Algorithms for Routing and Centralized Scheduling in IEEE Mesh Networks Harish Shetiya and Vinod Sharma Department of Electrical Communication Engineering Indian Institute of Science WCNC 2006

Outline  Introduction  System Model  Routing  Scheduling Algorithm  Simulation  Conclusion

Introduction  The IEEE d specifies a centralized scheduling scheme for mesh networks  The MSSs notify the MBS Data transfer requirements The quality of their links to their neighbors  The MBS uses the topology information along with the requirements of each MSS to decide the routing and the scheduling

System Model  MSSs are labeled 1,2,3 …… M need not be directly connected to the MBS  MBS is labeled by 0  Each node has infinite buffer to store the packets

Routing 1 M 2 BS a frames consisting of N time slots I 點的資料經過 J 點的 平均速率 P 2,1 P 2,0

Scheduling Algorithm  Tree Dynamic Programming Framework Maximum Transmission Scheme Per Slot Maximum Transmission Scheme Maximum Work Scheme Fixed Allocation Scheme Adaptive Fixed Allocation Scheme Order scheme  Downlink Scheduling Algorithm

Tree Dynamic Programming Framework_ Tree Structure BS A frame has N slots

Tree Dynamic Programming Framework_ Uplink Scheduling denote the maximum data extracted from node i in k slots denote the maximum reward obtained from node i in k slots

Tree Dynamic Programming Framework_ Maximum Transmission Scheme Construct a table : (1)First get: (2)then get: A B C rbrb rara rcrc

Tree Dynamic Programming Framework_ Example (schedule b, c) BS A A frame has N slots, One slot 1 s B C 6 M 2 M/S 2 M 1 M/S 3 2 k 值 {node} N {} {B} {B,C} (1,0)(2,0)(3,0)(3,1)(3,2)

Tree Dynamic Programming Framework _ Example (schedule a, b, c) Construct a table : B,c 在 (k-n) 個 slots 所傳的資料 量 min{A 點 queue 中的資料量 +(b,c 傳進的資料量 ), A 能傳送的資料量 } A B C rbrb rara rcrc

Tree Dynamic Programming Framework_ Example (schedule a, b, c) A frame has N slots, One slot 1 s k 值 {node} N {B,C} 0 (0,0) 2 (1,0) 4 (2,0) 6 (3,0) 7 (3,1) 8 (3,2) 8 {A,B C} 0 (0,0) 4 (1,0) 8 (2,0) 10 (2,1) 12 (2,2) 16 (3,2) BS A B C 6 M 2 M/S 2 M 1 M/S 3 2 8M 4M/S

Tree Dynamic Programming Framework_ Example (schedule b, c) A frame has N slots, One slot 8 s BS A B C 6 M 2 M/S 8 M 1 M/S k 值 {node} N {B, C} 0 (0,0) 8 (0,1) 14 (1,1) 14

Tree Dynamic Programming Framework_ Per Slot Maximum Scheme Suboptimal version of Maximum transmission scheme i 點的傳 輸 rate i 點的 queue 資 料量 A3M4M/s B5M2M/s C25M/S

Tree Dynamic Programming Framework_ Maximum Work Scheme Total work in the system at the beginning of the jth frame (work is the time to extract entire data from the network ): 1 M 2 BS P 2,1 P 2,0

Tree Dynamic Programming Framework_ Maximum Work Scheme b,c 所需 的時間 a 所須的 時間 A B C rbrb rara rcrc 7 M 3 M/S 1M 1M/S 1 3 Slot Full Slot

Tree Dynamic Programming Framework_ Fixed Allocation Scheme 其他點經過 I 的 資料量

Tree Dynamic Programming Framework_ Adaptive Fixed Allocation Scheme(1) denote the set of good and bad links Ex. First round: is the upper bound of accumulated credit

Tree Dynamic Programming Framework_ Adaptive Fixed Allocation Scheme(2) second round: Slots to assign good link

Tree Dynamic Programming Framework_ Order Scheme To get the order: The slot is assigned to node :, i has higher rate of data delivery to MBS + E點:E點: ++ = 1

Tree Dynamic Programming Framework_ Downlink Scheduling Algorithm  there are M possible destinations in the downlink. Hence we need to track the data as it passes through the network.  Since all the traffic originates at the MBS. Hence, using schemes for the downlink in a manner that is analogous to the uplink.

Simulation Mesh network of 10 nodes

Simulation_ Physical Layer Parameter

Simulation_ Burst Profile

Simulation_ comparison of uplink scheduling scheme

Simulation_ Comparison between different Fixed Allocation Scheme

Simulation_ Comparison between different Maximum Transmission Scheme

Simulation_ Comparison of downlink scheduling scheme

Conclusion  To develop efficient routing and scheduling algorithm for multihop wireless networks as formed by IEEE standard