Advisor: Professor Yeong-Sung Lin Student: Yeong-Cheng Tzeng (曾勇誠) Fair Intra-TAP Temporal and Throughput (Delay) Routing Algorithms in Mesh Networks Advisor: Professor Yeong-Sung Lin Student: Yeong-Cheng Tzeng (曾勇誠)

Outline Introduction Problem Description Related Work Motivation Notation Problem Formulation Relaxation Subproblem and Solution Approach

1. Introduction WiFi networks have become increasingly popular: Clients need to be in the immediate vicinity of the Internet HS Have to deploy hot spots at well-chosen locations Wireless Mesh Networks: An extension of WiFi The TAPs are not directly connected to the Internet

1. Introduction (cont’d) If the protocol is poorly designed Severe unfairness (starvation) Low bandwidth utilization Issues: Fairness Backhaul deployment

1.1. Related Work Mesh Networks I. F. Akyildiz, X. Wang, and W. Wang. Wireless Mesh Networks: A Survey. Computer Networks Journal (Elsevier), 47(4), 2005. Present a survey on recent advances and open research issues in WMNs Point out an important research topic: Revise the design of MAC protocols based on TDMA or CDMA

1.1. Related Work (cont’d) Fairness in Mesh Networks V. Gambiroza, B. Sadeghi, and E. Knightly, “End-to-End Performance and Fairness in Multihop Wireless Backhaul Networks" in Proceedings of MobiCom 2004. Chain topology Temporal fairness (max min channel access time)

1.2. Motivation To propose a fair resource allocation algorithm that achieves: Optimize backhaul deployment Minimize maximum end-to-end delay Assign bandwidth to the links in the WMN Min max delay fairness

2. Problem Description

2.1. Problem Description Given The network topology includes TAP set and link set. The capacity of all links. The set of all candidate backhauls. The total budget to build up the backhauls. The cost of building backhaul. The set of all candidate paths from each TAP to backhaul. Data rate of each TAPs required to be transmitted.

2.1. Problem Description Objective: Subject to: To determine: To minimize the maximum end-to-end transmission delay. Subject to: The backhaul assignment with budget constraints will be considered. Routing constraints will be considered. Tree constraints will be considered. The TAPs must route to the “to-be-determined” backhaul with delay time and capacity constraints. To determine: Backhaul deployment Routing assignment Bandwidth allocation

2.2. Notation Given Parameters Notation Description V The set of TAPs which is also the set of candidate backhauls, where v  V. B The set of candidate backhauls, where b  B. θ The budget to build up the backhaul. cb The cost to build the backhaul b. Pbs The set of paths from original TAP s to destination TAP b or vice versa, where p  Pbs. puv Indication function, which denote link uv on the path p. Cuv The capacity of link uv. as Required data rate of TAP s. ε Estimated error.

2.2. Notation (cont’d) Decision Variables Notation Description b 1 if TAP b is selected to be a backhaul; otherwise 0. zbs 1 if TAP s connects to wired network via backhaul b; otherwise 0. xp 1 if path p from TAP, s, to TAP b is selected; otherwise 0. yuv 1 if link uv is on the tree; otherwise 0. bsuv Bandwidth allocation to TAP s on link uv. tsuv Data transmission delay of TAP s on link uv. T Maximum end-to-end delay from each TAP to associated backhaul.

2.3. Problem Formulation Objective function subject to

2.3. Problem Formulation (cont’d)

2.3. Problem Formulation (cont’d)

2.4. Relaxation We can transform (IP) into LR problem where Constraints (1), (2), (3), (6), (8), (9), (10), (12), (13), (14), and (16) are relaxed. Optimization Problem (LR):

2.4. Relaxation (cont’d) subject to

2.4. Relaxation (cont’d)

2.5. Subproblem and Solution Approach Subproblem1 (related to decision variableηb) subject to solution

2.5. Subproblem and Solution Approach (cont’d) Subproblem2 (related to decision variable zbs) subject to solution 1. Decompose into |V| independent subproblems 2. Calculate the coefficient of zbs 3. For all coefficients in ascending, we assign the first zbs=1 , others 0.

2.5. Subproblem and Solution Approach (cont’d) Subproblem3 (related to decision variable xp) subject to solution (SUB 3) can be decomposed into |V| independent shortest path problems

2.5. Subproblem and Solution Approach (cont’d) Subproblem4 (related to decision variable yuv) subject to solution

2.5. Subproblem and Solution Approach (cont’d) Subproblem5 (related to decision variable bsuv) subject to

2.5. Subproblem and Solution Approach (cont’d) Subproblem6 (related to decision variable tsuv) subject to

2.5. Subproblem and Solution Approach (cont’d) Subproblem7 (related to decision variable T) subject to

The End