology and applications is a vital issue in MANET. A QoS-aware protocol in MANETs aims to find more efficient paths between the source and destination nodes of the network and, hence, the requirements of the QoS. This paper proposes a different hybrid algorithm that combines Cellular Automata (CA) with the African Buffalo Optimization (ABO), CAABO, to improve the QoS of MANETs. The CAABO optimizes the path selection in the ad-hoc on-demand distance vector (AODV) routing protocol. The test results show that with the aid of the CAABO, the AODV manifests energy and delay-aware routing protocol

Quality Of Service Enabled Cross-Layer Multicast Framework For Mobile Ad Hoc Networks.

Rangkaian ad hoc bergerak merupakan suatu rangkaian tanpa wayar yang boleh dibentuk secara bebas, dinamik serta disusunatur dan ditadbir dalam bentuk topologi rangkaian sementara dan arbitrari. Mobile ad hoc networks (MANETs) are wireless networks that can freely and dynamically be created, organized and administered into arbitrary and temporary network topologies

Energy Efficient Multicast Routing in Mobile Ad Hoc Networks: Contemporary Affirmation of Benchmarking Models in Recent Literature

The Mobile Ad hoc Networks playing critical role in network aided communication requirements The features such as ad hoc and open architecture based connectivity and node mobility are elevating the mobile ad hoc networks as much as feasible to deploy and use The direct communication between any of two nodes in this network is possible if target node is in the range of source node If not the indirect communication took place which is usually referred as multi hop routing The multi hop routing occurs as either a unicast model one source node to one destination node multicast model one source node to multiple destination nodes or multiple casting manifold unicast routing In these routing strategies provision of service quality in multi hop routing is a challenging task The optimal quality of service in routing magnifies the delivery ratio transmission rate network life span and other expected characteristics of the ad hoc routing Among the quality service provision factors minimal energy conservation is prime factor which is since the nodes involved in routing are self-energized and if discharged early then the route will be destructed that causes discontinued routing The energy consumption is more specific in multicast routing hence it is grabbing the more attention of the current research contribution

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems

This paper presents a new hybrid evolutionary algorithm to solve multi-objective multicast routing problems in telecommunication networks. The algorithm combines simulated annealing based strategies and a genetic local search, aiming at a more flexible and effective exploration and exploitation in the search space of the complex problem to find more non-dominated solutions in the Pareto Front. Due to the complex structure of the multicast tree, crossover and mutation operators have been specifically devised concerning the features and constraints in the problem. A new adaptive mutation probability based on simulated annealing is proposed in the hybrid algorithm to adaptively adjust the mutation rate according to the fitness of the new solution against the average quality of the current population during the evolution procedure. Two simulated annealing based search direction tuning strategies are applied to improve the efficiency and effectiveness of the hybrid evolutionary algorithm. Simulations have been carried out on some benchmark multi-objective multicast routing instances and a large amount of random networks with five real world objectives including cost, delay, link utilisations, average delay and delay variation in telecommunication networks. Experimental results demonstrate that both the simulated annealing based strategies and the genetic local search within the proposed multi-objective algorithm, compared with other multi-objective evolutionary algorithms, can efficiently identify high quality non-dominated solution set for multi-objective multicast routing problems and outperform other conventional multi-objective evolutionary algorithms in the literature