Standard

IoT resource-aware orchestration framework for edge computing. / Agrawal, Niket; Rellermeyer, Jan; Ding, Aaron Yi.

2019. 62-64 Abstract from 15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019, Orlando, United States.

Research output: Contribution to conferenceAbstractScientific

Harvard

Agrawal, N, Rellermeyer, J & Ding, AY 2019, 'IoT resource-aware orchestration framework for edge computing', 15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019, Orlando, United States, 9/12/19 - 12/12/19 pp. 62-64. https://doi.org/10.1145/3360468.3368179

APA

Agrawal, N., Rellermeyer, J., & Ding, A. Y. (2019). IoT resource-aware orchestration framework for edge computing. 62-64. Abstract from 15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019, Orlando, United States. https://doi.org/10.1145/3360468.3368179

Vancouver

Agrawal N, Rellermeyer J, Ding AY. IoT resource-aware orchestration framework for edge computing. 2019. Abstract from 15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019, Orlando, United States. https://doi.org/10.1145/3360468.3368179

Author

Agrawal, Niket ; Rellermeyer, Jan ; Ding, Aaron Yi. / IoT resource-aware orchestration framework for edge computing. Abstract from 15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019, Orlando, United States.3 p.

BibTeX

@conference{d2bf352d46fd41f582249785cf5d2fd0,
title = "IoT resource-aware orchestration framework for edge computing",
abstract = "Existing edge computing solutions in the Internet of Things (IoT) domain operate with the control plane residing in the cloud and edge as a slave that executes the workload deployed by the cloud. The growing diversity in the IoT applications requires the edge to be able to run multiple distinct workloads corresponding to the dedicated inputs it receives, each catering to a specific task. Achieving this with the current approach poses a limitation as the cloud lacks the local knowledge at the edge and sharing this knowledge regularly between the edge and the cloud will defeat the very purpose of edge computing, i.e., low latency, less network congestion and data privacy. To solve this problem, we propose an orchestration framework for edge computing that enables the edge to actively initiate and orchestrate the workloads on request by using the local knowledge available in the form of IoT resources at the edge.",
author = "Niket Agrawal and Jan Rellermeyer and Ding, {Aaron Yi}",
year = "2019",
month = dec,
day = "9",
doi = "10.1145/3360468.3368179",
language = "English",
pages = "62--64",
note = "15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019 ; Conference date: 09-12-2019 Through 12-12-2019",

}

RIS

TY - CONF

T1 - IoT resource-aware orchestration framework for edge computing

AU - Agrawal, Niket

AU - Rellermeyer, Jan

AU - Ding, Aaron Yi

PY - 2019/12/9

Y1 - 2019/12/9

N2 - Existing edge computing solutions in the Internet of Things (IoT) domain operate with the control plane residing in the cloud and edge as a slave that executes the workload deployed by the cloud. The growing diversity in the IoT applications requires the edge to be able to run multiple distinct workloads corresponding to the dedicated inputs it receives, each catering to a specific task. Achieving this with the current approach poses a limitation as the cloud lacks the local knowledge at the edge and sharing this knowledge regularly between the edge and the cloud will defeat the very purpose of edge computing, i.e., low latency, less network congestion and data privacy. To solve this problem, we propose an orchestration framework for edge computing that enables the edge to actively initiate and orchestrate the workloads on request by using the local knowledge available in the form of IoT resources at the edge.

AB - Existing edge computing solutions in the Internet of Things (IoT) domain operate with the control plane residing in the cloud and edge as a slave that executes the workload deployed by the cloud. The growing diversity in the IoT applications requires the edge to be able to run multiple distinct workloads corresponding to the dedicated inputs it receives, each catering to a specific task. Achieving this with the current approach poses a limitation as the cloud lacks the local knowledge at the edge and sharing this knowledge regularly between the edge and the cloud will defeat the very purpose of edge computing, i.e., low latency, less network congestion and data privacy. To solve this problem, we propose an orchestration framework for edge computing that enables the edge to actively initiate and orchestrate the workloads on request by using the local knowledge available in the form of IoT resources at the edge.

UR - http://www.scopus.com/inward/record.url?scp=85077966392&partnerID=8YFLogxK

U2 - 10.1145/3360468.3368179

DO - 10.1145/3360468.3368179

M3 - Abstract

SP - 62

EP - 64

T2 - 15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019

Y2 - 9 December 2019 through 12 December 2019

ER -

ID: 68926803