42 research outputs found

    Performance Comparison of TR and FSRUWB System Using Particle Filter: Effects of Frequency, Data Rate, Multi-Path and Multi-Channel Communication

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    In this study, we introduced a novel scheme based on Transmitted References (TR) and Frequency Shifted Reference (FSR) for ultra-wideband (UWB) system. By taking into account tracking loop-based particle filtering together with a data collecting approach for single and multi-path channel situations, the suggested method is an enhanced model. Each particle's location is determined using this filtering technique, which is then utilised to calculate the timing inaccuracy and regulate the UWB system's timing pulse. Also, it can tackle the multimodal distribution of errors then effectively approximate the optimal solution. The data distribution is discretised via a number of particles that are weighted samples evolving concerning time duration. The simulation results show that, in terms of error rate, number of particles, and delay response, the recommended model of FSR-UWB with particle filter performs better than the TR-UWB with and without considering particle filter

    Energy Efficient Bandwidth Management in Wireless Sensor Network

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    A Review on OFDMA and MU-MIMO MAC Protocols for upcoming IEEE Standard 802.11ax

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    IEEE introduced a new standard IEEE 802.11ax for the next generation WLANs.As we know,the current throughput is very low because of the current Media Access Control(MAC) in present wireless area networks.So,the concept of Orthogonal Frequency Multiple Access(OFDMA) to facilitate multi user access is introduced.The main challenges of adopting OFDMA areoverhead reduction and synchronization.To meet these challenges this paper revised an OFDMA based OMAX protocol.And due to various various bandwidth consuming applications and devices today’s WLANs have become stressed and low at throughput.To handle this problem MU MIMO is used to improve the performance of WLANs.This paper surveys uplink/downlink mutli user MAC protocols for MIMO enabled devices.It also identifies the key requirements of MAC protocol design

    A survey on self-organized cluster-based wireless sensor network

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    Study on Wireless Sensor Network (WSN) has been expended enormously in recent years. Sensor nodes are deployed in harsh environment which is operated autonomously. Network formation of WSNs are of two types, namely flat network and cluster-based network. Cluster-based network has various advantages as compare to flat network such as, efficient topology management, energy efficiency, minimized delay, better network communication, etc. Another important feature of cluster-based network is self-organized network. Self-organized enables new nodes joining to increase the coverage of the network and existing nodes leaving the network as node have limited energy. In recent years the demand of self-organized network is tremendously increasing to overcome the problem of node joining and leaving which maintain the smooth data communication. Thus, this survey addresses latest research works regarding self-organized cluster-based network. Moreover, a unique performance matrix is also investigated in this article to measure the algorithms. Finally, open research issues are highlighted for self-organized clustering schemes that might be future line of action

    A Game-Theoretic Approach to Strategic Resource Allocation Mechanisms in Edge and Fog Computing

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    With the rapid growth of Internet of Things (IoT), cloud-centric application management raises questions related to quality of service for real-time applications. Fog and edge computing (FEC) provide a complement to the cloud by filling the gap between cloud and IoT. Resource management on multiple resources from distributed and administrative FEC nodes is a key challenge to ensure the quality of end-user’s experience. To improve resource utilisation and system performance, researchers have been proposed many fair allocation mechanisms for resource management. Dominant Resource Fairness (DRF), a resource allocation policy for multiple resource types, meets most of the required fair allocation characteristics. However, DRF is suitable for centralised resource allocation without considering the effects (or feedbacks) of large-scale distributed environments like multi-controller software defined networking (SDN). Nash bargaining from micro-economic theory or competitive equilibrium equal incomes (CEEI) are well suited to solving dynamic optimisation problems proposing to ‘proportionately’ share resources among distributed participants. Although CEEI’s decentralised policy guarantees load balancing for performance isolation, they are not faultproof for computation offloading. The thesis aims to propose a hybrid and fair allocation mechanism for rejuvenation of decentralised SDN controller deployment. We apply multi-agent reinforcement learning (MARL) with robustness against adversarial controllers to enable efficient priority scheduling for FEC. Motivated by software cybernetics and homeostasis, weighted DRF is generalised by applying the principles of feedback (positive or/and negative network effects) in reverse game theory (GT) to design hybrid scheduling schemes for joint multi-resource and multitask offloading/forwarding in FEC environments. In the first piece of study, monotonic scheduling for joint offloading at the federated edge is addressed by proposing truthful mechanism (algorithmic) to neutralise harmful negative and positive distributive bargain externalities respectively. The IP-DRF scheme is a MARL approach applying partition form game (PFG) to guarantee second-best Pareto optimality viii | P a g e (SBPO) in allocation of multi-resources from deterministic policy in both population and resource non-monotonicity settings. In the second study, we propose DFog-DRF scheme to address truthful fog scheduling with bottleneck fairness in fault-probable wireless hierarchical networks by applying constrained coalition formation (CCF) games to implement MARL. The multi-objective optimisation problem for fog throughput maximisation is solved via a constraint dimensionality reduction methodology using fairness constraints for efficient gateway and low-level controller’s placement. For evaluation, we develop an agent-based framework to implement fair allocation policies in distributed data centre environments. In empirical results, the deterministic policy of IP-DRF scheme provides SBPO and reduces the average execution and turnaround time by 19% and 11.52% as compared to the Nash bargaining or CEEI deterministic policy for 57,445 cloudlets in population non-monotonic settings. The processing cost of tasks shows significant improvement (6.89% and 9.03% for fixed and variable pricing) for the resource non-monotonic setting - using 38,000 cloudlets. The DFog-DRF scheme when benchmarked against asset fair (MIP) policy shows superior performance (less than 1% in time complexity) for up to 30 FEC nodes. Furthermore, empirical results using 210 mobiles and 420 applications prove the efficacy of our hybrid scheduling scheme for hierarchical clustering considering latency and network usage for throughput maximisation.Abubakar Tafawa Balewa University, Bauchi (Tetfund, Nigeria

    A Mixed-Integer Programming Approach for Jammer Placement Problems for Flow-Jamming Attacks on Wireless Communication Networks

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    In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks

    A Mixed-Integer Programming Approach for Jammer Placement Problems for Flow-Jamming Attacks on Wireless Communication Networks

    Get PDF
    In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks
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