Paper List

Zigbee

1. Li-Hsing Yen and Wei-Ting Tsai, "The Room Shortage Problem of Tree-Based ZigBee/IEEE802.15.4 Wireless Networks," Computer Communications, October 2009.
   
   
2. Meng-Shiuan Pan, Chia-Hung Tsai, and Yu-Chee Tseng, "The Orphan Problem in ZigBee Wireless Networks," IEEE Transactions on Mobile Computing, Mar 2009.
   
   
3. Lain-Jinn Hwang, Shiann-Tsong Sheu, Yun-Yen Shih, and Yen-Chieh Cheng, "Grouping Strategy for Solving Hidden Node Problem in IEEE 802.15.4 LR-WPAN," Proceedings of the First International Conference on Wireless Internet, pp. 26-32, July 2005.
   
   
4. Anis Koubâa, André Cunha, Mário Alves, and Eduardo Tovar, "TDBS: a time division beacon scheduling mechanism for ZigBee cluster-tree wireless sensor networks," Real-Time Systems, vol. 40, pp. 321-354, October 2008.
   
   
5. Lun-Wu Yeh, Meng-Shiuan Pan, Yu-Chee Tseng, "Two-Way Beacon Scheduling in ZigBee Tree-BasedWireless Sensor Networks," IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing, pp. 130-137, June 2008.
   
   
6. M.-S. Pan, H.-W. Fang, Y.-C. Liu, and Y.-C. Tseng, "Address Assignment and Routing Schemes for ZigBee-Based Long-Thin Wireless Sensor Networks," IEEE Vehicular Technology Conference, pp. 173-177, 2008.
   
   
7. Jin-Woo Kim, Jihoon Kim, and Doo-Seop Eom, "Multi-Dimensional Channel Management Scheme to Avoid Beacon Collision in LR-WPAN," IEEE Transactions on Consumer Electronics, vol. 54, pp. 396-404, 2008.
   
   
8. Bing Han and Gwendal Simon, "Optimizing Multi-hop Queries in ZigBee Based Multi-sink Sensor Networks," Lecture Notes In Computer Science, Vol. 5408, pp. 294-305, 2009.
   

Wireless Sensor Network

1. Bing-Hong Liu, Wei-Chieh Ke, Chin-Hsien Tsai, and Ming-Jer Tsai, "Constructing a Message-Pruning Tree with Minimum Cost for Tracking Moving Objects in Wireless Sensor Networks is NP-Complete and an Enhanced Data Aggregation Structure," IEEE Transactions on Computers, vol. 57, pp. 849-863, June 2008.
   
   
2. Mário Macedo, António Grilo, and Mário Nunes, "Distributed Latency-Energy Minimization and interference avoidance in TDMA Wireless Sensor Networks," Computer Networks: The International Journal of Computer and Telecommunications Networking, vol. 53, pp. 569-582, April 2009.
   
   
3. Bing Han, J. Leblet, and G. Simon, "Query range problem in wireless sensor networks," IEEE Communications Letters, vol. 13, pp. 55-57, January 2009.

IEEE 802.11 WLANs

1. Huazhi Gong, Kitae Nahm, and JongWon Kim, "Distributed Fair Access Point Selection for Multi-Rate IEEE 802.11 WLANs," 5th IEEE Consumer Communications and Networking Conference, pp. 528-532, January 2008.
   
   
2. Huazhi Gong and JongWon Kim, "Dynamic Load Balancing through Association Control of Mobile Users in WiFi Networks," IEEE Transactions on Consumer Electronics, Vol. 54, No. 2, MAY 2008.
   
   
3. [MBS08] Kimaya Mittala, Elizabeth M. Beldingb, and Subhash Suri, "A game-theoretic analysis of wireless access point selection by mobile users," January 2008.

Game Theory

1. [CMC08] M. Cesana, I. Malanchini, and A. Capone, "Modelling Network Selection and Resource Allocation in Wireless Access Networks with Non-Cooperative Games," 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, pp. 404-409, October 2008.
   
   
2. M. Cesana, N. Gatti, and I. Malanchini, "Game Theoretic Analysis of Wireless Access Network Selection: Models, Inefficiency Bounds, and Algorithms," International Conference On Performance Evaluation Methodologies And Tools & Workshops, 2008.
   
   
3. [JPW08] Libin Jiang, S. Parekh, and J. Walrand, "Base Station Association Game in Multi-cell Wireless Networks," IEEE Wireless Communications and Networking Conference, pp. 1616-1621, March 2008.
   
