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題名 智慧家庭具服務品質感知的頻寬分配研究
QoS aware banwidth allocation for smart homes作者 黃麒瑋
Huang, Chi-Wei貢獻者 張宏慶
Jang, Hung-Chin
黃麒瑋
Huang, Chi-Wei關鍵詞 智慧家庭
頻寬分配
封包排程
Smart Home
Bandwidth Allocation
Packet Scheduling日期 2017 上傳時間 1-Mar-2017 17:13:52 (UTC+8) 摘要 隨著智慧家庭概念與技術的興盛與成熟，未來ISP(Internet Service Provider)業者勢必面臨管理大量智慧家庭中各種不同應用競爭頻寬資源的情況。為因應大量且繁雜類型的應用服務彼此競爭智慧家庭端及ISP端的頻寬資源，考量並應用適當的頻寬分配法則以盡可能優化使用者體驗(QoE)是本研究的研究動機。相關文獻的排程演算法如TDPSS (Time Domain Priority Set Scheduler)、MSCDL (Mac Scheduler)、Proportional Fair (PF)及Adaptive Modified Largest Weighted Delay First (AMLWDF)等。若要用以管理大量智慧家庭的頻寬資源時，ISP業者須將家庭申辦頻寬方案以及ISP端的系統頻寬分開考量。ISP在整合(aggregate)多個家庭的頻寬資源請求時，會依服務類別分配頻寬，最後依據不同類別採取適當處理，進而提升不同應用的QoS品質。本篇論文著重於延遲時間的考量，提出能分類來自各個智慧家庭中，屬於不同QCI (QoS Class Identifier)級別的頻寬請求並以不同佇列存放，依DADS (Delay Aware Dynamical Scheduling)演算法計算優先權值。我們利用保障頻寬與動態配置頻寬給不同用戶服務佇列，並優先分配頻寬給較高優先權的用戶服務，以期在維持一定公平性的前提下，盡可能地降低延遲來提升QoS品質。在我們的實驗數據分析中，我們將DADS和其他方法如MSCDL、PF、TDPSS以及AMLWDF進行公平性、產能、延遲以及抖動率等效能優劣的比較與分析。最後在總結與未來研究方向，我們歸納與整理了DADS與PF、MSCDL、TDPSS以及AMLWDF等演算法的效能優劣。實驗結果顯示，在延遲上，DADS勝過PF和TDPSS，但略輸MSCDL及AMLWDF；在抖動率及產能上，DADS均較其它四者為差；公平性上則是劣於TDPSS、PF及MSCDL但優於AMLWDF。雖然DADS在整體的表現並非最好，但在特別重視延遲時間的Category1類別(包含QCI級別為1、2及5的應用服務)的延遲效能僅輸AMLWDF些許，而產能卻明顯勝過AMLWDF，由此可見DADS在Category1的表現最佳。
With the concept and technology of smart homes becoming more and more mature and popular, Internet service provider (ISP) must face managing large set of various applications from smart homes which competing for bandwidth resources. In order to enhance Quality of Services (QoS) of a lot of various applications while they are competing bandwidth resources of both smart homes (home internal) and Internet service provider (home external), we propose a QoS aware bandwidth allocation criterion to optimize Quality of user Experience (QoE). Since ISP has to manage bandwidth resources of large set of smart homes, in the proposed criterion each ISP separates the bandwidth resources for home external bandwidth and system bandwidth of ISP, respectively. Then, aggregates bandwidth requests of large number of smart homes according to distinct service classes.This thesis focuses on the performance index of delay. We proposed to classify bandwidth requests from smart homes and put them into different queues, finally, calculate priority values by DADS (Delay Aware Dynamical Scheduling) algorithm. The proposed method is able to effectively reduce delay time with certain degree of fairness guarantee by dynamically allocate bandwidth resources for services with distinct service priorities.In the experiments, we compared DADS with other algorithms such as MSCDL (Mac Scheduler), PF (Proportional Fair), TDPSS (Time Domain Priority Set Scheduler) and AMLWDF (Adaptive Modified Largest Weighted Delay First), etc. in terms of fairness, throughput, delay and jitter. The experiments results show that DADS performs much better than PF and TDPSS but a bit worse than MSCDL and AMLWDF in terms of delay. However, DADS shows no better performance than all other algorithms in terms of jitter and throughput. In fairness comparison, DADS is worse than PF, TDPSS and MSCDL but is better than AMLWDF. Though DADS has no superior performance on overall indices, it is a bit worse than AMLWDF in delay of Category1 (including QCI 1, 2 and 5), its throughput is better than AMLWDF. Therefore, DADS’s performance is the best on Category1 considering overall indices.