Exploitation of Mobile Edge Computing in 5G Distributed Mission-Critical Push-to-Talk Service Deployment

Solozabal, Rubén; Sanchoyerto, Aitor; Atxutegi, Eneko; Blanco, Bego; Fajardo, José Oscar; Liberal, Fidel

doi:10.1109/access.2018.2849200

Cited by 27 publications

(11 citation statements)

References 13 publications

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“…In [10], Kim et al proposed an algorithm to shorten the time of the initial uplink transmission in order to reduce the control plane latency. In [11], Solozobal et al looked at using mobile edge computing to provide a flexible architecture in 5G networks where the user plane can be deployed closer to the users, thus improving performance. The proposed solution would also allow the network operator to deploy the control plane at the edge of the network to provide a standalone service if the evolved NodeB (eNodeB) is disconnected from the core network.…”

Section: Introductionmentioning

confidence: 99%

Access Time Analysis of MCPTT Off-Network Mode over LTE

Sun

Garey

Rouil

et al. 2019

Wireless Communications and Mobile Computing

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Public safety organizations around the world started migrating toward Long-Term Evolution (LTE) networks to support the increasing needs for video and data. To address the unique voice communication requirements of first responders, the 3rd Generation Partnership Project (3GPP) introduced new capabilities that aim at providing similar functionalities as the traditional Land Mobile Radio (LMR) systems, namely, Direct Mode communication and mission critical push-to-talk (MCPTT). Direct Mode communication, also called Proximity Services (ProSe), allows public safety users to communicate directly with each other regardless of the network status. MCPTT was the first mission critical service, and first application, standardized by 3GPP to provide both on- and off-network voice capability. Assessing the performance of those capabilities is critical to accelerate their deployment and adoption by first responders. In this study, we evaluate the performance of an off-network mode MCPTT device over ProSe by focusing on the access time, a measure of the delay incurred before a user can talk. We develop analytical models for various types of calls and verify the accuracy of the predicted access time using ns-3 simulations. We perform sensitivity analysis to show the validity of the models for various scenarios. Finally, we show how the models can be used to guide parameter configuration for both MCPTT and ProSe to optimize the performance.

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Section: Introductionmentioning

confidence: 99%

Access Time Analysis of MCPTT Off-Network Mode over LTE

Sun

Garey

Rouil

et al. 2019

Wireless Communications and Mobile Computing

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“…5) C5: Connectivity of the Mobile Edge Orchestrator (MEO) and the 5G Core Network A secure interface has to be defined for the MEO and 5G core network [104]. The control signals will be exchanged between the 5G core network and MEO via this interface.…”

Section: ) C2: Operation Support System (Oss)mentioning

confidence: 99%

Survey on Multi-Access Edge Computing Security and Privacy

Ranaweera

Jurcut

Liyanage

2021

IEEE Commun. Surv. Tutorials

233

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The European Telecommunications Standards Institute (ETSI) has introduced the paradigm of Multi-Access Edge Computing (MEC) to enable efficient and fast data processing in mobile networks. Among other technological requirements, security and privacy are significant factors in the realization of MEC deployments. In this paper, we analyse the security and privacy of the MEC system. We introduce a thorough investigation of the identification and the analysis of threat vectors in the ETSI standardized MEC architecture. Furthermore, we analyse the vulnerabilities leading to the identified threat vectors and propose potential security solutions to overcome these vulnerabilities. The privacy issues of MEC are also highlighted, and clear objectives for preserving privacy are defined. Finally, we present future directives to enhance the security and privacy of MEC services.

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“…In [76], a non-standalone (i.e., disconnected from the Internet) MEC-based architecture is presented for mission-critical public safety services in order to achieve the delay requirement (i.e., less than 1 ms (ideal) or 10 ms (maximum) of round trip time) of 5G. The proposed architecture achieves the objective of improving QoS (O.2) by providing local computation (R.2), local decision making (R.4), and local operation (R.5).…”

Section: B Mec Based Solutionsmentioning

confidence: 99%

Edge Computing in 5G: A Review

2019

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5G is the next generation cellular network that aspires to achieve substantial improvement on quality of service, such as higher throughput and lower latency. Edge computing is an emerging technology that enables the evolution to 5G by bringing cloud capabilities near to the end users (or user equipment, UEs) in order to overcome the intrinsic problems of the traditional cloud, such as high latency and the lack of security. In this paper, we establish a taxonomy of edge computing in 5G, which gives an overview of existing state-of-the-art solutions of edge computing in 5G on the basis of objectives, computational platforms, attributes, 5G functions, performance measures, and roles. We also present other important aspects, including the key requirements for its successful deployment in 5G and the applications of edge computing in 5G. Then, we explore, highlight, and categorize recent advancements in edge computing for 5G. By doing so, we reveal the salient features of different edge computing paradigms for 5G. Finally, open research issues are outlined.

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Exploitation of Mobile Edge Computing in 5G Distributed Mission-Critical Push-to-Talk Service Deployment

Cited by 27 publications

References 13 publications

Access Time Analysis of MCPTT Off-Network Mode over LTE

Access Time Analysis of MCPTT Off-Network Mode over LTE

Survey on Multi-Access Edge Computing Security and Privacy

Edge Computing in 5G: A Review

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