Program File Placement Strategies for Machine-to-Machine Service Network Platform in Dynamic Scenario
Summary :
The machine-to-machine (M2M) service network platform that accommodates and controls various types of Internet of Things devices has been presented. This paper investigates program file placement strategies for the M2M service network platform that achieve low blocking ratios of new task requests and accommodate as many tasks as possible in the dynamic scenario. We present four strategies for determining program file placement, which differ in the computation method and whether the relocation of program files being used by existing tasks is allowed or not. Simulation results show that a strategy based on solving a mixed-integer linear programming model achieves the lowest blocking ratio, but a heuristic algorithm-based strategy can be an attractive option by allowing recomputation of the placement when the placement cannot be obtained at the timing of new task request arrival.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E103-B No.11 pp.1353-1366
- Publication Date
- 2020/11/01
- Publicized
- 2020/05/08
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2020EBP3001
- Type of Manuscript
- PAPER
- Category
- Network
Authors
Takehiro SATO
Kyoto University
Eiji OKI
Kyoto University
Keyword
Latest Issue
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Takehiro SATO, Eiji OKI, "Program File Placement Strategies for Machine-to-Machine Service Network Platform in Dynamic Scenario" in IEICE TRANSACTIONS on Communications,
vol. E103-B, no. 11, pp. 1353-1366, November 2020, doi: 10.1587/transcom.2020EBP3001.
Abstract: The machine-to-machine (M2M) service network platform that accommodates and controls various types of Internet of Things devices has been presented. This paper investigates program file placement strategies for the M2M service network platform that achieve low blocking ratios of new task requests and accommodate as many tasks as possible in the dynamic scenario. We present four strategies for determining program file placement, which differ in the computation method and whether the relocation of program files being used by existing tasks is allowed or not. Simulation results show that a strategy based on solving a mixed-integer linear programming model achieves the lowest blocking ratio, but a heuristic algorithm-based strategy can be an attractive option by allowing recomputation of the placement when the placement cannot be obtained at the timing of new task request arrival.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2020EBP3001/_p
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@ARTICLE{e103-b_11_1353,
author={Takehiro SATO, Eiji OKI, },
journal={IEICE TRANSACTIONS on Communications},
title={Program File Placement Strategies for Machine-to-Machine Service Network Platform in Dynamic Scenario},
year={2020},
volume={E103-B},
number={11},
pages={1353-1366},
abstract={The machine-to-machine (M2M) service network platform that accommodates and controls various types of Internet of Things devices has been presented. This paper investigates program file placement strategies for the M2M service network platform that achieve low blocking ratios of new task requests and accommodate as many tasks as possible in the dynamic scenario. We present four strategies for determining program file placement, which differ in the computation method and whether the relocation of program files being used by existing tasks is allowed or not. Simulation results show that a strategy based on solving a mixed-integer linear programming model achieves the lowest blocking ratio, but a heuristic algorithm-based strategy can be an attractive option by allowing recomputation of the placement when the placement cannot be obtained at the timing of new task request arrival.},
keywords={},
doi={10.1587/transcom.2020EBP3001},
ISSN={1745-1345},
month={November},}
Copy
TY - JOUR
TI - Program File Placement Strategies for Machine-to-Machine Service Network Platform in Dynamic Scenario
T2 - IEICE TRANSACTIONS on Communications
SP - 1353
EP - 1366
AU - Takehiro SATO
AU - Eiji OKI
PY - 2020
DO - 10.1587/transcom.2020EBP3001
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E103-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 2020
AB - The machine-to-machine (M2M) service network platform that accommodates and controls various types of Internet of Things devices has been presented. This paper investigates program file placement strategies for the M2M service network platform that achieve low blocking ratios of new task requests and accommodate as many tasks as possible in the dynamic scenario. We present four strategies for determining program file placement, which differ in the computation method and whether the relocation of program files being used by existing tasks is allowed or not. Simulation results show that a strategy based on solving a mixed-integer linear programming model achieves the lowest blocking ratio, but a heuristic algorithm-based strategy can be an attractive option by allowing recomputation of the placement when the placement cannot be obtained at the timing of new task request arrival.
ER -
English
