Enabling Technologies to realise Smart Mall Concept in 5G Era

Raj, Dhanesh; Lekshmi, S; Guruprasad, J P; Urmila, M S; Lakshmi, T Aiswarya; Vinod, Athira; Anulakshmi,; Swathi, T V

doi:10.1109/iccic.2018.8782338

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…Through providing a virtualizationbased security and trust infrastructure, the system supports functions such as authentication, asset tagging, and secure storage. In [82], the authors used edge computing to address data traffic problems and reduce end-to-end latency in the smart mall scenario of smart cities. They also merged edge computing with the NFV technology, which can provide high bandwidth and low latency, enhance resource usage, and deploy automatic services.…”

Section: Edge Computingmentioning

confidence: 99%

Using 5G in Smart Cities: A Systematic Mapping Study

Chen¹,

Peng²,

Fu³

et al. 2022

Preprint

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5G is the fifth generation wireless network, with a set of characteristics, such as high bandwidth and data rates, massive connectivity, broad coverage, and low latency. The scenarios of using 5G include enhanced Mobile Broadband (eMBB), massive Machine Type Communications (mMTC), and ultra-Reliable and Low-Latency Communications (uRLLC). 5G is expected to support a wide variety of applications, such as city management, healthcare, transportation, agriculture, and energy management. In this paper, we conducted a systematic mapping study that covers the literature published between January 2012 and December 2019 regarding using 5G in smart cities. The scenarios, architecture, technologies, challenges, and lessons learned of using 5G in smart cities are summarized and further analyzed based on 32 selected studies, and the results are that: (1) The studies are distributed over 27 publication venues. 17 studies report results based on academic studies and 13 studies use demonstration or toy examples. Only 2 studies report using 5G in smart cities based on industrial studies. 16 studies include assumptions of 5G network design or smart city scenarios. (2) The most discussed smart city scenario is transportation, followed by public safety, healthcare, city tourism, entertainment, and education. (3) 28 studies propose and/or discuss the architecture of 5G-enabled smart cities, containing smart city architecture (treating 5G as a component), 5G network architecture in smart cities, and business architecture of using 5G in smart cities. (4) The most mentioned 5G-related technologies are radio access technologies, network slicing, and edge computing. (5) Challenges are mainly about complex context, challenging requirements, and network development of using 5G in smart cities. (6) Most of the lessons learned identified are benefits regarding 5G itself or the proposed 5G-related methods in smart cities. This work provides a reflection of the past eight years of the state of the art on using 5G in smart

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Section: Edge Computingmentioning

confidence: 99%

Using 5G in Smart Cities: A Systematic Mapping Study

Chen¹,

Peng²,

Fu³

et al. 2022

Preprint

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“…The processing of massive amounts of data from different sources requires a data optimizer (DO) at the edge. The current network configuration is a mixture of wireless technologies (cellular/non-cellular) [2] which is used to support various IoT applications. The diverse set of IoT devices streaming the data (measurements) to the servers in the network presents security challenges at the edge.…”

Section: Introductionmentioning

confidence: 99%

Data Optimization-Based Security Enhancement in 5G Edge Deployments

Lekshmi

Bandodkar

Vippalapalli

et al. 2021

Innovative Data Communication Technologies and Application

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Recently, edge computing and data analytics have been recognized as some of the key technologies to deliver low latency, high data rate services using the 5G networks. The 5G edge infrastructure is likely to cater to a mix of cellular and non-cellular devices mainly covering the Internet of things (IoT) and miniature sensor devices. The network vulnerability and threat mitigation at the edge become utmost important to protect the network from upstream attacks originating from the sensors. In mobile network deployments, the app data from multiple user devices can be collected at the mobile edge analytics server residing on the network side. These app data feeds can be processed at the edge server to dynamically build network quality maps. The quality analysis can be utilized to precisely monitor the experience of the users. Further, the serving cells or base stations serving those users within the edge can also be identified on the maps. This can help to pinpoint the real-time traffic variations per user in each cell. The user traffic trends, derived from the app-based quality analysis, can also help to identify security anomalies that may be taking place at the edge. In this paper, a novel framework to couple the traffic analysis and security monitoring at the mobile edge has been proposed with an example

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