AN ADAPTIVE GATEWAY DISCOVERY IN HYBRID MANETS F. D. Trujillo, A. Triviño, E. Casilari and A. Díaz-Estrella Department of Electronic Technology University of Malaga A. J. Yuste Department of Telecommunication Engineering University of Jaen
Contents 1.- Introduction 2.- Previous studies 3.- Adaptive Gateway Algorithm (AGW) 4.- Performance evaluation 5.- Conclusions
Introduction (I) – Interconnection of Mobile Ad hoc NETwork (MANET) and Internet to increase the network capacity – Necessity of an access router and an internet gateway Modified Router Advertisement messages (MRA) – The emission of MRA messages can be achieved by three diferents schemes: • Proactive mechanism : the internet gateway disseminates the message periodically • Reactive mechanism : these messages are generated only on demand as reply of a MRS message • Hybrid mechanism : combines both previous schemes (MRA messages to devices nearby to the internet gateway)
Introduction (II) – We will focus on the proactive gateway method – Procedure of performance: 1. A mobile node receives the MRA message 2. This mobile node updates its route entry 3. It rebroadcasts the MRA message – The interval of generation of MRA messages (T period) affects the network: • Low value : the limited MANET resources can be cousumed • High value : former routing information can be stored in the nodes – It is necessary to choose very carefully this advertisement period
Introduction (and III) – In proactive mechanism, better performance (packet delay) is obtained (but with a high bandwidth use) – The goal: decrease control traffic – Algorithm based on the estimation of network conectivity from the percentage of nodes located in the transmission range of the internet gateway: • High number of neighbours: shorther routes are required for external communications (longer lifetimes) T higher • The gateway analyzes the number of MRA messages and changes T to avoid emission of excessive routing packets. • This tuning process is supported by a control system configured by means of statistical properties (after explained)
Previous studies (I) – The interval of emission of MRA messages (T) must be adapted to the network conditions – Related algorithm: • Maximal Source Coverage (MSC) : T is a fixed value and the internet gateway sents the next MRA message with TTL = minimun number of hops • Regulated Mobility Degree (RMD) : the MRA messages broadcasting depends on the number of active sources and the number of intermediate nodes • Use of an auto-regressive filter to adjust both T and TTL, simultaneously. Necessity of monitor de traffic load in internet gateways • Dynamically tuning of T by means of the estimation of reactive route solicitations from the nodes by means of auto-regressive filter • Adaptive Gateway Algorithm (AGW) : the adaptation of T is based on the number of MRA messages retransmitted by the gateway’s neighbours
Adaptive Gateway Algorithm (I) – Until now : the T period is fixed to a constant value – However : the optimum value depends on the network conditions (load, number of traffic sources, the node mobility, etc) – From now : the T period is adjusted with regard to the number of received MRA messages which are retransmitted by the gateway’s neighbours: • Many MRA messages received : all these nodes have updated the routing entry to the internet gateway the T could be incremented • Few MRA messages received : the T must be decreased to guarantee that nodes keep valid route to the internet gateway
Adaptive Gateway Algorithm (II) Output function of control system to adapt T period – Input : the number of MRA messages received by the internet gateway – Output : the T period – The measurement of received MRA messages is carried out every period of T – Some necessary simulations to justify the selection of a linear function like measurement of the network connectivity
Adaptive Gateway Algorithm (III) 24 22 20 18 16 MRA received 14 12 10 8 6 4 5 10 15 20 25 30 35 40 Real node mobile close GW MRA messages received versus node mobile close to the gateway – The probability p that a node is near a gateway can be calculated and it depends on the node number, gateway location and topologies – With this value of p in mind, the probability that there are n nodes in the coverage area of a gateway can be computed as a binomial distribution (with N the total number of mobile nodes): N = − g n p n p N − n ( ) · ·( 1 ) n
