474 research outputs found

    Maximize resource utilization based channel access model with presence of reactive jammer for underwater wireless sensor network

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    Underwater sensor networks (UWSNs) are vulnerable to jamming attacks. Especially, reactive jamming which emerged as a greatest security threat to UWSNs. Reactive jammer are difficult to be removed, defended and identified. Since reactive jammer can control and regulate (i.e., the duration of the jam signal) the probability of jamming for maintaining high vulnerability with low detection probability. The existing model are generally designed considering terrestrial wireless sensor networks (TWSNs). Further, these models are limited in their ability to detect jamming correctly, distinguish between the corrupted and uncorrupted parts of a packet, and be adaptive with the dynamic environment. Cooperative jamming model has presented in recent times to utilize resource efficiently. However, very limited work is carried out using cooperative jamming detection. For overcoming research challenges, this work present Maximize Resource Utilization based Channel Access (MRUCA). The MRUCA uses cross layer design for mitigating reactive jammer (i.e., MRUCA jointly optimizes the cooperative hopping probabilities and channel accessibility probabilities of authenticated sensor device). Along with channel, load capacity of authenticated sensor device is estimated to utilize (maximize) resource efficiently. Experiment outcome shows the proposed MRUCA model attain superior performance than state-of-art model in terms of packet transmission, BER and Detection rate

    Average Load Distance (ALD) radio communication model for wireless sensor networks

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    The lifetime of network is one of the most critical issues that have to be considered in the application of wireless sensor networks. The network nodes are battery powered and remain operational as long as they can transmit the sensed data to the processing (sink) node. The main energy consumption of sensor node can be attributed to the task of data transmission to sink node or cluster head. Hence, conserving energy in transmitting data shall maximize functional life of the wireless networks. In this paper we proposed a computationally efficient Average Load Distance (ALD) communication model for forwarding data from sensor to the cluster head. Experiment results indicate that the proposed model can be up to 88% more efficient over direct mode of communication, in respect of per-round maximum energy consumption. An application study shows that ALD can save up to 89% of wireless sensor networks operational cost when compared to direct mode transmission

    W-GUN: Whale Optimization for Energy and Delay centric Green Underwater Networks

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    Underwater Sensor Networks (UWSNs) has witnessed significant R&D attention in both academia and industries due to its growing application domain such as border security, freight via sea or river, natural petroleum production, etc. Considering the deep underwater oriented access constraints, energy centric communication for lifetime maximization of tiny sensor nodes in UWSNs is one of the key research themes in this domain. Existing literature on green UWSNs are majorly adapted from the existing techniques in traditional wireless sensor network without giving much attention to the realistic impact of underwater network environments resulting in degraded performance. Towards this end, this paper presents an adapted whale optimization algorithm-based energy and delay centric green UWSNs framework (W-GUN). It focuses on exploiting dynamic underwater network characteristics by effectively utilizing underwater whale centric optimization in relay node selection. Firstly, an underwater relay- node optimization model is mathematically derived focusing on whale and wolf optimization algorithms for incorporating realistic underwater characteristics. Secondly, the optimization model is used to develop an adapted whale and grey wolf optimization algorithm. Thirdly, a complete work-flow of the W-GUN framework is presented with the optimization flowchart. The comparative performance evaluation attests the benefits of the proposed framework as compared to the state-of-the-art techniques considering various metrics related to underwater network environments

    Data Gathering in UWA Sensor Networks : Practical Considerations and Lessons from Sea Trials

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    Underwater acoustic (UWA) network protocol design is a challenging task due to several factors, such as slow propagation of acoustic waves, low frequency bandwidth and high bit error and frame error rates often encountered in real UWA environments. In this paper, we consider the design of a robust and scalable data gathering protocol for UWA sensor networks (UASNs), focusing on practical considerations and lessons learnt from multiple lake and sea trials. A cross-layer protocol is presented that integrates a network discovery process, intelligent routing, scheduling via Transmit Delay Allocation MAC (TDA-MAC) and multi-node Automatic Repeat Request (ARQ), to facilitate reliable data gathering in practical UASN deployments. Furthermore, this paper presents the details of a novel experimental testbed and underwater sensor node prototype that were used for the trials reported in this study. Based on the results of the trials, important conclusions are drawn on the protocol features required to achieve reliable networked communication in realistic UWA environments. The insights gained from the trials are valuable both for further development of the proposed data gathering protocol, and for the wider UWA networking research community concerned with developing practical solutions for real-world UASN deployments

    An effective data-collection scheme with AUV path planning in underwater wireless sensor networks

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    Data collection in underwater wireless sensor networks (UWSNs) using autonomous underwater vehicles (AUVs) is a more robust solution than traditional approaches, instead of transmitting data from each node to a destination node. However, the design of delay-aware and energy-efficient path planning for AUVs is one of the most crucial problems in collecting data for UWSNs. To reduce network delay and increase network lifetime, we proposed a novel reliable AUV-based data-collection routing protocol for UWSNs. The proposed protocol employs a route planning mechanism to collect data using AUVs. The sink node directs AUVs for data collection from sensor nodes to reduce energy consumption. First, sensor nodes are organized into clusters for better scalability, and then, these clusters are arranged into groups to assign an AUV to each group. Second, the traveling path for each AUV is crafted based on the Markov decision process (MDP) for the reliable collection of data. The simulation results affirm the effectiveness and efficiency of the proposed technique in terms of throughput, energy efficiency, delay, and reliability. © 2022 Wahab Khan et al

