4,093 research outputs found

    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

    A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

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    Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks

    Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

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    Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

    Prospectiva de seguridad de las redes de sensores inalĂĄmbricos

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    En las Redes de Sensores InalĂĄmbricos (WSN), los nodos son vulnerables a los ataques de seguridad porque estĂĄn instalados en un entorno difĂ­cil, con energĂ­a y memoria limitadas, baja capacidad de procesamiento y transmisiĂłn de difusiĂłn media; por lo tanto, identificar las amenazas, los retos y las soluciones de seguridad y privacidad es un tema candente hoy en dĂ­a. En este artĂ­culo se analizan los trabajos de investigaciĂłn que se han realizado sobre los mecanismos de seguridad para la protecciĂłn de las WSN frente a amenazas y ataques, asĂ­ como las tendencias que surgen en otros paĂ­ses junto con futuras lĂ­neas de investigaciĂłn. Desde el punto de vista metodolĂłgico, este anĂĄlisis se muestra a travĂ©s de la visualizaciĂłn y estudio de trabajos indexados en bases de datos como IEEE, ACM, Scopus y Springer, con un rango de 7 años como ventana de observaciĂłn, desde 2013 hasta 2019. Se obtuvieron un total de 4.728 publicaciones, con un alto Ă­ndice de colaboraciĂłn entre China e India. La investigaciĂłn planteĂł desarrollos, como avances en los principios de seguridad y mecanismos de defensa, que han llevado al diseño de contramedidas en la detecciĂłn de intrusiones. Por Ășltimo, los resultados muestran el interĂ©s de la comunidad cientĂ­fica y empresarial por el uso de la inteligencia artificial y el aprendizaje automĂĄtico (ML) para optimizar las medidas de rendimiento.In Wireless Sensor Networks (WSN), nodes are vulnerable to security attacks because they are installed in a harsh environment with limited power and memory, low processing power, and medium broadcast transmission. Therefore, identifying threats, challenges, and solutions of security and privacy is a talking topic today. This article analyzes the research work that has been carried out on the security mechanisms for the protection of WSN against threats and attacks, as well as the trends that emerge in other countries combined with future research lines. From the methodological point of view, this analysis is shown through the visualization and study of works indexed in databases such as IEEE, ACM, Scopus, and Springer, with a range of 7 years as an observation window, from 2013 to 2019. A total of 4,728 publications were obtained, with a high rate of collaboration between China and India. The research raised developments, such as advances in security principles and defense mechanisms, which have led to the design of countermeasures in intrusion detection. Finally, the results show the interest of the scientific and business community in the use of artificial intelligence and machine learning (ML) to optimize performance measurements

    Smart Signs: Showing the way in Smart Surroundings

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    This paper presents a context-aware guidance and messaging system for large buildings and surrounding venues. Smart Signs are a new type of electronic door- and way-sign based on wireless sensor networks. Smart Signs present in-situ personalized guidance and messages, are ubiquitous, and easy to understand. They combine the easiness of use of traditional static signs with the flexibility and reactiveness of navigation systems. The Smart Signs system uses context information such as user’s mobility limitations, the weather, and possible emergency situations to improve guidance and messaging. Minimal infrastructure requirements and a simple deployment tool make it feasible to easily deploy a Smart Signs system on demand. An important design issue of the Smart Signs system is privacy: the system secures communication links, does not track users, allow almost complete anonymous use, and prevent the system to be used as a tool for spying on users

    Enhancing Security and Energy Efficiency in Wireless Sensor Network Routing with IOT Challenges: A Thorough Review

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    Wireless sensor networks (WSNs) have emerged as a crucial component in the field of networking due to their cost-effectiveness, efficiency, and compact size, making them invaluable for various applications. However, as the reliance on WSN-dependent applications continues to grow, these networks grapple with inherent limitations such as memory and computational constraints. Therefore, effective solutions require immediate attention, especially in the age of the Internet of Things (IoT), which largely relies on the effectiveness of WSNs. This study undertakes a comprehensive review of research conducted between 2018 and 2020, categorizing it into six main domains: 1) Providing an overview of WSN applications, management, and security considerations. 2) Focusing on routing and energy-saving techniques. 3) Reviewing the development of methods for information gathering, emphasizing data integrity and privacy. 4) Emphasizing connectivity and positioning techniques. 5) Examining studies that explore the integration of IoT technology into WSNs with an eye on secure data transmission. 6) Highlighting research efforts aimed at energy efficiency. The study addresses the motivation behind employing WSN applications in IoT technologies, as well as the challenges, obstructions, and solutions related to their application and development. It underscores that energy consumption remains a paramount issue in WSNs, with untapped potential for improving energy efficiency while ensuring robust security. Furthermore, it identifies existing approaches' weaknesses, rendering them inadequate for achieving energy-efficient routing in secure WSNs. This review sheds light on the critical challenges and opportunities in the field, contributing to a deeper understanding of WSNs and their role in secure IoT applications
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