參考文獻 [1] C. Mehlfuhrer, M.Wrulich, J.C Ikuno, D.Bosnska, and M. Rupp, Aug. 2009 “Simulating the Long Term Evolution Physical Layer,” in Proc. of the 17th European Signal processing conference(EUSIPCO 2009), Glasgow, Scotland,.[2] H. Fattah and H. Alnuweiri, “A Cross-Layer Design for Dynamic Resource Block Allocation in 3G Long Term Evolution System,” Mobile Adhoc and Sensor Systems, IEEE, Oct 2009, pp.929-934.[3] S. Schwarz, C. Mehlfuhrer and M. Rupp, “Low Complexity Approximate Maximum Throughput Scheduling for LTE,” 44th Annual Asilomar conference on Signals, Systems and Computers, California, USA, 2010. [4] J. M. Holtzman, QUALCOMM Inc. “Asymptotic Analysis of Proportional Fair Algorithm,” Personal, Indoor and Mobile Radio Communications (IEEE PIMRC), vol.2, Aug. 2001, page(s): F-33-F37.[5] R. Basukala, H.A. Mohd Ramli, and K. Sandrasegaran, “Performance Analysis of EXP/PF and M-LWDF in Downlink 3GPP LTE System,” in Proc. of the 1st Asian Himalayas International Conference on Internet(AH-ICI’09), Aug. 2009, pp.1-5.[6] 3GPP TS 23.107, Quality of Service (QoS) Concept and Architecture, ver. 5.4.0., Mar. 2002.[7] H. C. Jang and C. P. Hu, “Fairness-Based Adaptive QoS Scheduling for LTE,” International Conference on ICT Convergence 2013 (ICTC 2013), Jeju Island, Korea, Oct. 14-16, 2013.[8] J. Liu, J. Li, G. Shou, Y. Hu, Z. Guo, Wei Dai,” SDN Based Load Balancing Mechanism for Elephant Flow in Data Center Networks,”17th International Symposium on Wireless Personal Multimedia Communications (WPMC2014), retrieved on Apr.17, 2016.[9] G. Monghal, K. I. Pedersen, I. Z. Kovács, P. E. Mogensen, ” QoS Oriented Time and Frequency Domain Packet Schedulers for The UTRAN Long Term Evolution, ”Vehicular Technology Conference, 2008. VTC Spring 2008. IEEE. 20 May 2008[10] Y. Zaki1, T. Weerawardane1, Carmelita Görg1, and Andreas Timm-Giel2,” Multi-QoS-aware Fair Scheduling for LTE, ”Vehicular Technology Conference (VTC Spring), 2011 IEEE 73rd, 18 July 2011.[11] H. C. Jang, C. W. Huang, F. K. Yeh,” Design a bandwidth allocation framework for SDN based smart home,”2016 IEEE 7th Annual on Information Technology, Electronics and Mobile Communication Conference (IEMCON).[12] H. H. Gharakheili, J. Bass, L. Exton, V. Sivaraman†, ”Personalizing the Home Network Experience using Cloud-Based SDN,”2014 IEEE 15th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), June, 2014.[13] Y. Kim, Y. Lee,” Automatic Generation of Social Relationships between Internet of Things in Smart Home using SDN-based Home Cloud,” 2015 29th International Conference on Advanced Information Networking and Applications Workshops, 2015.[14] M. Lee, Y. Kim, Y. Lee, “A Home Cloud-based Home Network Auto-Configuration using SDN, ”Proceedings of 2015 IEEE 12th International Conference on Networking, Sensing and Control Howard Civil Service International House, April 9-11, 2015.[15] F. Capozzi, G. Piro, Student Member,” Downlink Packet Scheduling in LTE Cellular Networks: Key Design Issues and a Survey,” IEEE Communications Surveys & Tutorials (Volume: 15, Issue: 2, Second Quarter of 2013).