Adjusted Counter-Based Broadcast for Wireless Mobile Ad hoc Networks

1. Adjusted Counter-Based Broadcast for Wireless Mobile Ad hoc Networks Sara Omar al-Humoud Department of Computing Science University of Glasgow First Year Viva Supervisors: Dr. L.M. Mackenzie and Dr. M. Ould-Khaoua

2. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

3. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

4. Introduction MANETs Characteristics and Limitations • MANETs? • Decentralized • Dynamic topology • Radio communication • Energy constrained

5. Introduction MANET Applications • Military applications • Collaborative and distributed computing • Emergency operations • Inter-Vehicle Communications • Hybrid wireless networks

6. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

7. Introduction Routing in MANET • Table Driven Routing Protocols (Proactive) • Destination-Sequenced Distance-Vector Routing (DSDV) • Clusterhead Gateway Switch Routing (CGSR) • Global state routing (GSR) • Source-tree adaptive routing (STAR) • Fisheye state routing (FSR) • Distance routing effect algorithm for mobility (DREAM) • Optimised link state routing (OLSR) • Topology broadcast reverse path forwarding (TBRPF) • Wireless Routing Protocol (WRP)

8. Introduction Routing in MANET • Source-initiated On-demand Routing (reactive) • Ad-hoc On-Demand Distance Vectoring (AODV) • Dynamic Source Routing (DSR) • Temporally-Ordered Routing Algorithm (TORA) • Associativity Based Routing (ABR) • Light-weight mobile routing (LMR) • Routing on-demand acyclic multi-path (ROAM) • Relative distance micro-discovery ad hoc routing (RDMAR) • Location-aided routing (LAR) • Ant-colony-based routing algorithm (ARA) • Flow oriented routing protocol (FORP) • Cluster-based routing protocol (CBRP) • Signal Stability Routing (SSR)

9. Introduction Routing in MANET • Hybrid routing protocols • Zone routing protocol (ZRP) • Zone-based hierarchical link state (ZHLS) • Scalable location update routing protocol (SLURP) • Distributed spanning trees based routing protocol (DST) • Distributed dynamic routing (DDR)

10. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

11. Introduction Broadcasting Applications • Discovering neighbours • Collecting global information • Addressing • Helping in multicasting and Unicast • Route discovery, route reply • in on-demand routing protocols like DSR, AODV to broadcast control messages. • Conventionally broadcast is done through flooding

12. Introduction Broadcasting Applications • Flooding may lead to • Redundancy x Consume limited bandwidth • Contention x Increase in delay • Collision x High packet loss rate • Broadcast storm problem! f(n) = n2 – 2n + 1

13. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

14. Related work Probability-based Rebroadcast with probability P Counter-based Rebroadcast if the node received less than Cth copies of the msg Location-based Rebroadcast if the area within the node’s range that is yet to be covered by the broadcast > Ath Distance-based Rebroadcast if the node did not receive the msg from another node at a distance less than Dth Probabilistic Broadcasting Methods Receiver rebroadcast decision Simple Implementation RD based on instantaneous information from broadcast msgs

15. Related work Reliable Broadcast Self-pruning Scalable broadcasting Dominant Pruning Cluster-based Deterministic Broadcasting Methods Sender rebroadcast decision Elaborate Implementation Rebroadcast decision based on neighbourhood study

16. Related work Counter-based broadcast Adaptive Counter-based broadcast Color-based broadcast Distance-aware counter-based broadcast Counter-Based related Broadcasting Methods

17. Related work 1- Counter-based broadcast Scheme: When receiving a message: a counter c is set to keep track of number of duplicate messages received. Random Assessment Delay (RAD) timer is set. When the RAD timer expires the counter is tested against a fixed threshold value C, broadcast is inhibited if c ≥ C. Remarks: The threshold is fixed: scores high efficiency only when used with homogeneous density networks; when the network is sparse a high threshold is used and when dense low threshold value. Adaptive Counter-based broadcast Threshold = C(n) where n is the number of neighbors The function C(n) is undefined yet Counter-Based related Broadcasting Methods 17

