Offload (only) the right jobs: Robust offloading using the Markov decision processes

Esa Hyytia; Thrasyvoulos Spyropoulos; Jorg Ott

doi:10.1109/WoWMoM.2015.7158127

Offload (only) the right jobs: Robust offloading using the Markov decision processes

Esa Hyytia
, Thrasyvoulos Spyropoulos
, Jorg Ott

Helsinki University of Technology
Institut Eurecom

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

36 Scopus citations

Abstract

We consider a dynamic offloading problem arising in the context of mobile cloud computing (MCC). In MCC, three types of tasks can be identified: (i) those which can be processed only locally in a mobile device, (ii) those which are processed in the cloud, and (iii) those which can be processed either in the mobile or in the cloud. For type (iii) tasks, it is of interest to consider when they should be processed locally and when in the cloud. Furthermore, for both type (ii) and (iii) tasks, there is typically two ways to access the cloud: via a (costly) cellular connection or via intermittently available WLAN hotspots. The optimal strategy involves multi-dimensional considerations such as the availability of WLAN hotspots, energy consumption, communication costs and the expected delays. We approach this challenging problem in the framework of Markov decision processes and derive a near-optimal offloading policy.

Original language	English
Title of host publication	Proceedings of the WoWMoM 2015
Subtitle of host publication	A World of Wireless Mobile and Multimedia Networks
Editors	Luciano Bononi, Guevara Noubir, Victoria Manfredi
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479984619
DOIs	https://doi.org/10.1109/WoWMoM.2015.7158127
State	Published - 14 Jul 2015
Externally published	Yes
Event	16th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2015 - Boston, United States Duration: 14 Jun 2015 → 17 Jun 2015

Publication series

Name	Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks

Conference

Conference	16th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2015
Country/Territory	United States
City	Boston
Period	14/06/15 → 17/06/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1109/WoWMoM.2015.7158127

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Hyytia, E., Spyropoulos, T., & Ott, J. (2015). Offload (only) the right jobs: Robust offloading using the Markov decision processes. In L. Bononi, G. Noubir, & V. Manfredi (Eds.), Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks Article 7158127 (Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WoWMoM.2015.7158127

Hyytia, Esa ; Spyropoulos, Thrasyvoulos ; Ott, Jorg. / Offload (only) the right jobs : Robust offloading using the Markov decision processes. Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks. editor / Luciano Bononi ; Guevara Noubir ; Victoria Manfredi. Institute of Electrical and Electronics Engineers Inc., 2015. (Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks).

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title = "Offload (only) the right jobs: Robust offloading using the Markov decision processes",

abstract = "We consider a dynamic offloading problem arising in the context of mobile cloud computing (MCC). In MCC, three types of tasks can be identified: (i) those which can be processed only locally in a mobile device, (ii) those which are processed in the cloud, and (iii) those which can be processed either in the mobile or in the cloud. For type (iii) tasks, it is of interest to consider when they should be processed locally and when in the cloud. Furthermore, for both type (ii) and (iii) tasks, there is typically two ways to access the cloud: via a (costly) cellular connection or via intermittently available WLAN hotspots. The optimal strategy involves multi-dimensional considerations such as the availability of WLAN hotspots, energy consumption, communication costs and the expected delays. We approach this challenging problem in the framework of Markov decision processes and derive a near-optimal offloading policy.",

author = "Esa Hyytia and Thrasyvoulos Spyropoulos and Jorg Ott",

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Hyytia, E, Spyropoulos, T & Ott, J 2015, Offload (only) the right jobs: Robust offloading using the Markov decision processes. in L Bononi, G Noubir & V Manfredi (eds), Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks., 7158127, Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks, Institute of Electrical and Electronics Engineers Inc., 16th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2015, Boston, United States, 14/06/15. https://doi.org/10.1109/WoWMoM.2015.7158127

Offload (only) the right jobs: Robust offloading using the Markov decision processes. / Hyytia, Esa; Spyropoulos, Thrasyvoulos; Ott, Jorg.
Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks. ed. / Luciano Bononi; Guevara Noubir; Victoria Manfredi. Institute of Electrical and Electronics Engineers Inc., 2015. 7158127 (Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T2 - 16th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2015

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AU - Spyropoulos, Thrasyvoulos

AU - Ott, Jorg

PY - 2015/7/14

Y1 - 2015/7/14

N2 - We consider a dynamic offloading problem arising in the context of mobile cloud computing (MCC). In MCC, three types of tasks can be identified: (i) those which can be processed only locally in a mobile device, (ii) those which are processed in the cloud, and (iii) those which can be processed either in the mobile or in the cloud. For type (iii) tasks, it is of interest to consider when they should be processed locally and when in the cloud. Furthermore, for both type (ii) and (iii) tasks, there is typically two ways to access the cloud: via a (costly) cellular connection or via intermittently available WLAN hotspots. The optimal strategy involves multi-dimensional considerations such as the availability of WLAN hotspots, energy consumption, communication costs and the expected delays. We approach this challenging problem in the framework of Markov decision processes and derive a near-optimal offloading policy.

AB - We consider a dynamic offloading problem arising in the context of mobile cloud computing (MCC). In MCC, three types of tasks can be identified: (i) those which can be processed only locally in a mobile device, (ii) those which are processed in the cloud, and (iii) those which can be processed either in the mobile or in the cloud. For type (iii) tasks, it is of interest to consider when they should be processed locally and when in the cloud. Furthermore, for both type (ii) and (iii) tasks, there is typically two ways to access the cloud: via a (costly) cellular connection or via intermittently available WLAN hotspots. The optimal strategy involves multi-dimensional considerations such as the availability of WLAN hotspots, energy consumption, communication costs and the expected delays. We approach this challenging problem in the framework of Markov decision processes and derive a near-optimal offloading policy.

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Hyytia E, Spyropoulos T, Ott J. Offload (only) the right jobs: Robust offloading using the Markov decision processes. In Bononi L, Noubir G, Manfredi V, editors, Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks. Institute of Electrical and Electronics Engineers Inc. 2015. 7158127. (Proceedings of the WoWMoM 2015: A World of Wireless Mobile and Multimedia Networks). doi: 10.1109/WoWMoM.2015.7158127

Offload (only) the right jobs: Robust offloading using the Markov decision processes

Abstract

Publication series

Conference

UN SDGs

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