[16] K. Sandrasegaran, H. A. M. Ramli and R. Basukala,” Delay-Prioritized Scheduling (DPS) for Real Time Traffic in 3GPP LTE System,” IEEE Wireless Communications and Networking Conference (WCNC), 2010.[17] G. Piro, Student Member,” Two-Level Downlink Scheduling for Real-Time Multimedia Services in LTE Networks,” IEEE Transactions on Multimedia, Volume: 13, Issue: 5, Oct. 2011.[18] E. Skondras, A. Michalas, A. Sgora, and D. D. Vergados, “A downlink scheduler supporting real time services in LTE cellular networks,” in Information, Intelligence, Systems and Applications (IISA), 2015 6th International Conference on. IEEE, 2015, pp. 1–6.[19] H. A. M. Ramli, R. Basukala, K. Sandrasegaran, and R. Patachaianand, “Performance of well known packet scheduling algorithms in the downlink 3GPP LTE system,” in Communications (MICC), 2009 IEEE 9th Malaysia International Conference on. IEEE, 2009, pp. 815–820.[20] E. Skondras, A. Michalas, A. Sgora, D. D. Vergados,” QoS-aware scheduling in LTE-A networks with SDN control,” in Information, Intelligence, Systems & Applications (IISA), 2016 7th International Conference on IEEE,2016, pp.1-6.[21] M. H. H. Mohammed Abdul Jawad M. Al-Shibly and M. R. Islam, “Radio resource scheduling in LTE-Advanced system with Carrier Aggregation,” ARPN Journal of Engineering and Applied Sciences, vol. 10, no. 22, 2015 , pp. 17281–17285. [22] S. Oh, J. Na, and D. Kwon, “Performance Analysis of Cross Component Carrier Scheduling in LTE Small Cell Access Point System,” in The Second International Conference on Electrical, Electronics, Computer Engineering and their Applications (EECEA2015), 2015, p. 146.[23] H. A. M. Ramli, K. Sandrasegaran, R. Basukala, R. Patachaianand, M. Xue and Cheng-Chung Lin, “Resource Allocation Technique for Video Streaming Applications in the LTE System,” 19th Annual Wireless and Optical Communications Conference (WOCC), 2010.[24] A. K. F. Khattab and K. M. F. Elsayed, "Opportunistic Scheduling of Delay Sensitive Traffic in OFDMA-based Wireless Networks," in International Symposium on a World of Wireless, Mobile and Multimedia Networks, 2006.[25] D. Li, Student Member,” Distributed Smart-Home Decision-Making in a Hierarchical Interactive Smart Grid Architecture,” IEEE Transactions on Parallel and Distributed Systems, Volume: 26, Issue: 1, Jan. 2015. 描述 碩士
國立政治大學
資訊科學學系
103753004@nccu.edu.tw資料來源 http://thesis.lib.nccu.edu.tw/record/#G0103753004 資料類型 thesis dc.contributor.advisor 張宏慶 zh_TW dc.contributor.advisor Jang, Hung-Chin en_US dc.contributor.author (Authors) 黃麒瑋 zh_TW dc.contributor.author (Authors) Huang, Chi-Wei en_US dc.creator (作者) 黃麒瑋 zh_TW dc.creator (作者) Huang, Chi-Wei en_US dc.date (日期) 2017 en_US dc.date.accessioned 1-Mar-2017 17:13:52 (UTC+8) - dc.date.available 1-Mar-2017 17:13:52 (UTC+8) - dc.date.issued (上傳時間) 1-Mar-2017 17:13:52 (UTC+8) - dc.identifier (Other Identifiers) G0103753004 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/106880 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊科學學系 zh_TW dc.description (描述) 103753004@nccu.edu.tw zh_TW dc.description.abstract (摘要) 隨著智慧家庭概念與技術的興盛與成熟，未來ISP(Internet Service Provider)業者勢必面臨管理大量智慧家庭中各種不同應用競爭頻寬資源的情況。為因應大量且繁雜類型的應用服務彼此競爭智慧家庭端及ISP端的頻寬資源，考量並應用適當的頻寬分配法則以盡可能優化使用者體驗(QoE)是本研究的研究動機。