5G Multi-Access Edge Computing: Security, Dependability, and Performance Gianfranco Nencioni, Rosario G

Total Page:16

File Type:pdf, Size:1020Kb

5G Multi-Access Edge Computing: Security, Dependability, and Performance Gianfranco Nencioni, Rosario G ©2021 IEEE. This paper is under review at IEEE Communications Surveys & Tutorials. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,1 creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. 5G Multi-access Edge Computing: Security, Dependability, and Performance Gianfranco Nencioni, Rosario G. Garroppo, and Ruxandra F. Olimid Abstract—The main innovation of the Fifth Generation (5G) smartphones have already been produced and sold by many of mobile networks is the ability to provide novel services with manufacturers. Currently, mMTC is not under deployment new and stricter requirements. One of the technologies that since many network operators have deployed LTE-M and NB- enable the new 5G services is the Multi-access Edge Computing (MEC). MEC is a system composed of multiple devices with IoT in relatively recent times. URRLC is a usage scenario that computing and storage capabilities that are deployed at the edge is more immature and challenging, and it is attracting a lot of of the network, i.e., close to the end users. MEC reduces latency attention from the research community [2]. and enables contextual information and real-time awareness One of the technologies that enable 5G to provide URLLC of the local environment. MEC also allows cloud offloading services is the Multi-Access Edge Computing (MEC). MEC and the reduction of traffic congestion. Performance is not the only requirement that the new 5G services have. New mission- consists in the deployment of storage and computing platforms critical applications also require high security and dependability. at the edge of the (radio) access network. In this way, MEC These three aspects (security, dependability, and performance) is enabling the delivery of services with low latency but can are rarely addressed together. This survey fills this gap and also enable context awareness and task offloading. Moreover, presents 5G MEC by addressing all these three aspects. First, we MEC is also the enabler of the edge intelligence, which is overview the background knowledge on MEC by referring to the current standardization efforts. Second, we individually present anticipated to be one of the main innovations of the Sixth each aspect by introducing the related taxonomy (important for Generation (6G) of mobile networks [3]. the not expert on the aspect), the state of the art, and the MEC is the name given by the European Telecommunica- challenges on 5G MEC. Finally, we discuss the challenges of tions Standards Institute (ETSI) that has an Industry Spec- jointly addressing the three aspects. ification Group (ISG) [4] that is standardizing MEC since Index Terms—5G, MEC, Security, Dependability, Performance. 2014. Before 2017, MEC was standing for "Mobile Edge Computing", but ETSI decided to generalize the standard to other access technologies, not only 4G and 5G, but also fixed- access networks and Wireless Local Area Networks (WLAN). I. INTRODUCTION ETSI MEC is not the only standardization effort on edge The Fifth Generation (5G) of mobile networks is currently computing. Fog computing and cloudlet are the two main under deployment. The main innovation is the provision of alternatives. The cloudlet was proposed in 2009 [5] and can wireless connectivity for various usage scenarios [1]: en- be considered the first effort on edge computing. The cloudlet hanced Mobile Broadband (eMBB), for services with very consists of a micro-cloud close to the mobile device. Fog high data rate requirements (up to 20Gb/s); massive Machine- computing has been firstly proposed by Cisco in 2011. Since Type Communication (mMTC), developed for connecting a 2015, fog computing is promoted and standardized by the huge number of Internet-of-Things (IoT) devices (up to one OpenFog consortium [6]. Fog computing has been introduced million devices/km2); Ultra-Reliable Low-Latency Communi- as an extension of the cloud computing paradigm from the cation (URLLC), for services requiring high reliability and core to the edge of the network. Fog Computing consists arXiv:2107.13374v1 [cs.NI] 28 Jul 2021 very low latency (up to 1ms). eMBB allows improving the of a three-layer architecture where clouds, fog nodes, and services provided by the Fourth Generation (4G) of mobile IoT devices interact. There is also another technology called networks. mMTC enhances the services that are now pro- Mobile Cloud Computing (MCC), but it is not edge computing vided by Low-Power Wide Area Networks, such as Long- since it consists of offloading of tasks from the mobile users Term Evolution MTC (LTE-M) and Narrowband IoT (NB- to the cloud. This paper uses as reference the ETSI MEC, but IoT). URLLC enables innovative advanced services, such as many considerations can also be generalized for the other edge mission-critical applications, industrial