275 research outputs found

    Source Delay in Mobile Ad Hoc Networks

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    Source delay, the time a packet experiences in its source node, serves as a fundamental quantity for delay performance analysis in networks. However, the source delay performance in highly dynamic mobile ad hoc networks (MANETs) is still largely unknown by now. This paper studies the source delay in MANETs based on a general packet dispatching scheme with dispatch limit ff (PD-ff for short), where a same packet will be dispatched out up to ff times by its source node such that packet dispatching process can be flexibly controlled through a proper setting of ff. We first apply the Quasi-Birth-and-Death (QBD) theory to develop a theoretical framework to capture the complex packet dispatching process in PD-ff MANETs. With the help of the theoretical framework, we then derive the cumulative distribution function as well as mean and variance of the source delay in such networks. Finally, extensive simulation and theoretical results are provided to validate our source delay analysis and illustrate how source delay in MANETs are related to network parameters.Comment: 11page

    Optimisation of Mobile Communication Networks - OMCO NET

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    The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

    Implementation of CAVENET and its usage for performance evaluation of AODV, OLSR and DYMO protocols in vehicular networks

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    Vehicle Ad-hoc Network (VANET) is a kind of Mobile Ad-hoc Network (MANET) that establishes wireless connection between cars. In VANETs and MANETs, the topology of the network changes very often, therefore implementation of efficient routing protocols is very important problem. In MANETs, the Random Waypoint (RW) model is used as a simulation model for generating node mobility pattern. On the other hand, in VANETs, the mobility patterns of nodes is restricted along the roads, and is affected by the movement of neighbour nodes. In this paper, we present a simulation system for VANET called CAVENET (Cellular Automaton based VEhicular NETwork). In CAVENET, the mobility patterns of nodes are generated by an 1-dimensional cellular automata. We improved CAVENET and implemented some routing protocols. We investigated the performance of the implemented routing protocols by CAVENET. The simulation results have shown that DYMO protocol has better performance than AODV and OLSR protocols.Peer ReviewedPostprint (published version

    Anomaly Recognition in Wireless Ad-hoc Network by using Ant Colony Optimization and Deep Learning

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    As a result of lower initial investment, greater portability, and lower operational expenses, wireless networks are rapidly replacing their wired counterparts. The new technology that is on the rise is the Mobile Ad-Hoc Network (MANET), which operates without a fixed network infrastructure, can change its topology on the fly, and requires no centralised administration to manage its individual nodes. As a result, MANETs must focus on network efficiency and safety. It is crucial in MANET to pay attention to outliers that may affect QoS settings. Nonetheless, despite the numerous studies devoted to anomaly detection in MANET, security breaches and performance difficulties keep coming back. There is an increased need to provide strategies and approaches that help networks be more safe and robust due to the wide variety of security and performance challenges in MANET. This study presents outlier detection strategies for addressing security and performance challenges in MANET, with a special focus on network anomaly identification. The suggested work utilises a dynamic threshold and outlier detection to tackle the security and performance challenges in MANETs, taking into account metrics such as end-to-end delay, jitter, throughput, packet drop, and energy usage

    Review of Ad Hoc Networks scenarios and challenges in years 2015-2019

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    A Mobile Ad-hoc Network (MANET) protocol performance analysis depends on the type of simulation tools, mobility models, and metrics used. These parameters\u27 choice is crucial to researchers because it may produce an inaccurate result if it is not well chosen. The challenges researcher is facing are on the choice of these four parameters. Our survey shows an inclination to used Ad-hoc On-Demand Distance Vector routing (AODV) for performance comparison and enhancement of it by the researcher. Network simulation 2 (NS2) was the most selected tool, but we observe a decline in its utilization in recent years. Random Waypoint Mobility model (RWPM) was the most used mobility model. We have found a high percentage of the published article did not mention the mobility models use; this will make the result difficult for performance comparison with other works. Packet Delivery Ratio (PDR), End to End Delay (E2ED) were the most used metrics. Some authors have self-developed their simulation tools; the authors have also used new metrics and protocols to get a particular result based on their research objective. However, some criteria of choosing a protocol, metrics, mobility model, and simulation tool were not described, decreasing the credibility of their papers\u27 results. Improvement needs to be done in the Ad-hoc network in terms of benchmark, acceptable scenario parameters. This survey will give the best practice to be used and some recommendations to the Ad-hoc network community

    Design and Performance Analysis of Genetic Algorithms for Topology Control Problems

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    In this dissertation, we present a bio-inspired decentralized topology control mechanism, called force-based genetic algorithm (FGA), where a genetic algorithm (GA) is run by each autonomous mobile node to achieve a uniform spread of mobile nodes and to provide a fully connected network over an unknown area. We present a formal analysis of FGA in terms of convergence speed, uniformity at area coverage, and Lyapunov stability theorem. This dissertation emphasizes the use of mobile nodes to achieve a uniform distribution over an unknown terrain without a priori information and a central control unit. In contrast, each mobile node running our FGA has to make its own movement direction and speed decisions based on local neighborhood information, such as obstacles and the number of neighbors, without a centralized control unit or global knowledge. We have implemented simulation software in Java and developed four different testbeds to study the effectiveness of different GA-based topology control frameworks for network performance metrics including node density, speed, and the number of generations that GAs run. The stochastic behavior of FGA, like all GA-based approaches, makes it difficult to analyze its convergence speed. We built metrically transitive homogeneous and inhomogeneous Markov chain models to analyze the convergence of our FGA with respect to the communication ranges of mobile nodes and the total number of nodes in the system. The Dobrushin contraction coefficient of ergodicity is used for measuring convergence speed for homogeneous and inhomogeneous Markov chain models of our FGA. Furthermore, convergence characteristic analysis helps us to choose the nearoptimal values for communication range, the number of mobile nodes, and the mean node degree before sending autonomous mobile nodes to any mission. Our analytical and experimental results show that our FGA delivers promising results for uniform mobile node distribution over unknown terrains. Since our FGA adapts to local environment rapidly and does not require global network knowledge, it can be used as a real-time topology controller for commercial and military applications
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