相關文獻的排程演算法如TDPSS (Time Domain Priority Set Scheduler)、MSCDL (Mac Scheduler)、Proportional Fair (PF)及Adaptive Modified Largest Weighted Delay First (AMLWDF)等。若要用以管理大量智慧家庭的頻寬資源時，ISP業者須將家庭申辦頻寬方案以及ISP端的系統頻寬分開考量。ISP在整合(aggregate)多個家庭的頻寬資源請求時，會依服務類別分配頻寬，最後依據不同類別採取適當處理，進而提升不同應用的QoS品質。本篇論文著重於延遲時間的考量，提出能分類來自各個智慧家庭中，屬於不同QCI (QoS Class Identifier)級別的頻寬請求並以不同佇列存放，依DADS (Delay Aware Dynamical Scheduling)演算法計算優先權值。我們利用保障頻寬與動態配置頻寬給不同用戶服務佇列，並優先分配頻寬給較高優先權的用戶服務，以期在維持一定公平性的前提下，盡可能地降低延遲來提升QoS品質。在我們的實驗數據分析中，我們將DADS和其他方法如MSCDL、PF、TDPSS以及AMLWDF進行公平性、產能、延遲以及抖動率等效能優劣的比較與分析。最後在總結與未來研究方向，我們歸納與整理了DADS與PF、MSCDL、TDPSS以及AMLWDF等演算法的效能優劣。實驗結果顯示，在延遲上，DADS勝過PF和TDPSS，但略輸MSCDL及AMLWDF；在抖動率及產能上，DADS均較其它四者為差；公平性上則是劣於TDPSS、PF及MSCDL但優於AMLWDF。雖然DADS在整體的表現並非最好，但在特別重視延遲時間的Category1類別(包含QCI級別為1、2及5的應用服務)的延遲效能僅輸AMLWDF些許，而產能卻明顯勝過AMLWDF，由此可見DADS在Category1的表現最佳。 zh_TW dc.description.abstract (摘要) With the concept and technology of smart homes becoming more and more mature and popular, Internet service provider (ISP) must face managing large set of various applications from smart homes which competing for bandwidth resources. In order to enhance Quality of Services (QoS) of a lot of various applications while they are competing bandwidth resources of both smart homes (home internal) and Internet service provider (home external), we propose a QoS aware bandwidth allocation criterion to optimize Quality of user Experience (QoE). Since ISP has to manage bandwidth resources of large set of smart homes, in the proposed criterion each ISP separates the bandwidth resources for home external bandwidth and system bandwidth of ISP, respectively. Then, aggregates bandwidth requests of large number of smart homes according to distinct service classes.This thesis focuses on the performance index of delay. We proposed to classify bandwidth requests from smart homes and put them into different queues, finally, calculate priority values by DADS (Delay Aware Dynamical Scheduling) algorithm. The proposed method is able to effectively reduce delay time with certain degree of fairness guarantee by dynamically allocate bandwidth resources for services with distinct service priorities.In the experiments, we compared DADS with other algorithms such as MSCDL (Mac Scheduler), PF (Proportional Fair), TDPSS (Time Domain Priority Set Scheduler) and AMLWDF (Adaptive Modified Largest Weighted Delay First), etc. in terms of fairness, throughput, delay and jitter. The experiments results show that DADS performs much better than PF and TDPSS but a bit worse than MSCDL and AMLWDF in terms of delay. However, DADS shows no better performance than all other algorithms in terms of jitter and throughput. In fairness comparison, DADS is worse than PF, TDPSS and MSCDL but is better than AMLWDF. Though DADS has no superior performance on overall indices, it is a bit worse than AMLWDF in delay of Category1 (including QCI 1, 2 and 5), its throughput is better than AMLWDF. Therefore, DADS’s performance is the best on Category1 considering overall indices. en_US dc.description.tableofcontents 圖目錄 8表目錄 10第1章 緒論 121.1背景 121.1.1智慧家庭(Smart Home)簡介 121.1.2頻寬資源分配(Bandwidth Resource Allocation)簡介 131.2研究動機 141.3論文架構 15第2章 相關研究 162.1排程演算法 162.1.1Best Channel Quality Indicator 172.1.2Round Robin 172.1.3 Proportional Fair 182.1.4 Modified Largest Weighted Delay First (MLWDF) 192.1.5 