automation, and en- computing solutions, and, in our study, works on alternative hanced Vehicular to Everything (V2X) such as platooning or edge computing are also included. remote driving. eMBB services are under deployment, and 5G As already mentioned, URLLC is the most innovative and challenging usage scenario for 5G and the one that requires This work was supported by the Norwegian Research Council through the MEC. To support URLLC, MEC has to cope with high 5G-MODaNeI project (no. 308909). G. Nencioni is with the University of Stavanger, 4021 Stavanger, Norway requirements of ultra reliability, which means security and (e-mail: [email protected]). dependability, and of low latency, which is a performance R. G. Garroppo is with the Univrsity of Pisa, 56126 Pisa, Italy (e-mail: indicator. This is one of the reasons for which security, [email protected]). R. F. Olimid is with the University of Bucharest, 030018 Bucharest, dependability, and performance are three critical aspects of Romania (e-mail: [email protected]). MEC. 2 If MEC security has been to some extent investigated TABLE I during the recent years and several surveys are available, LIST OF ACRONYMS fewer surveys are available on performance and even less on 5G Fifth Generation of mobile networks dependability. To the best knowledge of the authors, this is the BSS Business Support System first work that jointly investigates the security, dependability, CN Core Network and performance of 5G MEC. CFS Customer-Facing Service DNS Domain-Name System This paper has the following contributions: EM Element Management • State of the art and challenges on the security, depend- ETSI European Telecommunications Standards Institute GR Group Report (ETSI) ability, and performance of 5G MEC. Each aspect is GS Group Specification (ETSI) addressed individually by using a similar structure and LCM Life-Cycle Management content organization. MANO Management and Orchestration MEAO MEC Application Orchestrator – First, the taxonomy of the investigated aspect is intro- MEC Multi-access Edge Computing duced. In this way, experts on the other aspects can MEH MEC Host MEO MEC Orchestrator better understand the investigated aspect. MEP MEC Platform – Second, the state of the art is presented. The state MEPM MEC Platform Manager of the art is divided into standardization efforts and MEPM-V MEC Platform Manager - NFV NFV Network Function Virtualization academic publications. NFVI NFV Infrastructure – Finally, the challenges are presented and organized NFVO NFV Orchestrator according to the ETSI MEC architecture. OSS Operation Support System RAN Radio Access Network • Challenges in jointly addressing security, dependability, SDN Software-Defined Networking and performance in 5G MEC. The joint provision of these SST Slice/Service Type three aspects and the related trade-offs are analyzed and VIM Virtualization/Virtualized Infrastructure Manager VM Virtual Machine discussed. VNF Virtualized Network Function The next section introduces the necessary background con- VNFM VNF Manager cepts and definitions of 5G MEC. Sections III, IV, and V present the state of the art and the challenges of 5G MEC re- lated to security, dependability, and performance, respectively. Section VI discusses the challenges and trade-offs of jointly addressing security, dependability, and performance aspects. Finally, Section VII presents the conclusions. II. BACKGROUND In the ETSI specifications [7], MEC is defined as "sys- tem which provides an IT service environment and cloud- computing capabilities at the edge of the access network which contains one or more type of access technology, and in close proximity to its users". Before presenting the state of the art of MEC focusing on the three different aspects, the fundamental concepts of MEC and the related enabling technologies are presented. Table I lists the main acronyms that will be used in the rest Fig. 1. ETSI MEC Reference Architecture [8] of the paper. Most of the MEC acronyms are defined in [7], [8]. Note that what is currently defined as MEC was previously defined as Mobile Edge. For example, MEO was the acronym Machines (VMs) and can offer and consume MEC services. of Mobile Edge Orchestrator. The MEP is a collection of functionalities required to run the MEC applications. The MEP can also host MEC services. More information on MEC applications can be found in [9] A. ETSI MEC Architecture (development) and in [10] (enablement). A MEC system is defined as a collection of MEC Hosts The MEC host-level management is composed of the MEC (MEHs) and MEC management necessary to run MEC applica- Platform Manager (MEPM) and the Virtualization Infrastruc- tions [7]. Figure 1 illustrates the ETSI MEC general reference ture Manager (VIM). The MEPM manages MEC applications’ architecture, divided into two levels: the MEC host level and life cycle, rules, and requirements (e.g., required resources, the MEC system level [8]. latency), and provides element management functions to the 1) MEC host level [8]: A MEH contains a virtualization MEP.
