Advisor: Dr. Frank Y. S. Lin Presented by Pei-Wei Li A Low-latency and Energy-efficient Scheduling Algorithm for Multi-group Multicasting in Mobile Ad Hoc Networks 具移動性隨意網路下多群組群播之 低延遲與能耗排程演算法 進度報告 Advisor: Dr. Frank Y. S. Lin Presented by Pei-Wei Li

Outline Problem Description Heuristics for getting primal feasible solutions Schedule

Problem Description Step1: construct a multicast tree for each multicast source to reach its group members Step 2: schedule the transmission time of the nodes on these multicast trees and avoid the collision of transmission Objective: minimize the latency of multicasting Consider the mobility of nodes and the energy consumption of transmission.

Problem Description

Problem Description Source 4 6 Source 5 1 7 8 2 3

Problem Description

Problem Description Assumption We get the location and mobility information of all nodes from GPS. Prediction of velocities and oncoming positions of nodes can be provided by Gauss-Markov mobility model. Transmission time can be divided into discrete slots. All nodes in the network have their clocks synchronized. Packet propagation delay can be ignored. Each multicast source has single data to send.

Problem Description

Problem Description Objective function

Heuristics for getting primal feasible solutions

Heuristics for getting primal feasible solutions s

Heuristics for getting primal feasible solutions =2 =3 max_t=2 max_t=3 =4 =3 =5 =1 max_t=4 max_t=5 max_t=3 max_t=1

Heuristics for getting primal feasible solutions max_t=-1 max_t=2 max_t=3 max_t=2 max_t=0 max_t=5 max_t=4 max_t=3 max_t=1

Heuristics for getting primal feasible solutions max_t=0 max_t=3 max_t=1

Heuristics for getting primal feasible solutions max_t=0 max_t=1 max_t=0 max_t=1 max_t=3 max_t=2 max_t=3 max_t=1 =2 max_t=3 =1 =3

Heuristics for getting primal feasible solutions Multicast tree 1: A.B.C.D.E node[A][A].t=1 node[B][A].t=2 Multicast tree 2: F.C.E.G.H node[F][F].t=1 node[C][F].t=2 node[E][F].t=3 A F B C G D E H

Heuristics for getting primal feasible solutions v=1 node[A][A].t=1 set1:A node[F][F].t=1 set2:F B C G D E H

Heuristics for getting primal feasible solutions set1:A set[1].t=2 set2:F set[2].t=1 2 1 B C 3 4 node[F][F].t=1 node[C][F].t=2 node[A][A].t=2 node[E][F].t=3 node[B][A].t=3 G D E 4 H

Heuristics for getting primal feasible solutions v=2 node[A][A].t=2 set1:A node[C][F].t=2 set2:C B C G D E H

Heuristics for getting primal feasible solutions set1:A set[1].t=2 set2:C set[2].t=3 A F 2 1 B C 3 4 node[A][A].t=2 node[B][A].t=3 node[C][F].t=3 node[E][F].t=4 G D E 4 H

Heuristics for getting primal feasible solutions v=3 node[B][A].t=3 set1:B node[C][F].t=3 set2:C B C G D E H

Heuristics for getting primal feasible solutions set1:B set[1].t=4 set2:C set[2].t=3 2 1 B C 3 4 G D node[C][F].t=3 node[B][A].t=4 node[E][F].t=4 E 4 H

Heuristics for getting primal feasible solutions v=4 node[B][A].t=4 set1:B node[E][F].t=4 set2:E 2 1 B C 3 set1:B set[1].t=4 set2:E set[2].t=4 4 G D E 4 H

Heuristics for getting primal feasible solutions 6 4 G G E E 5 4 D D H H

Heuristics for getting primal feasible solutions set1:B set[1].t=6 set2:E set[2].t=4 node[E][F].t=4 node[B][A].t=5 B C 6 G E 4 D H

Schedule 2009.3~2009.4 — Coding、實驗設計 2009.5 — 問題處理 (包括修改heuristic、調整參數) 2009.6 — 實驗數據整理、論文撰寫 2009.7 — 論文口試