Survey on Intelligence Edge Computing in 6G: Characteristics, Challenges, Potential Use Cases, and Market Drivers
Abstract
:1. Introduction
- Providing an efficient interaction among network’s infrastructure and applications as well as supporting emerging technologies in the market that enable digital society in 2030 and after.
- Supporting convenient and effective binding for critical connectivity and edge computing networks which could be used by new poles with tighter limits as well as more varied limits for latency and amplitude.
- Controlling the resources effectively and rising time awareness and moving beyond the current effort of the Internet by providing high bandwidth and new case’s communication service.
1.1. IEC’s Principles
1.2. Paper Motivation and Contributions
- We conducted an overview of IEC in 6G including characteristics, benefits, challenges, new and open cases and applications and recent market drivers.
- We summarized integration of IEC in 5G networks related works from 2014 to 2021 including surveys, state of the art and future research.
- Furthermore, we discussed the key factors for network 6G including momentum, architecture and market.
- Finally, open research challenges and issues and new future direction in IEC with 6G network will be provided.
1.3. Paper Organization
2. Related Work
2.1. IEC’s State of Art
2.2. Development Framework
3. IEC’S Characteristics and Benefits
- Network performance: Cloud Edge has the ability to transfer 10× more performance throughput than competing alternatives: more than 200 Gbps on a single Intel Xeon server. Furthermore, linear scaling, independent aircraft, data monitoring and user management allow projects to support local communities to network resources quickly and efficiently scale on the edge of the network [50,51,52].
- Flexibility: Due to the actual use case and other related business, intelligence edge computing has flexibility to deploy a centralized or distributed solution. This flexibility is critical to economies of scale—the ability that Cloud Edge provides. For example, a CSP looking to provide multiple cloud services with low latency will benefit significantly by focusing control plane functionality (according to network proximity) but deploying user-level instances in a distributed manner either in the CSP or the customer edge.
- Divergent experiences: Cloud Edge enables CSP to deliver premium services to its customers on a per-flow basis. This is achieved with a single, integrated and highly optimized platform consisting of basic mobile network and LAN functions such as vProbe, CG-NAT, deep packet inspection (DPI), optimization and load balancing.
- Virtualization and analytics: cloud computing service providers look to complement the various service offerings in the related businesses. Intelligence edge computing has the ability to provide a real-time network and insight into customer behavior. For instance, IECs define operational efficiencies, anticipate future demand and deliver service innovation which is considered to be a core value-addition. Cloud Edge supports audit paths including security data audits and provides these capabilities, along with real-time analytics.
- Automation: In the inevitable decoupling of mobile networks, intelligence edge computing has the ability to automate the process of integrating enterprises, end-user services, applications and dynamically expanding network infrastructure, especially with IEC applications. Applications and tools of cloud edge automation enable cloud computing services to provide the ability to quickly adjust traffic rises and falls automatically which leads to reduce the operational costs and reduce the time needed to generate revenue.
4. IEC’s Challenges
- Network openness: major challenges are related to mobile networks edge openness, where mobile operators work to control over the entire industry chain, and business risks from each other among equipment suppliers.
- Multiple services and processes: Several types of third-party providers such as application developers, content providers, OTT operators, and network equipment vendors work with service type creation and IEC server cluster management. All participants have to face the challenge of new business models and the value chain.
- Durability and Resiliency: When integrating smart networks into a mobile base station, the robustness of the IEC server must be ensured and that the integration between them does not affect the availability of the mobile network.
- Privacy and Security: Integration of intelligence edge computing and other communication systems raise many challenges about the security and privacy of users and organizations. For instance, security threats of cyber-attacks with more of consideration about privacy protection when analyzing data of different users or parties.
- Data normalization, which is the assimilation, alignment, and enrichment of data from various sources (objects, devices, and sensors) into a common data model with well-understood connotations.
- Filter and query data, so apps and analytics can efficiently access and use related data.
- Integration with Edge Analytics Because the whole reason this data is captured is the ability to analyze it, create new actionable insights, make decisions, and put these decisions into action. Converting data into different representations and formats for integration with the (IoT) ecosystem.
- Compiling abstract data and/or metadata, as preparation for local analyzes or pushing them to cloud services [18].