   
4. S. Shakkottai, E. Altman, and A. Kumar, "Multihoming of Users to Access Points in WLANs: A Population Game Perspective," Multihoming of Users to Access Points in WLANs: A Population Game Perspective, pp. 1207-1215, October 2007.
   
   
5. [Ros73] R. W. Rosenthal, "A Class of Games Possessing Pure-Strategy Nash Equilibria," International Journal of Game Theory, vol. 2, no. 1, pp. 65-67, December 1973.
   
   
6. [Mil96] I. Milchtaich, "Congestion Games with Player-Specific Payoff Functions," Games and Economic Behavior, vol. 13, pp. 111-124, March 1996.
   
   
7. D. Niyato, and E. Hossain, “Dynamics of Network Selection in Heterogeneous Wireless Networks: An Evolutionary Game Approach,” IEEE Trans. Vehicular Technology, vol.58, no.4, pp.2008-2017, May 2009.
   
   
8. Elias Koutsoupias and Christos Papadimitriou, "Worst-case equilibria," Computer Science Review, vol. 3, Issue 2, pp. 65-69, May 2009.
   
   
9. [MS96] D. Monderer and L. S. Shapley, "Potential Games," Games and Economic Behavior 14, pp. 124–143, 1996.

Coverage Game or Problem

1. [ZM09]M. Zhu and S. Mart´ınez, "Distributed coverage games for mobile visual sensors (I): Reaching the set of Nash equilibria," Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, pp. 169-174, December 2009.
   
   
2. [CTL+05]M. Cardei, M. T. Thai, Y. Li, and W. Wu, "Energy-Efficient Target Coverage in Wireless Sensor Networks," IEEE Infocom, 2005, pp.1976–1984.
   
   
3. [LG08]Y. Li and S. Gao, "Designing k-Coverage Schedules in Wireless Sensor Networks," Journal of Combinatorial Optimization, vol. 15, pp. 127–146, 2008.
   
   
4. [AST08]X. Ai, V. Srinivasan and C. Tham, "Optimality and Complexity of Pure Nash Equilibria in the Coverage Game," IEEE Journal on Selected Areas in Communications, vol. 26, no. 7, pp. 1170 - 1182, September 2008.
   
   
5. [CD05]M. Cardei and D. Du, "ImprovingWireless Sensor Network Lifetime through Power Aware Organization," Wireless Networks, vol. 11, no. 3, pp. 333-340, May 2005.
   
   
6. [CP09]M. Chaudhary and A. K. Pujari, "Q-Coverage Problem in Wireless Sensor Networks," Proceedings of the 10th International Conference on Distributed Computing and Networking, Vol. 5408, pp. 325 - 330 , 2009.

[Mil96] Congestion Games with Player-Specific Payoff Functions

這篇論文明確說明了[Ros73]所提出的是congestion game，以及congestion game of symmetric case (即是[Ros73]所提出的)中potential function的存在。它還提出了Nonsymmetric congestion game (就是論文題目所述的game)，說明了這個game和finite improvement property、Nash equilibrium的關係。另外還提出了Weighted congestion game。

[Ros73] A Class of Games Possessing Pure-Strategy Nash Equilibria

這篇論文定義了一種類型的game (其實就是congestion game，但論文中並沒有提到這個名詞)，並證明了這種game會存在pure-strategy Nash equilibrium，在證明過程中有使用到potential function，但是在這時potential game還未被定義，往後很多與game有關的文章都有引用這篇。

[MS96] Potential Games

這篇論文明確地定義了何謂potential game，以及說明了potential game的特性，potential game可分為ordinal potential game、w-potential game和exact potential game三種。它還說明了potential game與equilibrium、finite improvement path、close path、congestion game的關係。每個congestion game都可以找到它的potential function，所以每個congestion game都屬於potential game。

[ZM09] Distributed coverage games for mobile visual sensors (I): Reaching the set of Nash equilibria

這篇論文以game theory來model一個mobile visual sensor的coverage問題。假設有一塊區域，區域以正方形格子狀切割，sensor只能分布在格子中心點，sensor的可偵測區域是一個類似扇形的區域，sensor可以改變它的位置、旋轉角度和焦距來調整它的可偵測區域。要如何增加整體sensor的可偵測區域就是這篇論文所探討的問題，他們提出了restricted game來model此問題，並提出了inhomogeneous synchronous learning (ISL) algorithm來解這個game，最後證明了ISL algorithm可以收斂達到Nash equilibrium。