Adaptive Modified Largest Weighted Delay First(A-MLDWF) 192.1.6 Time Domain Prioriy Set Scheduling(TDPSS) 212.1.7 Mac Scheduler(MSCDL) 232.1.8 Delay Prioritized Scheduling 242.1.9 Frame Level Scheduler Advanced 272.1.10 Frame Level Scheduler Advanced – Cross Carrier 292.1.11 Extended Opportunistic 322.2總結 34第3章 研究方法 363.1問題分析 393.1.1智慧家庭服務品質的需求考量 393.1.2公平性、優先權及產能的考量 403.1.3避免佇列中的資料產生飢餓 413.1.4智慧家庭用戶服務競爭網路資源的平衡取捨 413.2研究方法 423.2.1智慧家庭應用外部頻寬允入控制之用戶服務分類 423.2.2考量QoS之DADS (Delay Aware Dynamical Scheduling)排程演算法 443.2.3排程演算法之架構與流程 46第4章 模擬實驗與結果分析 624.1實驗環境與假設 624.1.1評估指標 624.1.2模擬環境 644.2實驗數據與分析 654.2.1實驗一 654.2.2實驗二 71第5章 結論與未來研究 825.1結論 825.1.1 總效能比較與討論 845.2未來研究 85參考文獻 87 zh_TW dc.format.extent 2600939 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0103753004 en_US dc.subject (關鍵詞) 智慧家庭 zh_TW dc.subject (關鍵詞) 頻寬分配 zh_TW dc.subject (關鍵詞) 封包排程 zh_TW dc.subject (關鍵詞) Smart Home en_US dc.subject (關鍵詞) Bandwidth Allocation en_US dc.subject (關鍵詞) Packet Scheduling en_US dc.title (題名) 智慧家庭具服務品質感知的頻寬分配研究 zh_TW dc.title (題名) QoS aware banwidth allocation for smart homes en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) [1] C. Mehlfuhrer, M.Wrulich, J.C Ikuno, D.Bosnska, and M. Rupp, Aug. 2009 “Simulating the Long Term Evolution Physical Layer,” in Proc. of the 17th European Signal processing conference(EUSIPCO 2009), Glasgow, Scotland,.[2] H. Fattah and H. Alnuweiri, “A Cross-Layer Design for Dynamic Resource Block Allocation in 3G Long Term Evolution System,” Mobile Adhoc and Sensor Systems, IEEE, Oct 2009, pp.929-934.[3] S. Schwarz, C. Mehlfuhrer and M. Rupp, “Low Complexity Approximate Maximum Throughput Scheduling for LTE,” 44th Annual Asilomar conference on Signals, Systems and Computers, California, USA, 2010. [4] J. M. Holtzman, QUALCOMM Inc. “Asymptotic Analysis of Proportional Fair Algorithm,” Personal, Indoor and Mobile Radio Communications (IEEE PIMRC), vol.2, Aug. 2001, page(s): F-33-F37.[5] R. Basukala, H.A. Mohd Ramli, and K. Sandrasegaran, “Performance Analysis of EXP/PF and M-LWDF in Downlink 3GPP LTE System,” in Proc. of the 1st Asian Himalayas International Conference on Internet(AH-ICI’09), Aug. 2009, pp.1-5.[6] 3GPP TS 23.107, Quality of Service (QoS) Concept and Architecture, ver. 5.4.0., Mar. 2002.[7] H. C. Jang and C. P. Hu, “Fairness-Based Adaptive QoS Scheduling for LTE,” International Conference on ICT Convergence 2013 (ICTC 2013), Jeju Island, Korea, Oct. 14-16, 2013.[8] J. Liu, J. Li, G. Shou, Y. Hu, Z. Guo, Wei Dai,” SDN Based Load Balancing Mechanism for Elephant Flow in Data Center Networks,”17th International Symposium on Wireless Personal Multimedia Communications (WPMC2014), retrieved on Apr.17, 2016.[9] G. Monghal, K. I. Pedersen, I. Z. Kovács, P. E. Mogensen, ” QoS Oriented Time and Frequency Domain Packet Schedulers for The UTRAN Long Term Evolution, ”Vehicular Technology Conference, 2008. VTC Spring 2008. IEEE. 20 May 2008[10] Y. Zaki1, T. Weerawardane1, Carmelita Görg1, and Andreas Timm-Giel2,” Multi-QoS-aware Fair Scheduling for LTE, ”Vehicular Technology Conference (VTC Spring), 2011 IEEE 73rd, 18 July 2011.[11] H. C. Jang, C. W. Huang, F. K. Yeh,” Design a bandwidth allocation framework for SDN based smart home,”2016 IEEE 7th Annual on Information Technology, Electronics and Mobile Communication Conference (IEMCON).