Distributed Artificial Intelligence with Multi-Agent Systems for MEC

Leppänen, Teemu

doi:10.1109/icccn.2019.8846960

Cited by 9 publications

(6 citation statements)

References 28 publications

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“…Furthermore, MEC platforms will be offered and deployed by the network operator at any tiers of 5G networks, e.g., eNBs, multi-RAT aggregation points, neighbor mobile devices, which can be made open to authorised developers and content providers to deploy versatile and uninterrupted services on IoT applications [9]. In addition, based on the context and platforms of MEC, artificial intelligence (AI) on the edge can gain the huge benefit to realize distributed IoT applications and intelligent system management, which is now considered as a part of beyond 5G standardization [150]. Inversely, IoT also energizes MEC with mutual advantages.…”

Section: B Motivation To Use Mec For Iot and Challengesmentioning

confidence: 99%

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

et al. 2020

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Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research.

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Section: B Motivation To Use Mec For Iot and Challengesmentioning

confidence: 99%

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

et al. 2020

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“…In this Section, we instantiate the proposed development process for opportunistic MEC services on a simple yet effective Mobility Analysis Service (MECMMS), that was initially proposed in our earlier work in [40,41,42]. Indeed, a crucial component in mobile edge computing system is the mobility management system service(s) that collect data of user movement while connected to the system [3].…”

Section: Use Case: Mobility Analysis Servicementioning

confidence: 99%

“…The preconditions and constrains for MECMMS are that an instance is placed on each platform and that the microservice collective is deployed into the same platform for real-time content delivery in the close proximity of users. As described in [41], a set of MECMMS instances can be deployed as a hierarchy in the System, according to the capacity of Hosts, where additional preconditions are the microservice container size and adequate processing power. The service parameter, i.e.…”

Section: Mec Mobility Analysis Servicementioning

confidence: 99%

Service modeling for opportunistic edge computing systems with feature engineering

Leppänen

Savaglio

Fortino

2020

Computer Communications

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“…While the first three are operational approaches, aiming to support the service validation, verification and simulation, the last one provides high-level descriptive representations of both functional and non-functional properties of services. Further, software agent-based computing has been reported for the modeling and design of MEC and, in general, edge services in [9,10].…”

Section: B Service Modeling and Designmentioning

confidence: 99%

Edge-Based Microservices Architecture for Internet of Things: Mobility Analysis Case Study

Leppänen

Savaglio

Lovén

et al. 2019

2019 IEEE Global Communications Conference (GLOBECOM)

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In this paper, we describe how the microservices paradigm can be used to design and implement distributed edge services for Internet of Things applications. As a case study, traditionally monolithic user mobility analysis service is developed, with distributed and extendable microservices, for the standardized ETSI MEC system reference architecture. In each of the edge system three tiers, microservices implement the service logic with components for movement trace analysis, movement prediction and visualization of the results. The distributed service is implemented with Docker containers and evaluated on real-world settings with low capacity edge servers and real user mobility data. The results show that the edge promise of low latency can be met in such as implementation. The integration of a software development technology with a standardized edge system provides solid background for further development.

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Distributed Artificial Intelligence with Multi-Agent Systems for MEC

Cited by 9 publications

References 28 publications

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

Service modeling for opportunistic edge computing systems with feature engineering

Edge-Based Microservices Architecture for Internet of Things: Mobility Analysis Case Study

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