Abstract
Edge computing has enabled a large set of emerging edge applications by exploiting data proximity and offloading computation-intensive workloads to nearby edge servers. However, supporting edge application users at scale poses challenges due to limited point-of-presence edge sites and constrained elasticity. In this paper, we introduce a densely-distributed edge resource model that leverages capacity-constrained volunteer edge nodes to support elastic computation offloading. Our model also enables the use of geo-distributed edge nodes to further support elasticity. Collectively, these features raise the issue of edge selection. We present a distributed edge selection approach that relies on client-centric views of available edge nodes to optimize average end-to-end latency, with considerations of system heterogeneity, resource contention and node churn. Elasticity is achieved by fine-grained performance probing, dynamic load balancing, and proactive multi-edge node connections per client. Evaluations are conducted in both real-world volunteer environments and emulated platforms to show how a common edge application, namely AR-based cognitive assistance, can benefit from our approach and deliver low-latency responses to distributed users at scale.
Original language | English (US) |
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Title of host publication | Proceedings - 2022 IEEE 42nd International Conference on Distributed Computing Systems, ICDCS 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 403-413 |
Number of pages | 11 |
ISBN (Electronic) | 9781665471770 |
DOIs | |
State | Published - 2022 |
Event | 42nd IEEE International Conference on Distributed Computing Systems, ICDCS 2022 - Bologna, Italy Duration: Jul 10 2022 → Jul 13 2022 |
Publication series
Name | Proceedings - International Conference on Distributed Computing Systems |
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Volume | 2022-July |
Conference
Conference | 42nd IEEE International Conference on Distributed Computing Systems, ICDCS 2022 |
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Country/Territory | Italy |
City | Bologna |
Period | 7/10/22 → 7/13/22 |
Bibliographical note
Funding Information:Acknowledgment. This work is supported in part by NSF grant CNS-1908566.
Publisher Copyright:
© 2022 IEEE.
Keywords
- edge computing
- edge elasticity
- heterogeneity
- volunteer computing