Recommended publications
  • Mobile Edge Computing a Key Technology Towards 5G
    ETSI White Paper No. 11 Mobile Edge Computing A key technology towards 5G First edition – September 2015 ISBN No. 979-10-92620-08-5 Authors: Yun Chao Hu, Milan Patel, Dario Sabella, Nurit Sprecher and Valerie Young ETSI (European Telecommunications Standards Institute) 06921 Sophia Antipolis CEDEX, France Tel +33 4 92 94 42 00 [email protected] www.etsi.org About the authors Yun Chao Hu Contributor, Huawei, Vice Chair ETSI MEC ISG, Chair MEC IEG Working Group Milan Patel Contributor, Huawei Dario Sabella Contributor, Telecom Italia; Vice-Chair MEC IEG Working Group Nurit Sprecher Contributor, Nokia; Chair ETSI MEC ISG Valerie Young Contributor, Intel Mobile Edge Computing - a key technology towards 5G 2 Contents About the authors 2 Contents 3 Introduction 4 Market Drivers 5 Business Value 6 Mobile Edge Computing Service Scenarios 7 General 7 Augmented Reality 8 Intelligent Video Acceleration 9 Connected Cars 9 Internet of Things Gateway 11 Deployment Scenarios 11 ETSI Industry Specification Group on Mobile Edge Computing 12 Proofs of Concept 13 Conclusions 14 References 15 Mobile Edge Computing - a key technology towards 5G 3 Introduction Mobile Edge Computing (MEC) is a new technology which is currently being standardized in an ETSI Industry Specification Group (ISG) of the same name. Mobile Edge Computing provides an IT service environment and cloud-computing capabilities at the edge of the mobile network, within the Radio Access Network (RAN) and in close proximity to mobile subscribers. The aim is to reduce latency, ensure highly efficient network operation and service delivery, and offer an improved user experience. Mobile Edge Computing is a natural development in the evolution of mobile base stations and the convergence of IT and telecommunications networking.
    [Show full text]
  • Mobile Edge Computing: Architecture, Use-Cases, Applications Craig Pritchard, Yousef Beheshti, Mohammad Sepahi
    Mobile Edge Computing: Architecture, Use-cases, Applications Craig Pritchard, Yousef Beheshti, Mohammad Sepahi To cite this version: Craig Pritchard, Yousef Beheshti, Mohammad Sepahi. Mobile Edge Computing: Architecture, Use- cases, Applications. 2020. hal-02612631 HAL Id: hal-02612631 https://hal.archives-ouvertes.fr/hal-02612631 Preprint submitted on 19 May 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Mobile Edge Computing: Architecture, Use-cases, Applications Craig Pritchard, Yousef Beheshti, Mohammad Sepahi Abstract| By enormous growth in IoT and smart devices and the ad- vent of many new applications, Internet traffic volume has been grow- ing exponentially. Analyzing such flooding traffic requires enormous compute and bandwidth and raises privacy concerns. Edge platforms can become the tool to ease the burden by bringing resources to the proximity of data. Therefore, new architectures, which bring network functions and contents to the network edge, are proposed, i.e., mobile edge computing and caching. In this survey, we make an exhaustive review on the literature research efforts on mobile edge networks. We give an overview of mobile edge networks, including definition, archi- tecture, and application and use-cases . We then survey the issues related to computing, caching, and communication techniques at the network edge with the focus on applications and use cases of mobile edge networks.
