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Cyber foraging techniques have been proposed in edge computing to support resource-intensive and latency-sensitive mobile applications. In a natural or man-made disaster scenario, all cyber foraging challenges are exacerbated by two problems: edge nodes are scarce and hence easily overloaded and failures are common due to the ad-hoc hostile conditions. In this paper, we study the use of efficient load profiling and migration strategies to mitigate such problems. In particular, we propose FORMICA, an architecture for cyber foraging orchestration, whose goal is to minimize the completion time of a set of jobs offloaded from mobile devices. Existing service offloading solutions are mainly concerned with outsourcing a job out of the mobile responsibility. Our architecture supports both mobile-based offloading and backend-driven onloading i.e., the offloading decision is taken by the edge infrastructure and not by the mobile node. FORMICA leverages Gelenbe networks to estimate the load profile of each node of the edge computing infrastructure to make proactive load profiling decisions. Our evaluation on a proof-of-concept implementation shows the benefits of our policy-based architecture in several (challenged disaster) scenarios but its applicability is broad to other IoT-based latency-sensitive applications.
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A Decomposition-based Architecture for Distributed Cyber-Foraging of Multiple Edge Functions
Edge computing is an emerging paradigm whose goal is to boost with cloud resources available at the edge the computational capability of otherwise weak devices. This paradigm is mostly attractive to reduce user perceived latency. A central mechanism in edge computing is cyber-foraging, i.e., the search and delegation to capable edge cloud processes of tasks too complex, time consuming or resource intensive to be running on user devices or low-latency demanding to be running remotely, as a form of edge function. An edge function is any network or device-specific process that may be run on an edge process instead. Despite the recent interest for this technology from industry and academia, cyber-foraging techniques and protocols have yet to be standardized. In this paper, we leverage decomposition theory to propose an architecture providing insights in the design and implementation of protocols for cyber-foraging of multiple edge functions. In contrast with several existing solutions, we argue that the (distributed) cyber-foraging orchestration should be policy-based and not an ad-hoc solution, i.e., either a pure edge cloud burden or a device decision. To this end, via simulations, we show how our approach can be used by edge computing providers and application programmers to compare and evaluate different alternative cyber-foraging solutions. Our decomposition-based approach has general applicability to other network utility maximization problems, even outside the edge computing domain.
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- Award ID(s):
- 1647084
- PAR ID:
- 10082118
- Date Published:
- Journal Name:
- 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft)
- Page Range / eLocation ID:
- 247 to 251
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/NETSOFT.2018.8459933
