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dc.contributor.author | Huang, Huawei | en |
dc.contributor.author | Guo, Song | en |
dc.contributor.author | Liang, Weifa | en |
dc.contributor.author | Wang, Kun | en |
dc.contributor.alternative | 黄, 華威 | ja |
dc.date.accessioned | 2018-08-01T06:07:37Z | - |
dc.date.available | 2018-08-01T06:07:37Z | - |
dc.date.issued | 2018-05 | - |
dc.identifier.isbn | 9781538631812 | - |
dc.identifier.issn | 1938-1883 | - |
dc.identifier.uri | http://hdl.handle.net/2433/233042 | - |
dc.description | [The 54th IEEE International Conference on Communications (ICC 2018)] SELECTED AREAS IN COMMUNICATIONS SYMPOSIUM-SOCIAL NETWORKS TRACK: May 20-24, 2018. Kansas City, MO, USA. | en |
dc.description.abstract | As the critical supplementary to terrestrial communication networks, the low-earth-orbit (LEO) satellite based communication networks regain growing attentions in recent few years. In this paper, we focus on data gathering for geo- distributed Internet-of-Things (IoT) networks via LEO satellites. Normally, the power supply in IoT data-gathering gateways is a bottleneck resource that constrains the network throughput. Thus, the challenge is how to upload data from IoT gateways to LEO satellites under dynamic uplinks in an energy-efficient way. To address this problem, we first formulate a novel optimization problem, and then propose an online algorithm for green data-uploading in geo-distributed IoT networks. In the proposed framework, we aim to jointly maximize the network throughput and minimize the energy consumption at gateways, while avoiding the buffer overflow at gateways. We finally evaluate the performance of the proposed algorithm through simulations using both real-world and synthetic traces. The simulation results demonstrate that the proposed approach can achieve high efficiency on the power consumption and significantly reduce queue backlogs compared with a benchmark using greedy policy. | en |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | IEEE | en |
dc.rights | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en |
dc.rights | This is not the published version. Please cite only the published version. | en |
dc.rights | この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。 | ja |
dc.title | Green Data Gathering from Geo-distributed IoT Networks via LEO Satellites | en |
dc.type | conference paper | - |
dc.type.niitype | Conference Paper | - |
dc.identifier.jtitle | 2018 IEEE International Conference on Communications (ICC) | - |
dc.relation.doi | 10.1109/ICC.2018.8422522 | - |
dc.textversion | author | - |
dc.address | Department of IST, Graduate School of Informatics, Kyoto University | en |
dc.address | Department of Computing, The Hong Kong Polytechnic University | en |
dc.address | Research School of Computer Science, Australian National University | en |
dc.address | Nanjing University of Posts and Telecommunications | en |
dc.relation.url | ttp://icc2018.ieee-icc.org/ | - |
dcterms.accessRights | open access | - |
出現コレクション: | 学術雑誌掲載論文等 |
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