    [Show full text]
  • 5G and Edge Computing
    Market Driven Strategic Advisory EMERGING AND DISRUPTIVE TECHNOLOGY ANALYSIS 5G and Edge Computing Impact on Business Models, Service Providers, Datacenters, Applications, Business Users and Consumers https://mindcommerce.com/ Copyright 2019 ©Mind Commerce +1 206-395-9205 Market Driven Strategic Advisory EMERGING AND DISRUPTIVE TECHNOLOGY ANALYSIS Highlights and Findings • 5G Influence on Bandwidth and Data Economics: 5G will “reinvent” connectivity as there will be a very credible alternative to cable and fiber for business customers. 5G will bring about fundamental structural economic changes, such as significantly lower broadband pricing as a whole, and also much greater flexibility for enterprise, industrial, and government market segments in terms of how they connect public to private networks. • 5G Needs Edge Computing: LTE is improved with edge computing, but 5G absolutely requires it. In fact, without mobile edge computing, 5G would need to rely upon back-haul to centralized cloud resource for storage and computing, diminishing much of the otherwise positive impact of latency reduction enabled by 5G. • Mobile Edge Computing a Must for Private Wireless Networks: Enterprise and industrial segments will continue to deploy private networks utilizing LTE and WiFi. Many of these networks will evolve to 5G and include edge computing to maximize overall throughput and minimize latency, which will be crucial for certain critical communications solutions such as industrial process automation. • Combined 5G and Edge Solutions: A variety of enhanced services and new apps will be enabled, many of which will be directly or indirectly involved with smart cities, intelligent buildings, and smart homes and workplaces. Key 5G and MEC supported applications for business will be IoT connectivity, SMB/corporate mobility, and fixed wireless.
    [Show full text]
  • Edge Computing for 5G Networks
    5G PPP Technology Board Edge Computing for 5G Networks 5GPPP Technology Board Working Group 5G-IA’s Trials Working Group Edge Computing for 5G Networks Version 1.0 Date: 29-01-2021 Version: 1.0 DOI 10.5281/zenodo.3698117 URL https://doi.org/10.5281/zenodo.3698117 Dissemination level: Public Page 1 / 96 5G PPP Technology Board Edge Computing for 5G Networks Table of Contents Executive Summary ........................................................................................................ 4 1. Introduction - Why Edge Computing is key for 5G and beyond............................ 6 1.1 What is Edge Computing ............................................................................... 6 1.2 Why is Edge Computing critical for 5G ....................................................... 7 1.3 Where is the Edge of the Network ................................................................ 9 1.4 How does the Edge look like? ...................................................................... 12 1.5 Introduction to the 5G Edge Cloud Ecosystem.......................................... 13 2. Key Technologies for 5G on Edge Computing ..................................................... 15 2.1 Resources Virtualization framework .......................................................... 15 2.1.1 Virtual Machines and Containerization ................................................................................... 15 2.1.2 Lightweight virtualization ......................................................................................................
