智慧電網將會成為新一代電力系統，並在最近幾年獲得了相當的關注。在智慧電網中，智慧電表回報用電數據到控制中心，這個控制中心稱為電表數據管理系統。控制中心也會發送控制和命令信號到智慧電表。因此，雙向的通訊架構被稱為先進讀表基礎建設是必需的，用來支持控制中心和智慧電表之間即時，可靠的數據傳輸，而智慧電表在不久的將來會迅速成長。然而，支援大量的智慧電表可能會遇到許多問題。在本文中我們關注在壅塞控制問題上，雖然每個智慧電表以低速率傳輸小數據包，但整體流量可能會超過智慧電網的網路容量並導致核心網路嚴重的壅塞，這種不利的影響也可能會傳播到與控制中心分享的其他骨幹網路。
在這篇論文中，我們提出一個解決方法使每個智慧電表基於網路的壅塞水平來局部的調整數據回報的速率。當網路變的壅塞，壅塞節點發送一個信息給智慧電表，智慧電表根據發射概率p來調整數據回報的速率。我們使用NS-2模擬軟體來實現提出的方法，我們的方法在電表數量10000，p = 0.5和p = 0的情況下比較可以減少封包丟失率約20%。

Smart grids will be emerging as the next-generation electric power system and has
received considerable attention in recent years. In smart grids, smart meters report power
consumption data to the control center, referred to as the metering data management
system (MDMS). The MDMS also sends command and control signals to smart meters.
Thus, a two-way communication infrastructure called advanced metering infrastructure
(AMI) is required to support timely and reliably data exchange between the MDMS and
smart meters, whose number is expected to grow rapidly in the near future. However,
supporting a large number of meters may encounter many issues. In this thesis, we focus
on the congestion control problem that is critical to the successful deployment of smart
grids. Although each smart meter transmits small packets at a low rate, the overall traffic
volume may exceed the network capacity, resulting in severe congestions at the network
bottleneck. This adverse effect may also propagate to other types of internet traffic that
shares the same backbone with the MDMS.
In this thesis, we propose a solution that enables each smart meter to locally adjust its
data reporting rate based on the network congestion level. When the network becomes
congested, the congesting node sends a message to the smart meters, which then adjust
their data reporting rate based on an emission probability p. The proposed scheme is
implemented in NS-2 to validate its efficacy. With 10,000 meters, our approach is shown
to decrease the packet loss probability about 20% by setting p = 0:5.

[1] H. Farhangi, The path of the smart grid", IEEE Power and Energy Magazine,
vol. 8, pp. 18 { 28, January-February 2010.
[2] R. Hassan and G. Radman, Survey on smart grid", in Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon), 18-21 March 2010.
[3] N. Kayastha, D. Niyato, E. Hossain, and Z. Han, Smart grid sensor data collection, communication, and networking: a tutorial", [Online]. Available: http://onlinelibrary.wiley.com/doi/10.1002/wcm.2258/full.
[4] T. Khalifa, K. Naik, and A. Nayak, A survey of communication protocols for automatic meter reading applications", IEEE Communications Surveys and Tu-
torials, vol. 13, pp. 168 { 182, Second Quarter 2011.
[5] D. G. Hart, Using ami to realize the smart grid", in IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 20-24 July 2008.
[6] V.K. Sood, D. Fischer, J.M. Eklund, and T. Brown, Developing a communi-cation infrastructure for the smart grid", in IEEE Electrical Power and Energy Conference (EPEC), 22-23 Oct. 2009.
[7] H. G. Rodney Tan, C. H. Lee, and V. H. Mok, Automatic power meter read-ing system using gsm network", in International Power Engineering Conference (IPEC), 3-6 Dec. 2007.
[8] A. Clark and C. J. Pavlovski, Wireless networks for the smart energy grid :Application aware networks", in Proc. Int. MultiConf. of Engineers and Computer
Scientists, March 2010.
[9] S. Galli, A. Scaglione, and Z. Wang, Power line communications and the smart grid", in First IEEE International Conference on Smart Grid Communications
(SmartGridComm), 4-6 Oct. 2010.
[10] S. K. Kim, Automatic meter reading system and method using telephone line", in United States Patent 7102533, sept. 2006.
[11] J. Zhu and R. Pecen, A novel automatic utility data collection system using ieee 802.15.4- compliant wireless mesh networks", in in Proc. IAJC-IJME International
Conference, NOV. 2006.
[12] P. McDaniel and S. McLaughlin, Security and privacy challenges in the smart grid", IEEE Security and Privacy, vol. 7, pp. 75 { 77, May-June 2009.
[13] P. P. Parikh, M. G. Kanabar, and T. S. Sidhu, Opportunities and challenges of wireless communication technologies for smart grid applications", in IEEE Power
and Energy Society General Meeting, 25-29 July 2010.
[14] R. Mao and V. Julka, Wireless broadband architecture supporting advanced me-tering infrastructure", in IEEE Vehicular Technology Conference (VTC Spring),15-18 May 2011.
[15] R. Mao and V. Julka, Wimax for advanced metering infrastructure", in Inter-national Conference on Green and Ubiquitous Technology (GUT), 7-8 July 2012.
[16] D. Niyato and P. Wang, Cooperative transmission for meter data collection in smart grid", IEEE Communications Magazine, vol. 50, pp. 90 { 97, April 2012.
[17] K. R. Jung, A. Park, and S. Lee, Machine-type-communication (mtc) de-vice grouping algorithm for congestion avoidance of mtc oriented lte network",
Security-Enriched Urban Computing and Smart Grid, vol. 78, pp. 167{178, 2010.
[18] T. Khalifa, A. Abdrabou, K. Naik, M. Alsabaan, A. Nayak, and N. Goel, Design and analysis of split- and aggregated-transport control protocol (sa-tcp) for smart
metering infrastructure", in IEEE Third International Conference on Smart Grid Communications (SmartGridComm), 5-8 Nov. 2012.
[19] CATT, R2-100182: Access control of mtc devices", in 3GPP TSG RAN WG2 Meeting 68bis, January 2010.
[20] S. Y. Lien, T. H. Liau, C. Y. Kao, and K. C. Chen, Cooperative access class barring for machine-to-machine communications", IEEE Transactions on Wireless
Communications, vol. 11, pp. 27 { 32, January 2012.
[21] S. McCanne and S. Floyd, Ns network simulator",
http://www.isi.edu/nsnam/ns/.