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

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

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

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

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

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

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7 Introduction 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) Routing in MANET

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8 Introduction 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) Routing in MANET

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9 Introduction 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) Routing in MANET

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

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11 Introduction 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 Broadcasting Applications

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

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

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

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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

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16 Related work 1.Counter-based broadcast –Adaptive Counter-based broadcast 2.Color-based broadcast 3.Distance-aware counter-based broadcast Counter-Based related Broadcasting Methods

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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

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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 c1 c2 c3

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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

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

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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

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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

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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

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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 Avg SparseDense Neighbourhood Density

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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 SparseDenseMedium MinMax Neighbourhood Density

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

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Thesis Statement 27 Go to Thesis Statement Cont

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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 nodes 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

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29 Thesis Statement T2. The Adjusted Counter-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

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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

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

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Contributions 32 Algorithms Cont

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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

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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 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

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

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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

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37 Contributions Simulate a university campus with the following assumptions: –Existence of pedestrians and vehicles equipped with IEEE 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

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Contributions 38 Simulation parameters Simulation parameterValue Simulatorns-2 version (2.31) Network Area1500 x 1500 meter Transmission range100 meter Data Packet Size64 bytes Node Max. IFQ Length50 Simulation Time500 sec Pause Times0, 10, 20, 40 sec Number of Trials10 MAC layer protocolIEEE Mobility modelRandom waypoint model, Realistic Mobility Model Traffic TypeCBR (Constant Bit Rate) Channel Bandwidth2Mb/sec Confidence Interval 95% Number of Nodes20, 40, 50, 60, 80, 100 Packet Rate10, 20, 40, 60, , 150 packets per sec Counter threshold pairsACB: [2,3], [2,4], [3,4], HACB [2,3,4] Node Max. Speed1, 5, 10, 15, 20 m/sec

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

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Tentative work plan 40 Assumptions IDTaskEnd Date 1Submit my first year reportJuly/2007 2Experiment with ns2 simulatorAugust/2007 3Develop adaptive counter-based (ACB) schemeNov/2007 4Compare ACB with counter-based (CB) schemeDec/2007 5Develop Highly adaptive counter-based (HACB) schemeJan/2008 6Develop Adaptive counter-based AODVMar/2008 7Develop Highly Adaptive counter-based AODVMay/2008 8Develop a realistic mobility model for ACB and HACBJune/2008 9Submit my second year reportJuly/ Write up for my Ph.D. dissertationAugust/ Submit my dissertationJuly/ Do my final year VivaAugust/ Thesis correction and final submissionOct/2009

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

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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

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43 Questions

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EAC 44 (a)(b)

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