博碩士論文 104523020 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:13 、訪客IP:54.234.0.2
姓名 林家緯(Chia-Wei Lin)  查詢紙本館藏   畢業系所 通訊工程學系
論文名稱
(Load Reduction Device Grouping for Massive MTC Applications)
相關論文
★ 多路徑傳輸控制協定下從無線區域網路到行動網路之無縫換手★ 感知網路下具預算限制之異質性子頻段分配
★ 下行服務品質排程在多天線傳輸環境下的效能評估★ 多路徑傳輸控制協定下之整合型壅塞及路徑控制
★ Opportunistic Scheduling for Multicast over Wireless Networks★ 適用多用戶多輸出輸入系統之低複雜度比例公平性排程設計
★ 利用混合式天線分配之 LTE 異質網路 UE 與 MIMO 模式選擇★ 基於有限預算標價式拍賣之異質性頻譜分配方法
★ 適用於 MTC 裝置 ID 共享情境之排程式分群方法★ Efficient Two-Way Vertical Handover with Multipath TCP
★ 多路徑傳輸控制協定下可亂序傳輸之壅塞及排程控制★ 移動網路下適用於閘道重置之群體換手機制
★ 使用率能小型基地台之拍賣是行動數據分流方法★ 高速鐵路環境下之通道預測暨比例公平性排程設計
★ 用於行動網路效能評估之混合式物聯網流量產生器★ Network Coding Aware Early Termination for Streaming over Multipath TCP
檔案 [Endnote RIS 格式]    [Bibtex 格式]    至系統瀏覽論文 (2019-8-31以後開放)
摘要(中) 機器型態傳輸是一個能支援物聯網並可以滿足5G需求的通訊技術。大量的MTC傳輸會導致大量的信令並會造成核心網路和無線電接入網的負擔。在之前的解決方法裡,主要討論的方向為如何有效的在同一個群組分配裝置傳輸的排程。
但大部份的文獻裡並沒有討論如果加入了物聯網的應用程式必須完成的時限會有什麼問題。
在本篇論文裡將基於一個圖形模型提出一個演算法來最小化所需的分群數並考慮應用程式的時間限制。
我們列出了最小畫分群數的問題包含了延遲的限制並將這個問題修改成裝箱問題的一個變化並有隨時變動的分組數字。
這個問題可以利用MILP或是BFD演算法來解決。
在結果部份我們比較了4種不同的分群方法: 區域分群、特性分群、BFD、MILP。
摘要(英) Machine-Type Communication (MTC), an enabling communication technology, is actively evolving to support Internet of Things (IoT) and has become one of the 5G requirements.
Massive MTC connections cause significant signaling overload to both the Radio Access Network (RAN) and Core Network (CN).
Grouping devices to share resource has been widely adopted as a major solution to mitigate instantaneous signaling load in the previous works that focused on how to schedule the transmissions for the devices in the same group.
However, most of the previous works did not put the execution time constraints for the IoT applications into consideration while they designed the schedule algorithms.
In this thesis, considering the execution time constraints, we propose an algorithm based on a graph model to minimize the number of groups required for the devices.
We formulate a group number minimizing problem with latency constraint as a variation of the bin packing problem with unique emph{dynamic bin size} property,
which can be solved by specifically designed mixed-integer linear programming (MILP) or a low complexity best fit decreasing (BFD) algorithm.
Compared with methods using device location and features as grouping criteria, advantages of the group number minimizing strategy can be clearly observed.
