Details
| Original language | English |
|---|---|
| Pages | 62-64 |
| Number of pages | 3 |
| Publication status | Published - 2019 |
| Externally published | Yes |
| Event | 15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019 - , United States Duration: 9 Dec 2019 → 12 Dec 2019 |
Conference
| Conference | 15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019 |
|---|---|
| Country/Territory | United States |
| Period | 9 Dec 2019 → 12 Dec 2019 |
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.
ASJC Scopus subject areas
- Engineering(all)
- Electrical and Electronic Engineering
- Computer Science(all)
- Hardware and Architecture
- Computer Science(all)
- Computer Networks and Communications
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2019. 62-64 Abstract from 15th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2019 - Part of CoNEXT 2019, United States.
Research output: Contribution to conference › Abstract › Research › peer review
}
TY - CONF
T1 - IoT resource-aware orchestration framework for edge computing
AU - Agrawal, Niket
AU - Rellermeyer, Jan
AU - Ding, Aaron
N1 - Publisher Copyright: © 2019 Association for Computing Machinery.
PY - 2019
Y1 - 2019
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 -