    [Show full text]
  • The Role of Virtualization in the Small Cell Enabled Mobile Edge Computing Ecosystem
    The Role of Virtualization in the Small Cell Enabled Mobile Edge Computing Ecosystem Leonardo Goratti1, C.E. Costa1(&), Jordi Perez-Romero2, P.S. Khodashenas3, Alan Whitehead4, and Ioannis Chochliouros5 1 CREATE-NET, Via alla Cascata 56/D, Trento, Italy [email protected] 2 Universitat Politecnica de Catalunya (UPC), Barcelona, Spain 3 i2CAT, Barcelona, Spain 4 IP.Access, Cambourne, UK 5 Hellenic Telecommunications Organization (OTE), Marousi, Greece Abstract. Virtualisation is playing a fundamental role in the evolution of telecommunication services and infrastructures, bringing to rethink some of the traditional design paradigms of the mobile network and enabling those func- tionalities necessary for supporting new complex ecosystems where multiple actors can participate in a dynamic and secure environment. In Small Cell enabled Mobile Edge Computing deployments, the impact of virtualization technologies is significant in two main aspects: the design and deployment of the telecommuni- cation infrastructure, and the delivery of edge services. Besides, the adoption of virtualization technologies has implications also in the implementation of Self Organizing Network (SON) services and in the enforcement of Service Level Agreement (SLA) policies, both critical in the automation of the delivery of multi-tenant oriented services in such complex infrastructure. From the work performed by the H2020 SESAME project, the beneficial use of virtualization techniques emerges in adding network intelligence and services in the network edge. SESAME relays on virtualization for providing Small Cell as a Service (SCaaS) and per operator Edge Computing services, consolidating the emerging multi-tenancy driven design paradigms in communication infrastructures. Keywords: NFV Small Cell Virtualization 5G Á Á Á 1 Introduction Virtualization technologies decouple software from physical infrastructure, and create virtual resources dedicated to distinct services.
    [Show full text]
  • Mobile Edge Computing Versus Fog Computing in Internet of Vehicles
    Netware 2018 The Tenth International Conference on Advances In Future Internet AFIN 2018 Mobile Edge Computing versus Fog Computing in Internet of Vehicles Eugen Borcoci, Marius Vochin, Serban Obreja University POLITEHNICA of Bucharest [email protected] [email protected] [email protected] NETWARE 2018, September 16-20, Venice 1 Objectives • To identify general aspects related to • usage of the Edge computing technologies in the Internet of Vehicle (IoV) environment • Specific cases of technologies (which one to use in IoV?) • Multi-access (Mobile) Edge Computing • Fog Computing 222 NETWARE 2018, September 16-20, Venice Contents 1. Introduction 2. Edge computing architectures- examples 3. Relevant Internet of Vehicles architectures 4. MEC and Fog solutions integrated in IoV 5. MEC versus Fog in IoV 6. Conclusions 333 NETWARE 2018, September 16-20, Venice 1. Introduction . Vehicular networks evolve in Internet of Vehicles (IoV) - aiming to solve the current and novel challenging needs of transportation systems . Edge computing (EC) . move cloud computing capabilities close to the data sources/sinks . EC: distributed architectures, fast response, context awareness, minimization of the data transfer to the centralized data centers . EC- natural support for IoV . Multi-access (Mobile) Edge Computing (MEC), Fog Computing (FC), cloudlets, etc. – candidates to support IoV . These architectures and technologies have overlapping characteristics but also differences in approach . Today – open issues: . not yet a full convergence between EC technologies . which solution could be the best trade-off to be adopted in IoV context and for which use cases ? . This paper: . is not a complete survey . attempts a preliminary evaluation of some of the currently proposed MEC/Fog solutions for IoV 444 NETWARE 2018, September 16-20, Venice 1.
    [Show full text]
  • View on 5G Architecture
    5G PPP Architecture Working Group View on 5G Architecture Version 3.0, June 2019 Date: 2019-06-19 Version: 3.0 Dissemination level: Public Consultation Abstract The 5G Architecture Working Group as part of the 5G PPP Initiative is looking at capturing novel trends and key technological enablers for the realization of the 5G architecture. It also targets at presenting in a harmonized way the architectural concepts developed in various projects and initiatives (not limited to 5G PPP projects only) so as to provide a consolidated view on the technical directions for the architecture design in the 5G era. The first version of the white paper was released in July 2016, which captured novel trends and key technological enablers for the realization of the 5G architecture vision along with harmonized architectural concepts from 5G PPP Phase 1 projects and initiatives. Capitalizing on the architectural vision and framework set by the first version of the white paper, the Version 2.0 of the white paper was released in January 2018 and presented the latest findings and analyses of 5G PPP Phase I projects along with the concept evaluations. The work has continued with the 5G PPP Phase II and Phase III projects with special focus on understanding the requirements from vertical industries involved in the projects and then driving the required enhancements of the 5G Architecture able to meet their requirements. The results of the Working Group are now captured in this Version 3.0, which presents the consolidated European view on the architecture design. Dissemination level: Public Consultation Table of Contents 1 Introduction........................................................................................................................