[12] H. H. Gharakheili, J. Bass, L. Exton, V. Sivaraman†, ”Personalizing the Home Network Experience using Cloud-Based SDN,”2014 IEEE 15th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), June, 2014.[13] Y. Kim, Y. Lee,” Automatic Generation of Social Relationships between Internet of Things in Smart Home using SDN-based Home Cloud,” 2015 29th International Conference on Advanced Information Networking and Applications Workshops, 2015.[14] M. Lee, Y. Kim, Y. Lee, “A Home Cloud-based Home Network Auto-Configuration using SDN, ”Proceedings of 2015 IEEE 12th International Conference on Networking, Sensing and Control Howard Civil Service International House, April 9-11, 2015.[15] F. Capozzi, G. Piro, Student Member,” Downlink Packet Scheduling in LTE Cellular Networks: Key Design Issues and a Survey,” IEEE Communications Surveys & Tutorials (Volume: 15, Issue: 2, Second Quarter of 2013).[16] K. Sandrasegaran, H. A. M. Ramli and R. Basukala,” Delay-Prioritized Scheduling (DPS) for Real Time Traffic in 3GPP LTE System,” IEEE Wireless Communications and Networking Conference (WCNC), 2010.[17] G. Piro, Student Member,” Two-Level Downlink Scheduling for Real-Time Multimedia Services in LTE Networks,” IEEE Transactions on Multimedia, Volume: 13, Issue: 5, Oct. 2011.[18] E. Skondras, A. Michalas, A. Sgora, and D. D. Vergados, “A downlink scheduler supporting real time services in LTE cellular networks,” in Information, Intelligence, Systems and Applications (IISA), 2015 6th International Conference on. IEEE, 2015, pp. 1–6.[19] H. A. M. Ramli, R. Basukala, K. Sandrasegaran, and R. Patachaianand, “Performance of well known packet scheduling algorithms in the downlink 3GPP LTE system,” in Communications (MICC), 2009 IEEE 9th Malaysia International Conference on. IEEE, 2009, pp. 815–820.[20] E. Skondras, A. Michalas, A. Sgora, D. D. Vergados,” QoS-aware scheduling in LTE-A networks with SDN control,” in Information, Intelligence, Systems & Applications (IISA), 2016 7th International Conference on IEEE,2016, pp.1-6.[21] M. H. H. Mohammed Abdul Jawad M. Al-Shibly and M. R. Islam, “Radio resource scheduling in LTE-Advanced system with Carrier Aggregation,” ARPN Journal of Engineering and Applied Sciences, vol. 10, no. 22, 2015 , pp. 17281–17285. [22] S. Oh, J. Na, and D. Kwon, “Performance Analysis of Cross Component Carrier Scheduling in LTE Small Cell Access Point System,” in The Second International Conference on Electrical, Electronics, Computer Engineering and their Applications (EECEA2015), 2015, p. 146.[23] H. A. M. Ramli, K. Sandrasegaran, R. Basukala, R. Patachaianand, M. Xue and Cheng-Chung Lin, “Resource Allocation Technique for Video Streaming Applications in the LTE System,” 19th Annual Wireless and Optical Communications Conference (WOCC), 2010.[24] A. K. F. Khattab and K. M. F. Elsayed, "Opportunistic Scheduling of Delay Sensitive Traffic in OFDMA-based Wireless Networks," in International Symposium on a World of Wireless, Mobile and Multimedia Networks, 2006.[25] D. Li, Student Member,” Distributed Smart-Home Decision-Making in a Hierarchical Interactive Smart Grid Architecture,” IEEE Transactions on Parallel and Distributed Systems, Volume: 26, Issue: 1, Jan. 2015. zh_TW
