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OPPLOAD: Offloading Computational Workflows in Opportunistic Networks

Sterz, Artur and Baumgärtner, Lars and Höchst, Jonas and Lampe, Patrick and Freisleben, Bernd (2019):
OPPLOAD: Offloading Computational Workflows in Opportunistic Networks.
Osnabrück, Germany, In: 2019 IEEE 44th Conference on Local Computer Networks (LCN 2019), Osnabrück, Germany, [Conference or Workshop Item]

Abstract

Computation offloading is often used in mobile cloud computing, edge computing, and/or fog computing to cope with resource limitations of mobile devices in terms of computational power, storage, and energy. Computation offloading is particularly challenging in situations where network connectivity is periodic, intermittent, or error-prone. In this paper, we present OPPLOAD, a novel framework designed for offloading computational workflows in opportunistic networks that provide support for communication in such situations. The individual tasks forming a workflow can be assigned to particular remote execution platforms, called workers, either preselected ahead of time or decided just in time where a matching worker will automatically be assigned for the next task in the workflow. Workers announce their capabilities, i.e., tasks are only assigned to capable workers. Furthermore, tasks of a workflow can be executed on multiple workers that are automatically selected to balance the overall load. OPPLOAD also offers the ability to handle several types of error and exceptions appropriately. Our Python implementation of OPPLOAD, which uses the Serval Mesh to handle networking and routing, is publicly available as open source software. The results of our experimental evaluation demonstrate the feasibility of our approach.

Item Type: Conference or Workshop Item
Erschienen: 2019
Creators: Sterz, Artur and Baumgärtner, Lars and Höchst, Jonas and Lampe, Patrick and Freisleben, Bernd
Title: OPPLOAD: Offloading Computational Workflows in Opportunistic Networks
Language: English
Abstract:

Computation offloading is often used in mobile cloud computing, edge computing, and/or fog computing to cope with resource limitations of mobile devices in terms of computational power, storage, and energy. Computation offloading is particularly challenging in situations where network connectivity is periodic, intermittent, or error-prone. In this paper, we present OPPLOAD, a novel framework designed for offloading computational workflows in opportunistic networks that provide support for communication in such situations. The individual tasks forming a workflow can be assigned to particular remote execution platforms, called workers, either preselected ahead of time or decided just in time where a matching worker will automatically be assigned for the next task in the workflow. Workers announce their capabilities, i.e., tasks are only assigned to capable workers. Furthermore, tasks of a workflow can be executed on multiple workers that are automatically selected to balance the overall load. OPPLOAD also offers the ability to handle several types of error and exceptions appropriately. Our Python implementation of OPPLOAD, which uses the Serval Mesh to handle networking and routing, is publicly available as open source software. The results of our experimental evaluation demonstrate the feasibility of our approach.

Place of Publication: Osnabrück, Germany
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Multimedia Communications
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > A: Construction Methodology
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > A: Construction Methodology > Subproject A3: Migration
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms > Subproject B3: Economics of Adaption
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms > Subproject C5: Context-Centered Perspective
Event Title: 2019 IEEE 44th Conference on Local Computer Networks (LCN 2019)
Event Location: Osnabrück, Germany
Date Deposited: 26 Sep 2019 11:29
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