MEC-ConPaaS: An Experimental Single-Board Based Mobile Edge Cloud

Kempen, Alexandre van; Crivat, Teodor; Trubert, Benjamin; Roy, Debaditya; Pierre, Guillaume

doi:10.1109/mobilecloud.2017.17

Cited by 22 publications

(27 citation statements)

References 11 publications

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“…There are many ways to create an edge server; however, the implementation of single-board computers as edge clouds has been considered as an efficient and cost-effective solution. The increase in popularity of single-board computers (SBCs) (e.g., Raspberry Pi (RPi), Asus Tinker Board S, and Arduino Mega 2560) is due to their low cost, low energy, enough resource for various applications in not only education, but also in industry, hobbyists, prototype builders, and gamers [282], [283]. The availability of SBCs has introduced a new concept, disposable computing, such that SBCs are deployed as edge servers at any location where the edge service is not available or the current edge server is discarded and needs to be replaced by a new one.…”

Section: ) Single-board Computer Based Edge Cloudmentioning

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: ) Single-board Computer Based Edge Cloudmentioning

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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“…Much like cloud platforms, fog platforms rely on virtualization techniques to support multi-tenancy and increase resource utilization. For resource-efficiency reasons, most fog computing platforms rely on lightweight container technologies [8] rather than virtual machines, enabling one to envisage fog computing platforms making use of resources as limited as Raspberry Pis for example [9], [10].…”

Section: B State Of the Artmentioning

confidence: 99%

Proximity-Aware Traffic Routing in Distributed Fog Computing Platforms

Fahs¹,

Pierre²

2019

2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)

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Container orchestration engines such as Kubernetes do not take into account the geographical location of application replicas when deciding which replica should handle which request. This makes them ill-suited to act as a generalpurpose fog computing platforms where the proximity between end users and the replica serving them is essential. We present proxy-mity, a proximity-aware traffic routing system for distributed fog computing platforms. It seamlessly integrates in Kubernetes, and provides very simple control mechanisms to allow system administrators to address the necessary trade-off between reducing the user-to-replica latencies and balancing the load equally across replicas. proxy-mity is very lightweight and it can reduce average user-to-replica latencies by as much as 90% while allowing the system administrators to control the level of load imbalance in their system.

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“…As a matter of fact, one option which is being explored is to use single-board computers such as Raspberry PIs for this purpose. Despite their obvious hardware limitations, Raspberry PIs offer excellent performance/cost/energy ratios and are well-suited to scenarios where the device's physical size and energy consumption are important enablers for actual deployment [2,10].…”

Section: Introductionmentioning

confidence: 99%

Docker-pi: Docker container deployment in fog computing infrastructures

Ahmed

Pierre

2020

IJCC

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The transition from virtual machine-based infrastructures to containerbased ones brings the promise of swift and efficient software deployment in large-scale computing infrastructures. However, in fog computing environments which are often made of very small computers such as Raspberry PIs, deploying even a very simple Docker container may take multiple minutes. We demonstrate that Docker makes inefficient usage of the available hardware resources, essentially using different hardware subsystems (network bandwidth, CPU, disk I/O) sequentially rather than simultaneously. We therefore propose three optimizations which, once combined, reduce container deployment times by a factor up to 4. These optimizations also speed up deployment time by about 30% in datacenter-grade servers.

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MEC-ConPaaS: An Experimental Single-Board Based Mobile Edge Cloud

Cited by 22 publications

References 11 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

Proximity-Aware Traffic Routing in Distributed Fog Computing Platforms

Docker-pi: Docker container deployment in fog computing infrastructures

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