[JPW08] Base Station Association Game in Multi-cell Wireless Networks

主旨：
　　在無線網路中有複數個Base stations (BS's)可供選擇是相當常見的，如果只根據某些因素來選擇BS (e.g. data rate, signal strength)，可能會導致相當差的system performance。在這篇論文中，提出了一種分散式使用者自私的BS選擇方法，並且嘗試取得較好的系統效能。

問題：
　　假設使用者的數量是非常多而且連續的，要找出如何讓使用者選擇BS，並且使system performance (一個Total utility function，作者自行定義) 達到最高。

解法：
　　作者把鄰近physical location的users視為同一個class，相同class的users將擁有相同的data rate vector，並且提出了兩種BS的scheduling policies，分別是Equal-time allocation by the BS和Equal-throughput allocation by the BS，不同的scheduling policies將導致完全不同的結果，作者證明了若在Equal-time allocation by the BS的情況下，將可以達到optimal system performance。

[CMC08] Modelling Network Selection and Resource Allocation in Wireless Access Networks with Non-Cooperative Games

主旨：
　　傳統802.11 WLANs的AP選擇機制是利用AP的RSSI值來決定(在此篇稱為選擇AN問題)，有throughput unfairness, poor overall performance, and performance anomaly...等問題，本篇以一個non-cooperative games來modle此問題。

問題：
　　傳統802.11 WLANs的AP選擇機制是user選擇一個它所收到AP的RSSI值最大的AP去連接，如此一來，user就會很容易集中連接到某幾台AP，使得AP的Load不均，AP無法負荷，user的throughput也會因此下降。

解法：
　　使用雙層的non-cooperative games來解此問題，先以Interference Based Network Selection Game (INSG) 跑出結果，把INSG中的Nash Equilibrium代入Network Selection and Resource Allocation Game (NSRAG)，再跑出最終結果。

Dynamic Load Balancing through Association Control of Mobile Users in WiFi Networks

主旨：
　　傳統802.11 WLANs的AP選擇機制是利用AP的RSSI值來決定，有throughput unfairness, poor overall performance, and performance anomaly...等問題，本篇提出一個Distributed association algorithm來達到fairness。

問題：
　　傳統802.11 WLANs的AP選擇機制是user選擇一個它所收到AP的RSSI值最大的AP去連接，如此一來，user就會很容易集中連接到某幾台AP，使得AP的Load不均，AP無法負荷，user的throughput也會因此下降。

解法：
　　提出一個Distributed association algorithm，把MU傳送一個packet的時間定義為它帶給AP的load值，一開始MU選擇加入後load較低的AP聯結，然後若MU轉換AP後能使AP取得較低的load，則轉換聯結的AP，最後來比較所有APs的load值的lexicographic order，並且證明了load值的lexicographic order確實會下降(這部分有點問題)。

[MBS08] A game-theoretic analysis of wireless access point selection by mobile users

主旨：
　　傳統802.11 WLANs的AP選擇機制是利用AP的RSSI值來決定，有unfairness和poor overall performance等問題，這篇論文引入game theory來探討如何選擇較合適的AP。

問題：
　　傳統802.11 WLANs的AP選擇機制是user選擇一個它所收到AP的RSSI值最大的AP去連接，如此一來，user就會很容易集中連接到某幾台AP，使得AP的Load不均，AP無法負荷，user的throughput也會因此下降。

解法：
　　在802.11 AP選擇問題上引入了game theory，提出一個Cost function來作為選擇AP的依據，並且證明了依照此Cost function所選擇的結果必定會符合Nash equilibrium。

Q:
　　下圖關於traveled distance的關係?


A:
　　MIST固定為300，MIAT為3、10、30，比值 MIST/MIAT = 100、30、10，我們可以知道MIST/MIAT越大，則平均在系統內的user數較多，因此比較多user被迫於去選擇較遠的AP，traveled distance較大，而Simultaneous exit同時在系統內的user數最多，因此traveled distance最大。

Distributed Fair Access Point Selection for Multi-Rate IEEE 802.11 WLANs

主旨：
　　由於傳統802.11 WLANs的AP選擇機制是利用AP的RSSI值來決定，有unfairness和poor overall performance等問題，這篇論文提出一個更好的選擇機制，使得users的throughput更加fairness。

問題：
　　傳統802.11 WLANs的AP選擇機制是user選擇一個它所收到AP的RSSI值最大的AP去連接，如此一來，user就會很容易集中連接到某幾台AP，使得AP的Load不均，AP無法負荷，user的throughput也會因此下降，這篇論文定義了一個Max-min MUs throughput fairness做為最終目標。