18. Related work 2- Color-based broadcast Scheme: each broadcast node selects a color from a set of η colors which it writes to a color-field present in the broadcast message. all nodes which hear the message rebroadcast it unless they have heard all η colors by the time a random timer expires. Remarks: With the added overhead, we may end with a bad case: E.g. a node receive 3 messages with only c1 and this node will still rebroadcast the message. Counter-Based related Broadcasting Methods 18 c1 c2 c3

19. Related work 3- Distance-aware counter-based broadcast Scheme: Similar to the counter-based scheme in addition to: Two distinct RADs are applied to the border and interior nodes SRAD to border nodes LRAD to interior nodes Remarks: The use of distance as an enhancement factor to the original counter-based may be degraded knowing that real networks transmissions will be affected by obstacles. Counter-Based related Broadcasting Methods 19

20. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

21. Motivations and objectives Area-based scheme Rely on GPS Deterministic approaches High time overhead High number of control messages exchanged to broadcast one packet it demands accurate neighbourhood information and cannot ensure the coverage with outdated topology information. Related work limitations - overhead

22. Motivations and objectives Counter-based schemes Fixed counter-based Threshold = c Adaptive counter-based Threshold = C(n) where n is the number of neighbors The function C(n) is undefined yet Color-based Used with homogeneous density networks Rebroadcast when many duplicates received by the a partial set of colors Distance-aware counter-based Distance estimated by signal strength Not considering obstacle existence Related work limitations - overhead

23. Motivations and objectives Adjusted Counter-Based (ACB) Highly Adjusted Counter-Based (HACB). Counter-Based AODV Adjusted Counter-Based AODV Highly Adjusted Counter-Based AODV Study the superiority of our proposed schemes to the probabilistic broadcasting Objectives

24. Motivations and objectives Adjusted Counter-Based (ACB) Broadcast Based on the original counter-based scheme Add the ability to decide the counter according to neighbourhood density Neighbourhood density is divided according to the Average number of neighbours into: Density1: Sparse Density2: Dense Objectives Sparse Dense Neighbourhood Density Avg

25. Motivations and objectives Highly Adjusted Counter-Based (HACB) Broadcast Neighbourhood density is divided according to the Max and Min number of neighbours into: Density1: Sparse Density2: Medium Density3: Dense Adding the average as a discriminator will divide the neighbourhood density into four groups and will reveal a better adjustment Objectives Sparse Medium Dense Neighbourhood Density Min Max

26. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

27. Thesis Statement Go to Thesis Statement Cont

28. Thesis Statement T1.While most previous studies have used a fixed counter threshold for rebroadcasting irrespective of the node status, this research proposes two new counter-based algorithms that dynamically adjust the counter threshold as per the node’s neighbourhood distribution and node movement using one-hop neighbourhood information. Employing neighbourhood information in counter threshold decision will enhance the existing fixed counter-based flooding in terms of reachability, saved rebroadcast and delay. T1

29. Thesis Statement T2. The AdjustedCounter-Based (ACB) uses the average number of neighbour to dynamically adjust the threshold value to adapt to either sparse or dense network. Moreover, when incorporated in the Ad hoc On-Demand Distance Vector (AODV) routing protocol; one of the well-known and widely studied routing protocols over that past few years, ACB will perform better than both standard and fixed counter-based AODV protocols. T2

30. Thesis Statement T3. The Highly Adjusted Counter-Based (HACB) uses three items of derived neighbourhood information the maximum, the minimum in addition to the average number of neighbours to dynamically adjust the threshold value. HACB is better than ACB however, perhaps with an added complexity. Moreover, when incorporated in the AODV routing protocol; HACB will perform better than both standard and fixed counter-based AODV protocols. Additionally, it will perform better than probabilistic and adjusted probabilistic AODV routing protocols. T3

31. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

32. Contributions Algorithms Cont

33. Adjusted_Counter_Based_Broadcast_Algorithm • Pre: avg is average number of neighbors • a broadcast packet m at node X is heard • Post: rebroadcast the packet or drop it, according to the algorithm • Get the Broadcast ID • Get degree n of node X • Set RAD • c = 1 • If n < avg then • Sparse network • threshold = c1; • Else • Dense network • threshold = c2; • End if • While (RAD) Do • If (same packet heard) • Increment c • End while • If (counter > threshold) • drop packet • exit algorithm • End If • Submit the packet for transmission • End Adjusted_Counter_Based_Broadcast_Algorithm

34. Highly_Adjusted_Counter_Based_Broadcast_Algorithm • Pre: avg is average number of neighbors • min is minimum number of neighbors • max is maximum number of neighbors • a broadcast packet m at node X is heard • Post: rebroadcast the packet or drop it, according to the algorithm • Get the Broadcast ID • Get degree n of node X • Set RAD • c = 1 • If n < min then • threshold = c1; • Else • If n < max then • threshold = c2; • Else • threshold = c3; • End if • End if • While (RAD) Do • If (same packet heard) • Increment c • End while • If (counter > threshold) • drop packet • exit algorithm • End If • Submit the packet for transmission • End Highly_Adjusted_Counter_Based_Broadcast_Algorithm

35. Contributions Simulation study Firststudyconsiders a static network, using a Null MAC to evaluate and compare our proposed algorithms to simple flooding, the worst case. Secondstudyconsiders the network under two sources of instability: Mobility: changeable node speed. Congestion: variable quantities of packets originated per second. Thirdstudyconsiders a combination of variable node density, node speed, and congestion. Methodology

36. Contributions Reachability r/e, where r is the number of hosts receiving the broadcast packet and e is the number of mobile hosts that are reachable, directly or indirectly, from the source host . Saved Rebroadcast (r − t)/r, where r is the number of hosts receiving the broadcast message, and t is the number of hosts that actually transmitted the message. Average latency the interval from the time the broadcast was initiated to the time the last host finished its rebroadcasting. Performance measures

37. Contributions Simulate a university campus with the following assumptions: Existence of pedestrians and vehicles equipped with IEEE 802.11 wireless transceivers Speed: walk speed of 1 m/sec with appropriate pose times to vehicles having a maximum speed of 70 km/hour Area: First study: open unobstructed Second study: open with obstacles Mobility: First study: Random way point (RWP) mobility model Second study: Realistic Mobility Model We assume that a host can detect duplicate broadcast messages. Assume that nodes have sufficient power to function properly throughout the simulation time Assumptions

38. Contributions Simulation parameters

39. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

40. Tentative work plan Assumptions

41. Outline Characteristics & Limitations Applications MANETs 1.Introduction Routing Proactive Broadcasting Reactive 2.Related work Hybrid Probabilistic Deterministic 3.Motivations and objectives Counter Related 4.Thesis Statement ACB 5.Contributions Algorithms HACB Methodology Simulation study 6.Tentative work plan Measures Assumptions 7.Thesis structure

42. Thesis structure Chapter 1: Introduction MANET Broadcasting Related work Motivation Contribution Thesis statement Chapter 2: Background and related work Introduction Fixed counter-based broadcasting Chapter 3: Adjusted Counter-based Broadcasting Introduction Adjusted counter-based broadcasting Analysis on Adjusted counter-based Comparison between Fixed and Adjusted Counter-based Chapter 4: Highly Adjusted Counter-based Broadcasting Introduction Highly Adjusted counter-based broadcasting Analysis on Highly Adjusted counter-based Comparison between Adjusted and Highly Adjusted Counter-based Chapter 6: Performance Evaluation of AODV with Adjusted Counter-based Route Discovery Chapter 7: Performance evaluation of Counter-Based with Real mobility model Chapter 8: Conclusions and Future Work 42

43. Questions

44. (a) (b) EAC