Simple Ant Routing Algorithm Strategies for MANET Fernando Correia and Teresa Vazão Portuguese Naval Academy, 葡萄牙海軍學院 Ad Hoc Networks 2010

Page: 2 WMNL Introduction and Goals Simple Ant Routing Algorithm (SARA) Performance Evaluation Conclusions

Page: 3 WMNL Introduction and Goals Simple Ant Routing Algorithm (SARA) Performance Evaluation Conclusions

Page: 4 WMNL The growth of mobile devices and wireless networking –Made MANETs a popular research topic –Providing ubiquitous access to information –Enabled a wide variety of applications and services

Page: 5 WMNL A generalized dissemination is constrained imposed by –Limited bandwidth –The nodes can move randomly –Highly variable quality of the transmission path

Page: 6 WMNL Routing in MANETs is a major research issue –Allow the network to offer a good service –Robust, reliable and efficient –Low cost –As simple as possible

Page: 7 WMNL Many routing proposals have appeared –Broadcast –Table-driven –Demand-driven –Hybrid strategy –Opportunistic Routing

Page: 8 WMNL Many routing proposals have appeared –Broadcast Increase the overhead and the congestion and will cause extra power consumption –Table-driven –Demand-driven –Hybrid strategy –Opportunistic Routing

Page: 9 WMNL Many routing proposals have appeared –Broadcast –Table-driven Worse network performance to keep the network topology up-to-date. Makes them particularly less adequate for use in MATs –Demand-driven –Hybrid strategy –Opportunistic Routing

Page: 10 WMNL Many routing proposals have appeared –Broadcast –Table-driven –Demand-driven Require the use of a significant amount of control information during the route discovery process. –Hybrid strategy –Opportunistic Routing

Page: 11 WMNL Many routing proposals have appeared –Broadcast –Table-driven –Demand-driven –Hybrid strategy The overhead associated with the path discovery is high. –Opportunistic Routing

Page: 12 WMNL Many routing proposals have appeared –Broadcast –Table-driven –Demand-driven –Hybrid strategy –Opportunistic Routing Topology knowledge is required The overhead of this process increases significantly when nodes’ mobility increases.

Page: 13 WMNL Proposed a Routing Algorithm for MANETs –Reducing the overhead –Does not use any sort of extra information –Optimal performance –Dynamically adapted according to the traffic conditions

Page: 14 WMNL Introduction and Goals Simple Ant Routing Algorithm (SARA) Performance Evaluation Conclusions

Page: 15 WMNL SARA Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery

Page: 16 WMNL SARA

Page: 17 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d FANT Controlled Neighbor Broadcast (CNB) The cost of link u→j i The number of times previously selected The probability to choose node j i as the next hop.

Page: 18 WMNL nC(u,ji,d)C(u,ji,d) p(u,ji,d)p(u,ji,d) A010.5 B01 nC(u,ji,d)C(u,ji,d) p(u,ji,d)p(u,ji,d) A01 B01 nC(u,ji,d)C(u,ji,d) p(u,ji,d)p(u,ji,d) A B Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d FANT Controlled Neighbor Broadcast (CNB)

Page: 19 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d Controlled Neighbor Broadcast (CNB) nC(u,ji,d)C(u,ji,d) p(u,ji,d)p(u,ji,d) s B01 j1j1 01 j2j2 01 FANT nC(u,ji,d)C(u,ji,d) p(u,ji,d)p(u,ji,d) s B01 j1j1 01 j2j2 01 nC(u,ji,d)C(u,ji,d) p(u,ji,d)p(u,ji,d) s01 B01 j1j1 01 j2j2 01 nC(u,ji,d)C(u,ji,d) p(u,ji,d)p(u,ji,d) s B01 j1j1 01 j2j

Page: 20 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d Controlled Neighbor Broadcast (CNB) BANT

Page: 21 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d Controlled Neighbor Broadcast (CNB) S A j2j2 u j0j0 d B Time FANT_1 C_FANT_1 T1T1 FANT_1(2) C_FANT_1(2) BANT_1 T0T0 FANT_2 C_FANT_2 BANT_1

Page: 22 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d Controlled Neighbor Broadcast (CNB)

Page: 23 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery Controlled Neighbor Broadcast (CNB) S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d

Page: 24 WMNL SARA

Page: 25 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d

Page: 26 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d Increase Pheromone intensity (α) Decrease Pheromone intensity (γ)

Page: 27 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery Increase Pheromone intensity (α) Decrease Pheromone intensity (γ) Time Pheromone level τ1τ1 τ2τ2 τ3τ3 τ4τ4 T1T1 T1T1 T1T1 T1T1 T1T1 T1T1 T1T1 T1T1 α γ

Page: 28 WMNL SARA

Page: 29 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d The pheromone level between node u and node j i The number of hops from j i to destination The link cost The probability to choose node j i as the next hop.

Page: 30 WMNL SARA

Page: 31 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d R_FANT TTL=2

Page: 32 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d S A j2j2 u j0j0 d j1j1 Time DATA R_FANT R_BANT R_FANT R_BANT DATA

Page: 33 WMNL Route Repair Route Repair Route Selection Route Selection Route Maintenance Route Maintenance Route Discovery Route Discovery S S A A B B J2J2 J2J2 J1J1 J1J1 J3J3 J3J3 u u J4J4 J4J4 J0J0 J0J0 d d S A j2j2 u j0j0 d j1j1 Time DATA R_FANT RRT R_ERROR

Page: 34 WMNL Introduction and Goals Simple Ant Routing Algorithm (SARA) Performance Evaluation Conclusions

Page: 35 WMNL Simulation Parameters Size of network 1000  1000m 2 Number of nodes104 DeploymentRandomly Communication range200 m Simulation times60s Channel Capacity2Mbps Transmission Pair 4 CBR (8*512-byte per second) 4 FTP (1kB) Mobility0ms -1 ~10ms -1 Comparision ARA 、 AODV 、 AntHocNet

Page: 36 WMNL SARA Optimum configuration values F1 T0500 ms T11s RRT200ms τ500ms δ0.1 MAX_Tx2

Page: 37 WMNL Overhead CBR trafficFTP traffic

Page: 38 WMNL Route discovery time CBR trafficFTP traffic

Page: 39 WMNL Goodput CBR trafficFTP traffic

Page: 40 WMNL Introduction and Goals Simple Ant Routing Algorithm (SARA) Performance Evaluation Conclusions

Page: 41 WMNL Proposed a Routing Algorithm (SARA) for MANETs –Reducing the overhead –Does not use any sort of extra information –Optimal performance –Dynamically adapted according to the traffic conditions

Page: 42 WMNL Wireless & Mobile Network Laboratory (WMNL.) Department of Computer Science and Information Engineering, Tamkang University