解法：
　　這篇論文提出了一套Distributed AP selection algorithm，以AP的Load作為選擇的機制，新加入的user會去選擇加入後Load較小的AP做連接，已存在的user則會定時去偵測AP的Load，並且決定要不要更換到其他AP。

Optimizing Multi-hop Queries in ZigBee Based Multi-sink Sensor Networks

主旨：
　　本篇論文以Zigbee架構來實行Wireless sensor network(WSN)，在Infrastructure-less的WSN中，users的impact range會影響到sensor的load，本篇論文提到一個決定impact range的演算法，使得users的load可以達到所謂的max-min fairness。

問題：
　　本篇論文將決定impact range的問題轉換成一個Multi-dimensional Multiple Choice Knapsack Problem，並提出演算法達到Max-Min Fair impact range。

解法：
　　提出一套演算法達到Max-Min Fair impact range。

TDBS: a time division beacon scheduling mechanism for ZigBee cluster-tree wireless sensor networks

主旨：
　　本篇論文為了要在ZigBee cluster-tree結構下實行synchronization，因此必須解決在執行synchronization時所遇到的beacon碰撞問題，論文中說明了此問題如何而來，並且提供了解決方法與詳細的實做步驟。

問題：
　　在ZigBee cluster-tree結構下，ZC與ZR發送beacon時會有所謂的Direct beacon frame collisions problem及Indirect beacon frame collisions problem。

　　Direct beacon frame collisions problem是發生在ZR1與ZR2與被干擾點N1，ZR1與ZR2彼此都在各自的傳輸範圍內所發生的。

　　Indirect beacon frame collisions problem則是在ZR1與ZR2彼此都在傳輸範圍外，因此ZR1與ZR2彼此無法得知各自的存在。

解法：
　　Task Group 15.4b針對這個問題提出了兩個基本解法，分別是 (1) The time division approach (2) The beacon-only period approach ， (1) 解法是以將各ZR的beacon和supergframe的時間分開，已達到避免衝撞的目的，(2) 解法是將所有beacon都放到最前端的時間點，將各beacon排序後，按照順序傳遞beacon，所有beacon都傳完後再傳遞superframe。

　　這篇論文以 (1) 方法為主，提供了一個time division beacon scheduling mechanism(TDBS)來解決衝撞問題。

The Orphan Problem in ZigBee Wireless Networks

主旨：
　　點出Zigbee tree-based結構中，存在所謂的Orphan問題，將此問題切割，提出數個演算法來解決它，並以實驗數據佐證。

問題：
　　Zigbee樹狀網路中，由於存在位置分配的限制，使得部分的devices無法加入此網路，此paper將Orphan問題切割為兩個子問題，（1）儘可能連接較多的router（2）進可能連接較多的end-device，並將兩個子問題分別model成Bounded-degree-and-depth tree formation problem (BDDTF) 及End-Device Maximum Matching problem (EDMM) 。

解法：

1. 針對BDDTF problem，提出了Centralized Span-and-Prune Algorithm和Distributed Depth-then-Breadth-Search Algorithm 。
   
   
2. 對於EDMM problem，介紹了Centralized maximum matcing Algorithm以及提出了Distributed matching Algorithm。

The Room Shortage Problem of Tree-Based Zigbee/IEEE 802.15.4 Wireless Network

主旨：
　　介紹Zigbee的Addresses分配方式Distributed Address Assignment Mechanism（DAAM），並且點出其中的問題所在，針對這些問題提出解法，並且以實驗數據佐證這些解法確實有效。

問題：
　　DAAM中有所謂的Address shortage problem、Room shortage problem以及Routing detour problem，第一個問題較不重要，在此針對第二、三的問題提出三種方法取代DAAM。

解法：

1. Centralized Stateful Address Configuration (CSAC)，最具靈活性的一種方法，利用ZC分配devices位置，因此devices必須建立Routing Table，所以也是Storage Cost最高的方法。
   
   
2. Hybrid Address Configuration (HAC)，混合DAAM和CSAC的一種方法，以DAAM為優先，若DAAM無法使用，則用CSAC來取代其不足。
   
   
3. Router-Based Address Configuration，CSAC的改良版，使用一個固定的Block Size來分配位置，有效減少了Storage Cost，但靈活性也因此降低，在此Paper中RBAC被認為是最好的方法。