    [Show full text]
  • Mobile Edge Computing Empowers Internet of Things
    IEICE TRANS. ??, VOL.Exx–??, NO.xx XXXX 200x 1 INVITED PAPER Mobile Edge Computing Empowers Internet of Things Nirwan ANSARIya) and Xiang SUNyb), SUMMARY In this paper, we propose a Mobile Edge Internet of Things lored for IoT devices is critical to empowering the current (MEIoT) architecture by leveraging the fiber-wireless access technology, IoT system. In addition, only providing interconnections to the cloudlet concept, and the software defined networking framework. The share raw data among IoT devices is not enough to gain the MEIoT architecture brings computing and storage resources close to Internet of Things (IoT) devices in order to speed up IoT data sharing and analytics. insight behind the big IoT data; the insight is more valuable Specifically, the IoT devices (belonging to the same user) are associated to for the society as a whole. Thus, it is beneficial to provision a specific proxy Virtual Machine (VM) in the nearby cloudlet. The proxy the IoT system with a comprehensive cognitive capability VM stores and analyzes the IoT data (generated by its IoT devices) in real- such that high-level knowledge can be extracted from the time. Moreover, we introduce the semantic and social IoT technology in the context of MEIoT to solve the interoperability and inefficient access big IoT raw data streams by applying various types of data control problem in the IoT system. In addition, we propose two dynamic mining and machine learning methods [3]. The data center proxy VM migration methods to minimize the end-to-end delay between infrastructure has been demonstrated to provision resources proxy VMs and their IoT devices and to minimize the total on-grid energy flexibly and efficiently [4]; meanwhile, various parallel com- consumption of the cloudlets, respectively.
    [Show full text]
  • Review and Analysis of Mobile Edge Computing and Fog from a Security and Resilience Perspective
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 1 The Extended Cloud: Review and Analysis of Mobile Edge Computing and Fog from a Security and Resilience Perspective Syed Noorulhassan Shirazi, Antonios Gouglidis, Arsham Farshad and David Hutchison (Invited Paper) Abstract—Mobile Edge Computing (MEC) and Fog are emerging computing models that extend the cloud and its services to the edge of the network. The emergence of both MEC and fog introduce new requirements, which mean their supported deployment models must be investigated. In this paper, we point out the influence and strong impact of the extended cloud (i.e., the MEC and fog) on existing communication and networking service models of the cloud. Although the relation between them is fairly evident, there are important properties, notably those of security and resilience, that we study in relation to the newly posed requirements from the MEC and fog. Although security and resilience have been already investigated in the context of the cloud - to a certain extent - existing solutions may not be applicable in the context of the extended cloud. Our approach includes the examination of models and architectures that underpin the extended cloud, and we provide a contemporary discussion on the most evident characteristics associated with them. We examine the technologies that implement these models and architectures, and analyse them with respect to security and resilience requirements. Furthermore, approaches to security and resilience-related mechanisms are examined in the cloud (specifically, anomaly detection and policy based resilience management), and we argue that these can also be applied in order to improve security and achieve resilience in the extended cloud environment.