Adaptive Gateway Algorithm (and IV) 1 0.9 0.8 0.7 0.6 0.5 0.4 p=0.1 N=50 p=0.2 N=50 0.3 p=0.3 N=50 0.2 0.1 0 0 5 10 15 20 25 Nodes Cumulative density function, G(n) – The values of N 1 and N 2 must be chosen within the linear zone of G(n) – N 2 will be the mean of MRA messages received – N 1 is equal to the mean divided by 4 – But the values of N 1 and N 2 are dynamics and they change whenever a MRA message is sent by the gateway – The standard value of 2 seconds has been chosen for T MIN and the typical value of 20 seconds has been chose for T MAX
Performance evaluation (I) – Three different simulation settings are defined and used to validate the Adaptive Gateway Algorithm – The common parameters for the simulations have the following values: Transmission 250 m range Ad hoc AODV protocol Local repair disabled Link layer detection enabled Link layer 802.11 RTS/CTS enabled Mobility Maximum speed: 2 m/s to 5 m/s pattern Pause time: 10 s Ten sources CBR 15 packets/s Mobility Random Waypoint Model pattern (RWP) Speed 2 to 5 m/s Simulation common parameters
Performance evaluation (II) – The simulations have been implemented in three different environments (node density, surface and gateway position): • The Scene I corresponds to a rectangular area with the gateway in the center of the topology • The Scene II is a square area with two gateways, located in the opposite corners of the square • The Scene III is a wide rectangular area with two gateways SCENE I SCENE II SCENE III Dimension 1500 x 300 m 2 600 x 600 m 2 2500 x 500 m 2 Nodes 50 75 100 Location (0, 0) (625, 250) (750, 150) gateway (600, 600) (1875, 250) Different simulation scenes
Performance evaluation (III) – The simulations results of the AGW are compared with the MSC and the RMD algorithms (before explained) – A software module that includes the algorithm in the Global Connectivity support has been developed – And this module has been integrated into the Network Simulator, ns-2.29 on Linux – The algorithms have been tested in functions of these parameters: • Packet loss rate ( plr ) : defined as the ratio of the number of lost packets to the total number of transmitted packets • End-to-end delay ( delay ) : it represents the average value of the time that the received packets take to reach the destination • Routing overhead normalized ( ron ) : defined as the total number of control packets divided by the total number of received packets – plr and delay values are the two most important parameters from the point of view of the userd. ron is important due to the need of having a measurement of the battery consumption in the mobile nodes
Performance evaluation (IV) Maximum Speed Metric T 2 3 4 5 RMD 0.0738 0.0817 0.0854 0.0862 delay MSC 0.0689 0.0813 0.0820 0.0858 0.0686 0.0729 0.0793 0.0800 AGW RMD 0.0507 0.0519 0.0610 0.0650 plr MSC 0.0524 0.0548 0.0618 0.0629 0.0472 0.0474 0.0569 0.0582 AGW RMD 0.3852 0.4357 0.4590 0.5163 ron MSC 0.3928 0.4451 0.4601 0.4827 0.3604 0.4138 0.4345 0.4539 AGW Scene I – A comparison between RMD and MSC algorithms points out that the RMD algorithm is better regarding to plr and ron , but not in the delay parameter – Moreover, with the proposed AGW algorithm, the best results are achieved
Performance evaluation (V) Maximum Speed Metric T 2 3 4 5 RMD 0.1745 0.2373 0.2383 0.3367 delay MSC 0.1252 0.2143 0.2214 0.2820 0.1069 0.1243 0.1371 0.1756 AGW RMD 0.0179 0.0395 0.0411 0.0459 plr MSC 0.0278 0.0432 0.0463 0.0529 0.0153 0.0217 0.0241 0.0243 AGW RMD 0.1659 0.2004 0.2362 0.2592 ron MSC 0.01678 0.2130 0.2389 0.2645 0.1548 0.1900 0.2235 0.2458 AGW Scene II – The results obtained for RMD and MSC algorithms are very similar because the proposed parameter in RMD algorithm will be always higher than the threshold due to the position of the gateways which, in case of the square area, are located in the opposite corners. The MSC algorithm obtains worse results than RMD – The proposed AGW algorithm presents the best results
Performance evaluation (and VI) Maximum Speed Metric T 2 3 4 5 RMD 0.0309 0.0325 0.0358 0.0377 delay MSC 0.0303 00.0305 0.0345 0.0346 0.0254 0.0257 0.0270 0.0274 AGW RMD 0.0096 0.0106 0.0109 0.0120 plr MSC 0.0106 0.0109 0.0118 0.0129 0.0057 0.0063 0.0064 0.0075 AGW RMD 0.1427 0.1599 0.1837 0.2185 ron MSC 0.1484 0.1645 0.2051 0.2252 0.1333 0.1515 0.1723 0.2017 AGW Scene III – For this new environment, the MSC algorithm is the worst of the three algorithms – The proposed AGW algorithm obtains, again, the best results ( delay , plr and ron )
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