5. Potential Use Cases and Applications
5.1. Customer-Oriented Services
5.2. Operator and Third-Party Services
- Autonomous vehicles: The autonomous platoon of truck convoys was one of the first use cases of autonomous vehicles [79,80,81,82]. So a group of trucks moves closer to each other in a group, which saves fuel costs and reduces congestion. With advanced computing, it is possible to remove the need for drivers in all trucks except for the front-end trucks, because the trucks will be able to communicate with each other with extremely low latency. In addition, automated vehicles are powerful enough to manage all kinds of on-board computing tasks and well-connected enough to interact with more than one network or device [83]. These robotic vehicles will be in constant contact with the world while making split-second decisions based on information from smart sensors.
- Industrial IoT: Actually, IoT devices and processes that included into this category are often referred to as the Industrial Internet of Things (IIoT). Safety is one of the fundamental issues that needs attention in the sector of Industry [84,85,86]. By using intelligence edge computing technologies and hardware it enables, safety levels could be improved and also provide analysts with real-time information about equipment, machines, tools and vehicles so that workers can work in a safe environment [87].
- Big Data Analytic: This case, by using a pool of cloud-based service for external vendors depending on the collection of massive information (such as video, sensor data, etc.) from different devices, where these data are being analyzed before being sent to the central servers. These applications could be run in a single location (i.e., on a single host), distributed over a specific region such as campus or for the entire network. To support the restrictions imposed on a party that is requesting third-party service, it is necessary to run in all required sites (IEC hosts) applications.
- Tracking of locations: the main use of such cases enable real-time, network-metric tracking of active terminal equipment (regardless of GPS) using “best-in-class” geolocation algorithms [1]. In addition, deployment in the IEC system provides an efficient and scalable solution with local processing. It also enables these services to businesses and consumers (for example, on primary adherence), or in retail venues, locations and in different coverage areas where GPS services are not capable [88].
5.3. Network Performance and QoE Improvement
6. IEC’s Market Drivers
6.1. Smart Environments
6.2. Autonomous Vehicles
6.3. Healthcare
6.4. Gaming, AR and VR
6.5. Smart Energy
7. IEC in 6G and Open Research Challenges in IEC with 6G Network
7.1. Emerging Technology and Business
7.2. 6G Network Momentum
- Connectivity: there is a lack of research to find proper connection among applications and networks such as network reliability, security of delivered data, level of awareness, and capacity.
- Holographic and multi-sense media: streaming of holographic media has a very large scale of transferring data per second. It is not a limited problem for end-user or bandwidth problem but more about the ability of the network to enable connection without any jitter which may decrease the behavior of interactive applications.
- Accuracy of services time: Most of the market segments aim to be operationally and mechanically independent, both of which are time-bound functions. Factory automation aims to eliminate wasted time, improve quality, and be cost-effective, relying heavily on every sensor, actuator, electronic physical system, and robot to perform with the pinpoint accuracy of a few milliseconds.
- Coexistence of Heterogeneous of Network Infrastructure: Networks in general, and not just on the edge, are becoming increasingly more affluent in terms of technology, ownership, and end-user engagement. It is very likely that there is not only one network, but several public Internet networks. As a result, 6G Networks will need more consideration in terms of internet environments (Table 2).
- Entertainment: tele-presence in entertainment refers to the adoption of new technologies such as robotics to experience feeling of being present even the person is in another location. For instance, conducting teleconference video-call in daily meetings where several people carry out their presence to the same location. Furthermore, holo-portation depends on augmented and virtual reality tele-presence in 3D where objects and people interact in 3D teleportation in real time. Additionally, multi-sense, holographic media and gaming have changed the face of entertainment by involving overlaying the physical environment with virtual elements. Holographic 3D-capture technology and its applications for holo-portation and media are completely transforming how we exist as social beings.
- Healthcare: Tele-surgery is about delivering a real-time healthcare service effectively and accuracy to a remote location depending on wireless channel. The use of telemedicine in pre-operative evaluation and diagnosis, post-operative evaluation and follow-up visits became increasingly significant. Patients reported benefits of using telemedicine such as avoiding unnecessary trips to hospitals, saving time and reducing the number of lost work days.
