530 research outputs found

    Effects of Data Replication on Data Exfiltration in Mobile Ad hoc Networks Utilizing Reactive Protocols

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    A swarm of autonomous UAVs can provide a significant amount of ISR data where current UAV assets may not be feasible or practical. As such, the availability of the data the resides in the swarm is a topic that will benefit from further investigation. This thesis examines the impact of le replication and swarm characteristics such as node mobility, swarm size, and churn rate on data availability utilizing reactive protocols. This document examines the most prominent factors affecting the networking of nodes in a MANET. Factors include network routing protocols and peer-to-peer le protocols. It compares and contrasts several open source network simulator environments. Experiment implementation is documented, covering design considerations, assumptions, and software implementation, as well as detailing constant, response and variable factors. Collected data is presented and the results show that in swarms of sizes of 30, 45, and 60 nodes, le replication improves data availability until network saturation is reached, with the most significant benefit gained after only one copy is made. Mobility, churn rate, and swarm density all influence the replication impact

    Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks

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    This article is posted here with permission of IEEE - Copyright @ 2010 IEEEIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile networks [mobile ad hoc networks (MANETs)], wireless sensor networks, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, i.e., the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. In this paper, we propose to use GAs with immigrants and memory schemes to solve the dynamic SP routing problem in MANETs. We consider MANETs as target systems because they represent new-generation wireless networks. The experimental results show that these immigrants and memory-based GAs can quickly adapt to environmental changes (i.e., the network topology changes) and produce high-quality solutions after each change.This work was supported by the Engineering and Physical Sciences Research Council of U.K. underGrant EP/E060722/

    Algorithms based on spider daddy long legs for finding the optimal route in securing mobile ad hoc networks

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    Mobile ad hoc networks (MANETs) are wireless networks that are subject to severe attacks, such as the black hole attack. One of the goals in the research is to find a method to prevent black hole attacks without decreasing network throughput or increasing routing overhead. The routing mechanism in define uses route requests (RREQs; for discovering routes) and route replies (RREPs; for receiving paths). However, this mechanism is vulnerable to attacks by malicious black hole nodes. The mechanism is developed to find the shortest secure path and to reduce overhead using the information that is available in the routing tables as an input to propose a more complex nature-inspired algorithm. The new method is called the Daddy Long-Legs Algorithm (PGO-DLLA), which modifies the standard AODV and optimizes the routing process. This method avoids dependency exclusively on the hop counts and destination sequence numbers (DSNs) that are exploited by malicious nodes in the standard AODV protocol. The experiment by performance metrics End-to-End delay and packet delivery ratio are compared in order to determine the best effort traffic. The results showed the PGO-DLLA improvement of the shortest and secure routing from black hole attack in MANET. In addition, the results indicate better performance than the related works algorithm with respect to all metrics excluding throughput which AntNet is best in routing when the pause time be more than 40 seconds. PGODLLA is able to improve the route discovery against the black hole attacks in AODV. Experiments in this thesis have shown that PGO-DLLA is able to reduce the normalized routing load, end-to-end delay, and packet loss and has a good throughput and packet delivery ratio when compared with the standard AODV protocol, BAODV protocol, and the current related protocols that enhance the routing security of the AODV protocols

    Cost Optimization Approach for MANET using Particle Swarm Optimization

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    This paper present the approach require to increase the QoS of MANET network using particle swarm optimization algorithm. To improve data communication between two nodes we propose an efficient algorithm for AODV protocol using PSO where instead of suppling all default parameter with default value of AODV protocol we try to provide selective parameters with optimum value so that overall requirement of control packet get decrease that in turn result in to increase quality of service parameters of MANET. For the enhancement of reliability and reduction of cost, node speed control mechanism is implemented using PSO, The given method which is use for simulation, reduces the overall loss of data and also make transmission effective. We have also tested the performance of network by changing data rates and the speed of the node

    Genetic algorithms with elitism-based immigrants for dynamic shortest path problem in mobile ad hoc networks

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    This article is posted here with permission from the IEEE - Copyright @ 2009 IEEEIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks (ANNs), genetic algorithms (GAs), particle swarm optimization (PSO), etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless sensor network (WSN), etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP problem turns out to be a dynamic optimization problem (DOP) in MANETs. In this paper, we propose to use elitism-based immigrants GA (EIGA) to solve the dynamic SP problem in MANETs. We consider MANETs as target systems because they represent new generation wireless networks. The experimental results show that the EIGA can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

    A Survey on the Application of Evolutionary Algorithms for Mobile Multihop Ad Hoc Network Optimization Problems

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    Evolutionary algorithms are metaheuristic algorithms that provide quasioptimal solutions in a reasonable time. They have been applied to many optimization problems in a high number of scientific areas. In this survey paper, we focus on the application of evolutionary algorithms to solve optimization problems related to a type of complex network likemobilemultihop ad hoc networks. Since its origin, mobile multihop ad hoc network has evolved causing new types of multihop networks to appear such as vehicular ad hoc networks and delay tolerant networks, leading to the solution of new issues and optimization problems. In this survey, we review the main work presented for each type of mobile multihop ad hoc network and we also present some innovative ideas and open challenges to guide further research in this topic

    An Energy Efficient and Cost Reduction based Hybridization Scheme for Mobile Ad-hoc Networks (MANET) over the Internet of Things (IoT)

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    Wireless networks are viewed as the best-used network and specifically Portable Specially Appointed Organizations (MANETs) have tracked down numerous applications for its information transmission progressively. The plan issues in this organization are to confine the utilization of energy while communicating data and give security to the hubs. Soa protocol needs to be energy efficient to avoid network failures. Thereby this paper brings an effective energy efficient to optimize LEAR and make it energy efficient. The energy-mindfulness element is added to the LEAR guiding convention in this work using the Binary Particle Swarm Optimization method (BPSO). The recommended method selects programmes taking into account course length in addition to the programme level of energy when predicting the future. To get good results, the steered challenge is first designed using LEAR. The next step is to choose a route that enhances the weighting capability of the study hours and programming power used.This MANET has been secured using the cryptographic method known as AES.According to experimental findings, the proposed hybrid version outperformed other cutting-edge models

    A Secure Group Communication Architecture for a Swarm of Autonomous Unmanned Aerial Vehicles

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    This thesis investigates the application of a secure group communication architecture to a swarm of autonomous unmanned aerial vehicles (UAVs). A multicast secure group communication architecture for the low earth orbit (LEO) satellite environment is evaluated to determine if it can be effectively adapted to a swarm of UAVs and provide secure, scalable, and efficient communications. The performance of the proposed security architecture is evaluated with two other commonly used architectures using a discrete event computer simulation developed using MatLab. Performance is evaluated in terms of the scalability and efficiency of the group key distribution and management scheme when the swarm size, swarm mobility, multicast group join and departure rates are varied. The metrics include the total keys distributed over the simulation period, the average number of times an individual UAV must rekey, the average bandwidth used to rekey the swarm, and the average percentage of battery consumed by a UAV to rekey over the simulation period. The proposed security architecture can successfully be applied to a swarm of autonomous UAVs using current technology. The proposed architecture is more efficient and scalable than the other tested and commonly-used architectures. Over all the tested configurations, the proposed architecture distributes 55.2 – 94.8% fewer keys, rekeys 59.0 - 94.9% less often per UAV, uses 55.2 - 87.9% less bandwidth to rekey, and reduces the battery consumption by 16.9 – 85.4%
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