    [Show full text]
  • A Comprehensive Overview of TCP Congestion Control in 5G Networks: Research Challenges and Future Perspectives
    sensors Review A Comprehensive Overview of TCP Congestion Control in 5G Networks: Research Challenges and Future Perspectives Josip Lorincz 1,* , Zvonimir Klarin 2 and Julije Ožegovi´c 1 1 Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (FESB), University of Split, 21 000 Split, Croatia; [email protected] 2 Polytechnic of Sibenik, Trg Andrije Hebranga 11, 22 000 Sibenik, Croatia; [email protected] * Correspondence: [email protected] Abstract: In today’s data networks, the main protocol used to ensure reliable communications is the transmission control protocol (TCP). The TCP performance is largely determined by the used congestion control (CC) algorithm. TCP CC algorithms have evolved over the past three decades and a large number of CC algorithm variations have been developed to accommodate various network environments. The fifth-generation (5G) mobile network presents a new challenge for the implemen- tation of the TCP CC mechanism, since networks will operate in environments with huge user device density and vast traffic flows. In contrast to the pre-5G networks that operate in the sub-6 GHz bands, the implementation of TCP CC algorithms in 5G mmWave communications will be further compro- mised with high variations in channel quality and susceptibility to blockages due to high penetration losses and atmospheric absorptions. These challenges will be particularly present in environments such as sensor networks and Internet of Things (IoT) applications. To alleviate these challenges, this paper provides an overview of the most popular single-flow and multy-flow TCP CC algorithms used in pre-5G networks. The related work on the previous examinations of TCP CC algorithm Citation: Lorincz, J.; Klarin, Z.; performance in 5G networks is further presented.
    [Show full text]
  • Survey on Intelligence Edge Computing in 6G: Characteristics, Challenges, Potential Use Cases, and Market Drivers
    future internet Review Survey on Intelligence Edge Computing in 6G: Characteristics, Challenges, Potential Use Cases, and Market Drivers Ahmed Al-Ansi 1, Abdullah M. Al-Ansi 2 , Ammar Muthanna 1,* , Ibrahim A. Elgendy 3,4,* and Andrey Koucheryavy 1 1 Department of Communication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications (SPBSUT), 193232 St. Petersburg, Russia; [email protected] (A.A.-A.); [email protected] (A.K.) 2 Faculty of Economic and Management, University of Muhammadiyah Yogyakarta, Yogyakarta 55183, Indonesia; [email protected] 3 School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China 4 Department of Computer Science, Faculty of Computers and Information, Menoufia University, Shibin el Kom 32511, Egypt * Correspondence: [email protected] (A.M.); [email protected] (I.A.E.) Abstract: Intelligence Edge Computing (IEC) is the key enabler of emerging 5G technologies net- works and beyond. IEC is considered to be a promising backbone of future services and wireless communication systems in 5G integration. In addition, IEC enables various use cases and applica- tions, including autonomous vehicles, augmented and virtual reality, big data analytic, and other customer-oriented services. Moreover, it is one of the 5G technologies that most enhanced market drivers in different fields such as customer service, healthcare, education methods, IoT in agriculture Citation: Al-Ansi, A.; Al-Ansi, A.M.; and energy sustainability. However, 5G technological improvements face many challenges such as Muthanna, A.; Elgendy, I.A.; traffic volume, privacy, security, digitization capabilities, and required latency. Therefore, 6G is con- Koucheryavy, A.
    [Show full text]
  • 5G Americas ICN / MEC December 2016 1 TABLE of CONTENTS
    5G Americas ICN / MEC December 2016 1 TABLE OF CONTENTS 1.0 Introduction ............................................................................................................................................. 4 2.0 Mobile Edge Computing .......................................................................................................................... 6 2.1 Description of the Technology ............................................................................................................. 6 2.2 How Edge Computing addresses the problems .................................................................................. 7 2.3 Example Use cases ............................................................................................................................. 7 2.3.1 IoT ................................................................................................................................................. 7 2.3.2 Video Distribution/Content Cache ................................................................................................. 8 2.3.3 Generic Compute Resource ......................................................................................................... 8 2.3.4 Edge Analytics .............................................................................................................................. 8 2.3.5 Cell level performance optimization use case .............................................................................. 9 2.3.6 Latency-sensitive Applications ...................................................................................................
    [Show full text]