- Automotive: refers to self-propelled vehicles or machines. Automotive applications and technologies have a huge use in different industries including broadcasting, communication, computing, instrumentation, security, programming and networks. Situation response and time-awareness include devices that integrate with the vehicle, such as navigation systems and remote information systems, as well as those carried by drivers, such as cell phones, PDAs, etc., and they also include more advanced automation technologies, such as adaptive cruise control and lane-centering systems. Recently, automotive in vehicles has increased dramatically, with electronic control units (ECUs) communicating over increasingly complex and heterogeneous networks and presenting challenges in scalability, verification, and security.
- Education: in place presence or holographic in education refers to ability to use holographic representations in three-dimensional and life-size such as holographic video-conferencing. The HVC technology-enabled presenters to appear as 3D, life-size entities and to interact with the audience in real time. Monitors and holographic images were calibrated so that presenters were able to point to and achieve eye-contact with members of the audience. The adoption of HVC within higher education is at an early stage; however, there are significant efforts to ingrate these technologies in the near future.
- Industry: automation and time awareness in industrial sector refer to the use of control systems, such as computers or robots, and information technologies to deal with the various processes and mechanisms in an industries to replace the human being. It is the second step after mechanization in the manufacturing scale. Industrial automation is categorized into four types including fixed, programmable, flexible and integrated automation systems. The main goals of adopting automotive technologies are speeding up productivity, better use of resource, improve human safety and reducing mistakes.
7.3. 6G Network Market
- Unambiguous identification of traffic in the communication network, without introducing additional delays in the flow, in order to meet the requirements of communication networks with ultra-low delays.
- System online monitoring of a communication network from data flow, including virtual, to multi-parameter models of a network segment with many devices and systems.
- Short-term and long-term forecasting of the load both on network elements and on entire segments.
- Short-term and long-term prediction of the behavior of data streams at the data transfer level and service flows at the control level.
- Long-term forecasting of the load on the network and computing infrastructure, taking into account trends in traffic profiles, types of services, in order to determine and automatically generate proposals for reducing or expanding the network, as well as its threshold characteristics.
- Efficient allocation of 5G radio coverage with a prediction of cell load.
- Enhancing signal quality with predictive physical layer codecs.
- Short-term and long-term forecasting of user needs for certain services.
- Predicting the user’s movement geographically, as well as the formation of a model of his preferences in the content.
- Recognition and prediction of malicious attacks on the system with the formation of a proactive response to a possible attack.
- Application of AI technologies to consistently distribute services over the network on edge computing and fog computing frameworks.
- AI-based MEC system for integrating heterogeneous IoT technologies with 5G cellular system.
- Security-aware data offloading and resource allocation for edge computing systems.
8. Conclusions and Discussion
- Integration of IEC in 5G technologies enables sufficient and massive support for different services including IoT, smart environments, augmented and virtual reality, and sustainability of energy systems, vehicles connection, network performance, video games, economic services, education technology, ICT markets, and communication.
- IEC’s main characteristics and benefits include proximity of end-users, ultra-low latency, location awareness, integrated virtualization, super network performance, flexibility, real-time analytics, and automation.
- IEC’s current and up-to-date challenges include privacy and security, latency, distributed resource management, data traffic and bandwidth, heterogeneity, and scalability in addition to some issues related to network openness, multiple services and processes, data management, durability and resilience.
- IEC’s potential use cases and applications that have been investigated in this paper include three main categories as customer-oriented services, operator and third-party services, and network performance and QoE improvement. To enhance these categorizations, it is essential to integrate IEC in 5G technologies.
- IEC’s Market Drivers vary based on the different use and accessibility of 5G technologies in various sectors. We investigated five main sectors including smart environments, autonomous vehicles, healthcare, gaming in AR and VR and smart energy.