    Self-Organizing and Scalable Routing Protocol (SOSRP) for Underwater Acoustic Sensor Networks

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    Las redes de sensores acústicas submarinas (UASN) han ganado mucha importancia en los últimos años: el 71% de la superficie de la Tierra está cubierta por océanos. La mayoría de ellos, aún no han sido explorados. Aplicaciones como prospección de yacimientos, prevención de desastres o recopilación de datos para estudios de biología marina se han convertido en el campo de interés para muchos investigadores. Sin embargo, las redes UASN tienen dos limitaciones: un medio muy agresivo (marino) y el uso de señales acústicas. Ello hace que las técnicas para redes de sensores inalámbricas (WSN) terrestres no sean aplicables. Tras realizar un recorrido por el estado del arte en protocolos para redes UASN, se propone en este TFM un protocolo de enrutamiento denominado "SOSRP", descentralizado y basado en tablas en cada nodo. Se usa como criterio para crear rutas una combinación del valor de saltos hasta el nodo recolector y la distancia. Las funciones previstas del protocolo abarcan: autoorganización de las rutas, tolerancia a fallos y detección de nodos aislados. Mediante la implementación en MATLAB de SOSRP así como de un modelo de propagación y energía apropiados para entorno marino, se obtienen resultados de rendimiento en distintos escenarios (variando nºextremo de paquetes, consumo de energía o longitud de rutas creadas (con y sin fallo). Los resultados obtenidos muestran una operación estable, fiable y adecuada para el despliegue y operación de los nodos en redes UASN

    Mobile Ad Hoc Networks

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    Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

    EFFICIENT DYNAMIC ADDRESSING BASED ROUTING FOR UNDERWATER WIRELESS SENSOR NETWORKS

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    This thesis presents a study about the problem of data gathering in the inhospitable underwater environment. Besides long propagation delays and high error probability, continuous node movement also makes it difficult to manage the routing information during the process of data forwarding. In order to overcome the problem of large propagation delays and unreliable link quality, many algorithms have been proposed and some of them provide good solutions for these issues, yet continuous node movements still need attention. Considering the node mobility as a challenging task, a distributed routing scheme called Hop-by-Hop Dynamic Addressing Based (H2- DAB) routing protocol is proposed where every node in the network will be assigned a routable address quickly and efficiently without any explicit configuration or any dimensional location information. According to our best knowledge, H2-DAB is first addressing based routing approach for underwater wireless sensor networks (UWSNs) and not only has it helped to choose the routing path faster but also efficiently enables a recovery procedure in case of smooth forwarding failure. The proposed scheme provides an option where nodes is able to communicate without any centralized infrastructure, and a mechanism furthermore is available where nodes can come and leave the network without having any serious effect on the rest of the network. Moreover, another serious issue in UWSNs is that acoustic links are subject to high transmission power with high channel impairments that result in higher error rates and temporary path losses, which accordingly restrict the efficiency of these networks. The limited resources have made it difficult to design a protocol which is capable of maximizing the reliability of these networks. For this purpose, a Two-Hop Acknowledgement (2H-ACK) reliability model where two copies of the same data packet are maintained in the network without extra burden on the available resources is proposed. Simulation results show that H2-DAB can easily manage during the quick routing changes where node movements are very frequent yet it requires little or no overhead to efficiently complete its tasks

    Mobile Ad Hoc Networks

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    Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

    Intelligent deployment strategies for passive underwater sensor networks

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    Passive underwater sensor networks are often used to monitor a general area of the ocean, a port or military installation, or to detect underwater vehicles near a high value unit at sea, such as a fuel ship or aircraft carrier. Deploying an underwater sensor network across a large area of interest (AOI), for military surveillance purposes, is a significant challenge due to the inherent difficulties posed by the underwater channel in terms of sensing and communications between sensors. Moreover, monetary constraints, arising from the high cost of these sensors and their deployment, limit the number of available sensors. As a result, sensor deployment must be done as efficiently as possible. The objective of this work is to develop a deployment strategy for passive underwater sensors in an area clearance scenario, where there is no apparent target for an adversary to gravitate towards, such as a ship or a port, while considering all factors pertinent to underwater sensor deployment. These factors include sensing range, communications range, monetary costs, link redundancy, range dependence, and probabilistic visitation. A complete treatment of the underwater sensor deployment problem is presented in this work from determining the purpose of the sensor field to physically deploying the sensors. Assuming a field designer is given a suboptimal number of sensors, they must be methodically allocated across an AOI. The Game Theory Field Design (GTFD) model, proposed in this work, is able to accomplish this task by evaluating the acoustic characteristics across the AOI and allocating sensors accordingly. Since GTFD considers only circular sensing coverage regions, an extension is proposed to consider irregularly shaped regions. Sensor deployment locations are planned using a proposed evolutionary approach, called the Underwater Sensor Deployment Evolutionary Algorithm, which utilizes two suitable network topologies, mesh and cluster. The effects of these topologies, and a sensor\u27s communications range, on the sensing capabilities of a sensor field, are also investigated. Lastly, the impact of deployment imprecision on the connectivity of an underwater sensor field, using a mesh topology, is analyzed, for cases where sensor locations after deployment do not exactly coincide with planned sensor locations
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