1. An Energy-Efficient Flooding Algorithm in ad hoc Network (EFA) Concrete Mathematic Final presentation of term project Professor: Kwangjo KimKwangjo Kim Group 16: Tran Minh Trung, Nguyen Duc Long

2. An Energy-Efficient Flooding Algorithm in Ad-Hoc Network (EFA) Related Works Problem statement Proposed Solution Simulation & Evaluation

3. Related Works Related work (Previous paper: PAODV, APRA, MMBCR) Congested node, Week node: Reject or relay the coming connection - > Reduce the network connectivity Single path from source to destination: Slow transmission speed, Increase control packet over head -> Waste energy Disjoint a single path in to multiple paths (dependent on energy capacity of each sub path) Balance the power consumption between Strong node and week node -> reduce the partition problem (1) Increase Network Connectivity -> Reduce routing discovery phase (2) 1,2 -> Increase Network life time Proposed solution

4. Problem statement (1) Run “Routing discovery phase” again many times -> Waste time + Energy consuming Run “Routing discovery phase” fewer time -> Save time, Energy

5. Problem statement (2) Ad Hoc model: Directed Graph G(V, E) where V is the set of all nodes and E is the set of all directed links (i, j) where i, j  V. N i Set of all neighbors nodes of node (i) (i) (j) - Directed graph: G (V,E) - Weighted link: E (i,j) - Set of neighbor node: N (i)

6. Problem statement (2) Node (i) Energy available: In case of serving j node at the same time Otherwise ∑f (j,i) =∑f (i,k) e (i) = e r(i) - e rq(i) e (i) = e r(i) f(j,i) f(i,k) i

7. Problem statement (3) Directed link (i,j) exist if and only if J  N i Energy capacity of link (i,j) Life time of a routing path = Life time of each link or each node Source e (1) =10 e (2) =40 Dest. e (3) =60 e (4) =40 Link 1: e (sd) = Min (e (3),e (4) )=40 Link 2: e (sd) = Min (e (1),e (2) )=10 … e (i,j) = Min (e (i),e (j) ) e (5) =10

8. Path 1 is created with energy capacity = 8, Hop count = 3 RREQ Flooding method RREQ10RREQ(1)4 4RREQ(2)8 8 8 Path 1 is created with energy capacity = 4, Hop count = 4 RREQ(1)4 8

9. Lexicographic order A routing path will be chosen dependent on 3 information Fresh sequence number: F (i) Min Energy capacity: E (i) Hop count to destination: H (i) The path will be selected dependent on lexicographic order Path i: (F (i), E (i), H (i) ) The number of path is dependent on the total energy requirement, and the energy available of all possible paths

10. X X X X The mesh network example (1) X X X X X X X X X X X X Node with energy level 2 Node with energy level 3 Node with energy level 1 RREQ for link level 1 RREQ for link level 2 RREQ for link level 3 Full capacity: 10 Capacity levels: - Level 1: 1 -> 4 - Level 2: 4 -> 7 - Level 3: 7 -> 10 Eliminated because of containing weaker node Eliminated because of backward flooding (Increase hop count)

11. The mesh network example (2) Node with energy level 2 Node with energy level 3 Node with energy level 1 RREP for link level 1 RREP for link level 2 RREP for link level 3 Full capacity: 10 Capacity levels: - Level 1: 1 -> 4 - Level 2: 4 -> 7 - Level 3: 7 -> 10

12. Simulation & Evaluation(1) Simulation model: 10 - 50 mobile nodes are generated randomly in an area of 500M*500M. The moving speed of each node is 5m/s. 2-20 connections is established during 900 seconds simulation times. The energy model: initial energy of each node is 20mW. The energy usage for receiving and sending each packet are txPower = 0.6mW and rxPower = 0.3mW respectively.

13. Simulation & Evaluation(2) Expiration sequences of nodes Routing overhead (control messages)

14. Simulation & Evaluation(3) Route reliability End to End Delay

15. Conclusion (1) Final achievement: Use concrete mathematic knowledge for writing higher quality paper Graph theory Directed graph Weighted link Lexicographic Order Set theory Experiences in dealing with NS2, Perl, gnuplot

16. Conclusion (2) Contribution: Proposed new Energy-Efficient Flooding Algorithm for Ad-Hoc routing protocol Simulation results shows betters performance Future plan: Complete full paper (With more different & complicated scenarios – mobility measurement) After getting review & advice from Profesor -> submit to international conference Apply some Stochastic and Mathematical model -> Journal paper

17. Progress after midterm report Writing simulation program by NS2 ( Tran Minh Trung) Generate scenarios by TCL script Apply energy model to standard scenarios Write simulation results to log files Analisys simulation log files ( Nguyen Duc Long) Write perl modules (Collect & Split data) Write drawing script by gnuplot (linux)

18. Reference Paper: T.M Trung, S.-L. Kim, “An Adaptive Power Aware Routing Algorithm for Ad Hoc Networks”, Submitted to ICWC – Toronto Canada 2003 H.X.Tung, T.M Trung, V.D Liem, P.V Su, “Power – Aware Ad-Hoc Ondemand Distance Vector Routing Protocol”, KISA 2003 Charles E. Perkins, Elizabeth M. Belding-Royer, and Samir Das. "Ad Hoc On Demand Distance Vector (AODV) Routing." IETF Internet draft, draft-ietf-manet-aodv-10.txt, March 2002 (Work in Progress)."Ad Hoc On Demand Distance Vector (AODV) Routing." C.-K. Toh, H. Cobb, and D.A. Scott, “Performance evaluation of battery-life aware routing schemes for wireless Ad Hoc Networks” in Proc. IEEE, ICC Books & Link: Discrete Mathematics and Its Applications, 4th edition, Kenneth H. Rosen, McGRAW- HILL, 1999 http://mathworld.wolfram.com/LexicographicOrder.html