- Intelligence Edge Computing will have a significant role in 6G Network. Some of the examples and methods of using IEC in business have been discussed in addition to the architecture, momentum and market drivers of IEC in 6G Network.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Topic | Reference | Methods | Contributions |
---|---|---|---|
Intensive review of MEC, its characteristics and challenges | [18,19,22] | Surveys and Reviews | Overview of MEC technology and its potential use cases and applications. Determining IEC framework and performance and comprehensive overview of the state of arts, challenges, and further research directions for MEC. |
MEC Software and Applications | [28] | White Paper | Newly guidance for developers how to run and build the needed architect in edge cloud. |
MEC Vehicular Networks | [29] | Position Paper | MEC features in-premises and need for SDN and NFV in addition, mobility solutions and mitigation interface. |
MEC Game Theory | [30] | Survey | Applying game theory on MEC and Challenges over MEC services. |
Heterogeneous Networks MEC | [31] | A Novel Architecture | Architecture of MEC-empowered HetNets and offloading task in MEC-empowered UAV-assisted HetNets. |
MEC to support Enhanced (IoT) | [32] | Propose an architectural solution | Propose an ETSI-compliant MEC architecture solution that allows existing and future IoT platforms to be seamlessly integrated. |
MEC in 5G-connected cars | [33] | Automotive use cases | IPresenting automotive use cases relevant to MEC, providing insights into technologies identified and investigated by the ETSI MEC Group (ISG). |
Characteristics of MEC | [25,26] | Survey, Empirical study | Introducing MEC infrastructure to understand the characteristic and future deployment. |
SDN Management of MEC | [8] | Novel architecture Analysis | Introducing layback architecture to facilitate access to resources. Calculating function blocks with resource sharing between operators increases the revenue rate measurement by more than 25% compared to CRAN. |
5G Context-Awareness in MEC | [34] | Comprehensive system evaluation | A new, decentralized validation architecture is proposed based on Markov model. The numerical simulations showed that this approach is able to strike balance between MEC reliability and network operating cost. |
MEC Device-Enhanced | [17] | A survey | Surveying device-enhanced MEC and classifying: Sub-classifying MEC IEChanisms offloading and caching. |
Survey on MEC for IoT Realization | [27] | A survey | An overview of leveraging MEC technology to achieve IoT applications and synergies between them. Technical aspects of enabling MEC in the Internet of Things. |
MEC’s Market Drivers | [27,35,36,37] | Comprehensive system evaluation | MEC features in-premises and need for SDN and NFV in addition, mobility solutions and mitigation interface. |
Surveys on MEC | [21,22,23,24] | Different Surveys | MEC features in-premises and need for SDN and NFV in addition, mobility solutions and mitigation interface. |
Entertainment | Healthcare | Automotive | Education | Industry |
---|---|---|---|---|
Tele-Presence | Tele-Surgery | Coordinated | Coordinated | Autonomous |
Holo-portation | Tele-monitor | Situation Response | In-place Presence | Automation |
Multi-Sense | Tactile | Time Awareness | Holographic Media | Time Awareness |
Holographic Media | Haptics | Tactile | Haptic | Tactile |
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Al-Ansi, A.; Al-Ansi, A.M.; Muthanna, A.; Elgendy, I.A.; Koucheryavy, A. Survey on Intelligence Edge Computing in 6G: Characteristics, Challenges, Potential Use Cases, and Market Drivers. Future Internet 2021, 13, 118. https://doi.org/10.3390/fi13050118
Al-Ansi A, Al-Ansi AM, Muthanna A, Elgendy IA, Koucheryavy A. Survey on Intelligence Edge Computing in 6G: Characteristics, Challenges, Potential Use Cases, and Market Drivers. Future Internet. 2021; 13(5):118. https://doi.org/10.3390/fi13050118
Chicago/Turabian StyleAl-Ansi, Ahmed, Abdullah M. Al-Ansi, Ammar Muthanna, Ibrahim A. Elgendy, and Andrey Koucheryavy. 2021. "Survey on Intelligence Edge Computing in 6G: Characteristics, Challenges, Potential Use Cases, and Market Drivers" Future Internet 13, no. 5: 118. https://doi.org/10.3390/fi13050118
APA StyleAl-Ansi, A., Al-Ansi, A. M., Muthanna, A., Elgendy, I. A., & Koucheryavy, A. (2021). Survey on Intelligence Edge Computing in 6G: Characteristics, Challenges, Potential Use Cases, and Market Drivers. Future Internet, 13(5), 118. https://doi.org/10.3390/fi13050118