7 research outputs found

    Convergence of ICN and MEC for 5G:opportunities and challenges

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    Abstract Information-centric networking (ICN) builds on a content-centric network architecture to overcome the shortcomings of host-centric routing/operation and realize efficient pervasive and ubiquitous networking. Similarly, multi-access edge computing (MEC) is another key technology to fulfill the stringent requirements of 5G to offer anytime-anywhere connected services for massive numbers of devices with ultra-low delay and very large bandwidths. The amalgamation of the ICN paradigm with MEC opens up new opportunities as well some challenges to realize 5G vision and advance beyond 5G systems. The key motivation of this article is to discuss and elaborate the convergence of ICN and MEC for better future networks, and to identify the current standardization efforts. Moreover, the article renders the key use cases and identifies potential research directions with the coexistence of ICN and MEC

    The role of 5G for digital healthcare against COVID-19 pandemic:opportunities and challenges

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    Abstract COVID-19 pandemic caused a massive impact on healthcare, social life, and economies on a global scale. Apparently, technology has a vital role to enable ubiquitous and accessible digital health services in pandemic conditions as well as against “re-emergence” of COVID-19 disease in a post-pandemic era. Accordingly, 5G systems and 5G-enabled e-health solutions are paramount. This paper highlights methodologies to effectively utilize 5G for e-health use cases and its role to enable relevant digital services. It also provides a comprehensive discussion of the implementation issues, possible remedies and future research directions for 5G to alleviate the health challenges related to COVID-19

    Association of vaspin rs2236242 gene variants and circulating serum vaspin concentrations with coronary artery disease in a Turkish population.

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    Coronary artery disease (CAD) is the primary cause of death worldwide. Vaspin was a recently described adipokine, playing a protective role in many metabolic and cardiovascular diseases. This study aimed to assess the relation of serum vaspin levels and vaspin rs2236242 polymorphisms with CAD. The study included 105 healthy subjects and 105 CAD patients. Serum vaspin concentrations and vaspin rs2236242 polymorphisms were determined by enzyme-linked immunosorbent assay and polymerase chain reaction, respectively. There was a statistically significant difference between the genotypes of CAD patients (TT 26.7%, TA 71.4%, and AA 1.9%) and controls (TT 70.5%, TA 28.6%, and AA 1%;chi(2) = 40.3;df = 2;p = .000). The TA genotype increased the risk of CAD (odds ratio [OR] = 6.60; 95% confidence interval [CI] = 3.60-12.1;p = .000) as compared to the TT genotype. There was a statistically significant difference between the allelic distribution of CAD patients (T 62.4% and A 37.6%) and controls (T 84.8% and A 15.2%;chi(2) = 27.0;df = 1;p = .000). Those carrying the A allele had a higher risk of CAD compared to those with the T allele (OR = 3.35; 95% CI = 2.10-5.36;p = .000). The serum vaspin concentrations of the patients with TT, TA, and AA genotypes were 30.4 +/- 1.72, 28.4 +/- 2.89, and 36.4 +/- 6.38 pg/ml, respectively, and there was no significant difference between the serum vaspin levels and vaspin genotypes (p = .696). All of the above suggested that the vaspin rs2236242 polymorphism was associated with CAD in the Turkish population

    The fight against the COVID-19 pandemic with 5G technologies

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    Abstract The coronavirus disease (COVID-19) pandemic has affected the world in an unexpected manner. The human race is battling against the pandemic while schools, universities, industries, hospitals, and governments are seeking new methods and technologies to seamlessly continue their usual operations. In response, this article presents how 5G and Internet of Things (IoT) related technologies can be efficiently utilized and developed to fight against the COVID-19 pandemic. Several use-cases on how 5G and IoT can be enablers to provide innovative solutions in the areas of telehealth, contact tracing, education, retail and supply chains, e-government/ remote office/ information sharing, smart manufacturing and factory automation, e-tourism, and entertainment are presented along with their technical requirements and challenges. It is envisaged that the proposed solutions will be instrumental to facilitate the usual lifestyle, work, and other day-to-day activities of humans in the postpandemic world

    The role of blockchain in 6G:challenges, opportunities and research directions

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    Abstract The world is going through a fundamental transformation with the emergence of the intelligent information era. The key domains linked with human life such as healthcare, transport, entertainment, and smart cities are expected to elevate the quality of service with high-end user experience. Therefore, the telecommunication infrastructure has to meet unprecedented service level requirements such as ultra high data rates and traffic volume for the prominent future applications such as Virtual Reality (VR), holographic communications, and massive Machine Type Communications (mMTC). There are significant challenges identifiable in the communication context to match the envisaged demand surge. The blockchain and distributed ledger technology is one of the most disruptive technology enablers to address most of the current limitations and facilitate the functional standards of 6G. In this work, we explore the role of blockchain to address formidable challenges in 6G, future application opportunities and potential research directions

    Emerging directions for blockchainized 6G

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    Abstract The next generation of mobile networks, i.e., sixth generation (6G), is expected by 2030, with already burgeoning research efforts towards this goal. Along with various other candidate technologies, blockchain is envisioned to enable and enhance numerous key functionalities of 6G. Thus, the main objective of this paper is threefold: 1) to categorize the different aspects of 6G into four emerging directions that anticipate significant advancements leveraging blockchain, 2) to discuss the potential role of blockchainized 6G under each key emerging direction, 3) to expound on the technical challenges in blockchaining 6G along with possible solutions

    Integration of ICN and MEC in 5G and beyond networks:mutual benefits, use cases, challenges, standardization, and future research

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    Abstract Multi-access Edge Computing (MEC) is a novel edge computing paradigm that moves cloudbased processing and storage capabilities closer to mobile users by implementing server resources in the access nodes. MEC helps fulfill the stringent requirements of 5G and beyond networks to offer anytimeanywhere connectivity for many devices with ultra-low delay and huge bandwidths. Information-Centric Networking (ICN) is another prominent network technology that builds on a content-centric network architecture to overcome host-centric routing/operation shortcomings and to realize efficient pervasive and ubiquitous networking. It is envisaged to be employed in Future Internet including Beyond 5G (B5G) networks. The consolidation of ICN with MEC technology offers new opportunities to realize that vision and serve advanced use cases. However, various integration challenges are yet to be addressed to enable the wide-scale co-deployment of ICN with MEC in future networks. In this paper, we discuss and elaborate on ICN MEC integration to provide a comprehensive survey with a forward-looking perspective for B5G networks. In that regard, we deduce lessons learned from related works (for both 5G and B5G networks). We present ongoing standardization activities to highlight practical implications of such efforts. Moreover, we render key B5G use cases and highlight the role for ICN MEC integration for addressing their requirements. Finally, we layout research challenges and identify potential research directions. For this last contribution, we also provide a mapping of the latter to ICN integration challenges and use cases
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