關鍵字(中) ★ 機器型態傳輸
★ 分群
★ 共享ID
★ 物聯網
★ 排程
關鍵字(英)
論文目次 1 Introduction1
1.1 Motivation................................... 1
1.2 Contribution.................................. 2
1.3 Framework.................................. 2
2 Background of MTC/C-IoT 4
2.1 Definition and Generalities.......................... 4
2.2 Long Term Evolution(LTE)......................... 4
2.3 Architecture of C-IoT over LTE Rel.13.................... 5
2.4 Traffic Models for C-IoT........................... 6
2.4.1 Mobile Autonomous Reporting(MAR) Exception Reports..... 6
2.4.2 Mobile Autonomous Reporting(MAR) Periodic Reports...... 7
2.4.3 Network Command.......................... 7
2.4.4 Software Update/Reconfiguration Model.............. 8
2.5 Requirement in 5G............................... 8
2.6 Related Work................................. 9
3 System architecture 11
3.1 System model................................. 11
3.2 ID Sharing Scheme.............................. 12
3.3 Power Saving Mode Scheme......................... 12
3.4 Definition of Load.............................. 12
4 Problem Formulation 15
4.1 The Execution Model for IoT Applications.................. 15
4.2 Grouping benefit............................... 16
4.3 Grouping and Task Execution......................... 17
4.4 The Group Number Minimization Problem................. 18
5 Grouping Algorithms 22
5.1 MILP Solution with Fixed TimeConstraints................. 22
5.2 Best-Fit-Decreasing Solution with Dynamic Bin Size............ 23
5.3 Device Size.................................. 25
6 Performance Analysis 28
6.1 Simulation Setup............................... 28
6.2 Number of Tasks and Number of Devices.................. 30
6.3 Number of Groups and Task Missing Rates................. 31
6.4 Different Device Distribution......................... 33
7 Conclusion and Future Work 37
7.1 Conclusion.................................. 37
7.2 Futurework.................................. 37
Bibliography 38
參考文獻 [1]3GPP. System improvements for machine-type communications (mtc) (release 11).
Technical report, September 2012.

[2]3GPP. Cellular system support for ultra-low complexity and low throughput internet of things (ciot). TR 45.820 V13.1.0, 2015.
[3]3GPP. Architecture enhancements to facilitate communications with packet data net- works and applications. TS 23.682 V15.0.0, March 2017.
[4]MOSEK ApS. The MOSEK optimization toolbox for MATLAB manual. Version 7.1 (Revision 28)., 2015.
[5]Guo Chen, Jiwei Huang, Bo Cheng, and Junliang Chen. A social network based approach for iot device management and service composition. In 2015 IEEE World Congress on Services, pages 1–8. IEEE, 2015.
[6]M. Ito, N. Nishinaga, Y. Kitatsuji, and M. Murata. Reducing state information by sharing imsi for cellular iot devices. IEEE Internet of Things Journal, 3(6):1297– 1309, Dec 2016.
[7]Kookjin Lee, JaeSheung Shin, Yongwoo Cho, Kab Seok Ko, Dan Keun Sung, and Heonshik Shin. A group-based communication scheme based on the location infor- mation of MTC devices in cellular networks. In 2012 IEEE International Conference on Communications (ICC), pages 4899–4903. IEEE, jun 2012.
[8]S. Y. Lien, K. C. Chen, and Y. Lin. Toward ubiquitous massive accesses in 3gpp machine-to-machine communications. IEEE Communications Magazine, 49(4):66– 74, April 2011.
[9]Ronald L. Graham Panos M. Pardalos, Ding-Zhu Du. Handbook of Combinatorial Optimization. Springer, 2nd Edition, 2005.

[10]Hamidreza Shariatmadari, Rapeepat Ratasuk, Sassan Iraji, Andr e´s Laya, Tarik Taleb,
Riku Ja¨ntti, and Amitava Ghosh. Machine-type communications: current status and future perspectives toward 5G systems. IEEE Communications Magazine, 53(9):10– 17, sep 2015.
[11]K. Suto, H. Nishiyama, N. Kato, and C. W. Huang. An energy-efficient and delay- aware wireless computing system for industrial wireless sensor networks. IEEE Ac- cess, 3:1026–1035, 2015.
[12]Tarik Taleb and Adlen Ksentini. On alleviating MTC overload in EPS. Ad Hoc Networks, 18:24–39, jul 2014.
[13]Tarik Taleb, Adlen Ksentini, and Abdellatif Kobbane. Lightweight mobile core net- works for machine type communications. IEEE Access, 2:1128–1137, 2014.
[14]Ang-Hsun Tsai, Li-Chun Wang, Jane-Hwa Huang, and Tzu-Ming Lin. Overload Control for Machine Type Communications with Femtocells. In 2012 IEEE Vehicular Technology Conference (VTC Fall), pages 1–5. IEEE, September 2012.
[15]C. W. Tseng, R. Boisguene, C. W. Huang, P. Lin, and Y. Kawamoto. A scheduled grouping scheme for mtc device id sharing. In International Wireless Communica- tions and Mobile Computing Conference (IWCMC), pages 1307–1311, Aug 2015.
[16]X. Wang, M. J. Sheng, Y. Y. Lou, Y. Y. Shih, and M. Chiang. Internet of things session management over lte ;balancing signal load, power, and delay. IEEE Internet of Things Journal, 3(3):339–353, June 2016.
指導教授 黃志煒 審核日期 2017-8-24
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明