Rafiq Ul Islam, Claudio Savaglio, Giancarlo Fortino
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引用次数: 0
Abstract
The increasing diffusion of Smart Environments enabled by the Internet of Things (IoT) technologies has evidenced the limitations of traditional Internet Protocol (IP), thus pushing for a paradigm shift from host-centric to Information-Centric Networking (ICN). The Named Data Networking (NDN) is a particular ICN implementation that prospects more efficient and effective communication and service provision, reason why it is widely considered as an enabler towards Future Internet. Driven by the PRISMA methodology, in this work we systematically survey the current literature and analyze opportunities and limitations of NDN adoption within Smart Environments, targeted application areas, adopted technologies and research gaps. In particular, by means of a research framework, we highlight how, by shifting from the traditional IP-based to NDN, Smart Environments can benefit from unseen degrees of mobility, scalability, security and performance, paving the way to innovative and cutting-edge cyberphysical services.
期刊介绍:
Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications.
Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration.
Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.