Enabling cyber‐physical communication in 5G cellular networks: challenges, spatial spectrum sensing, and cyber‐security

Atat, Rachad; Liu, Lingjia; Chen, Hao; Wu, Jinsong; Yi, Yang

doi:10.1049/iet-cps.2017.0010

Cited by 149 publications

(56 citation statements)

References 41 publications

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“…Major security feature(s) General attributes [79] Access control for legacy traffic OpenFlow extended with vertical forwarding [80] HIP (Host Identity Protocol) w/ location update OpenFlow with secure mobility support [74] HIP, IPSec, & SecGW for control channel Independent of OpenFlow, resilience against DoS, IP spoofing, eavesdropping, but not volume based DoS [68] Traffic monitoring Extension of [74] [69] Security layer over control layer for access control Local agents at wireless APs, high-level design [81] 3-level unified control for security, mobility, routing, etc. High-level idea only [82] Exploit channel characteristics Focused on D2D communication [83] NFVI-TP (NFV Infrstructure-Trust Platform) Framework for security and trust within NFV-MANO [84] Authenticated handover Low-latency and simple authentication via centralized controller [85] Authentication, access control, periodic key updates, 3 OpenFlow GWs for UE, RAN, & network routing conflict analyzer [82] addressed the computational limitations of small wireless devices by proposing a light-weight security framework for D2D communication. They define spatial transmission region for D2D link that can guarantee a minimum secrecy rate through exploiting the physical characteristics of the wireless channels.…”

Section: Proposalmentioning

confidence: 99%

Will SDN Be Part of 5G?

Zaidi¹,

Friderikos

Yousaf³

et al. 2018

IEEE Commun. Surv. Tutorials

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For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers towards the realization of a virtualized, flexible, programmable and flexible 5G network. As SDN along with other technology enablers (including NFV) are still in the process of evolution, the first commercial deployment of 5G may take few years. However, some companies are claiming the availability of 5G solutions, but considering the monumental task of softwarization of mobile cellular networks there are genuine concerns that we may only see some point solutions involving SDN technology instead of a fully virtualized SDN-enabled 5G mobile network. In order to determine the technology readiness of SDN solutions in the context of 5G networks, this survey paper attempts to identify all important obstacles in the way, and looks at the state of the art of the relevant research. This survey is different from the previous surveys on SDN-based mobile networks as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities that softwarization brings along to the mobile network. We have also provided a summary of the architectural developments in SDN-based mobile network landscape, including deployment options for SDN within NFV framework, as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDNbased mobile networks and clearly points out the gaps in the technology.

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Section: Proposalmentioning

confidence: 99%

Will SDN Be Part of 5G?

Zaidi¹,

Friderikos

Yousaf³

et al. 2018

IEEE Commun. Surv. Tutorials

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“…Furthermore, network-intensive data can be processed and analyzed just one hop away from end-devices, thereby reducing the bandwidth demands on network links to distant data centers. The ease of processing and storing data close to the devices generating them will enable new services [4][5][6][7]. Finally, edge computing platforms support mobility of devices and geographically distributed applications [3].…”

Section: Introductionmentioning

confidence: 99%

Edge Computing for the Internet of Things: A Case Study

Premsankar

Francesco

Taleb

2018

IEEE Internet Things J.

523

238

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The amount of data generated by sensors, actuators and other devices in the Internet of Things (IoT) has substantially increased in the last few years. IoT data are currently processed in the cloud, mostly through computing resources located in distant data centers. As a consequence, network bandwidth and communication latency become serious bottlenecks. This article advocates edge computing for emerging IoT applications that leverage sensor streams to augment interactive applications. First, we classify and survey current edge computing architectures and platforms, then describe key IoT application scenarios that benefit from edge computing. Second, we carry out an experimental evaluation of edge computing and its enabling technologies in a selected use case represented by mobile gaming. To this end, we consider a resource-intensive 3D application as a paradigmatic example and evaluate the response delay in different deployment scenarios. Our experimental results show that edge computing is necessary to meet the latency requirements of applications involving virtual and augmented reality. We conclude by discussing what can be achieved with current edge computing platforms and how emerging technologies will impact on the deployment of future IoT applications.

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“…To provide the advanced connectivity to CPS, 5G technology is considered as one of the most important, because it integrates entities, communications, and control technologies [4,5], as 5G supports enhanced mobile broadband communications, ultra-reliable and low-latency communications (URLLC), and massive machine-type communications (mMTC) [6,7]. In this environment, URLLC and mMTC in 5G are closely related to CPS.…”

Section: Introductionmentioning

confidence: 99%

A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks

Cortés-Polo¹,

Gil²,

González-Sánchez³

et al. 2020

Sensors

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Cyber-physical systems allow creating new applications and services which will bring people, data, processes, and things together. The network is the backbone that interconnects this new paradigm, especially 5G networks that will expand the coverage, reduce the latency, and enhance the data rate. In this sense, network analytics will increase the knowledge about the network and its interconnected devices, being a key feature especially with the increment in the number of physical things (sensors, actuators, smartphones, tablets, and so on). With this increment, the usage of online networking services and applications will grow, and network operators require to detect and analyze all issues related to the network. In this article, a methodology to analyze real network information provided by a network operator and acquire knowledge of the communications is presented. Various real data sets, provided by Telecom Italia, are analyzed to compare two different zones: one located in the urban area of Milan, Italy, and its surroundings, and the second in the province of Trento, Italy. These data sets describe different areas and shapes that cover a metropolitan area in the first case and a mainly rural area in the second case, which implies that these areas will have different comportments. To compare these comportments and group them in a single cluster set, a new technique is presented in this paper to establish a relationship between them and reduce those that could be similar.

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Enabling cyber‐physical communication in 5G cellular networks: challenges, spatial spectrum sensing, and cyber‐security

Cited by 149 publications

References 41 publications

Will SDN Be Part of 5G?

Will SDN Be Part of 5G?

Edge Computing for the Internet of Things: A Case Study

A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks

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