The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Platform rangkaian perkhidmatan mesin-ke-mesin (M2M) yang menampung dan mengawal pelbagai jenis peranti Internet of Things telah dipersembahkan. Kertas kerja ini menyiasat strategi penempatan fail program untuk platform rangkaian perkhidmatan M2M yang mencapai nisbah penyekatan rendah permintaan tugas baharu dan menampung sebanyak mungkin tugasan dalam senario dinamik. Kami membentangkan empat strategi untuk menentukan penempatan fail program, yang berbeza dalam kaedah pengiraan dan sama ada penempatan semula fail program yang digunakan oleh tugas sedia ada dibenarkan atau tidak. Keputusan simulasi menunjukkan bahawa strategi berdasarkan penyelesaian model pengaturcaraan linear integer bercampur mencapai nisbah penyekatan terendah, tetapi strategi berasaskan algoritma heuristik boleh menjadi pilihan yang menarik dengan membenarkan pengiraan semula peletakan apabila peletakan tidak dapat diperoleh pada masa ketibaan permintaan tugas baru.
Takehiro SATO
Kyoto University
Eiji OKI
Kyoto University
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Salinan
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
Salinan
@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},}
Salinan
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 -