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Robust MANET Design. John P. Mullen, Ph.D. Timothy I. Matis, Ph.D. Smriti Rangan Karl Adams Center for Stochastic Modeling New Mexico State University May 16, 2004. What Are MANETS ?. A MANET is a mobile ad-hoc wireless communication network that is capable of autonomous operation
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Robust MANET Design John P. Mullen, Ph.D. Timothy I. Matis, Ph.D. Smriti Rangan Karl Adams Center for Stochastic Modeling New Mexico State University May 16, 2004
What Are MANETS ? A MANET is a mobile ad-hoc wireless communication network that is capable of autonomous operation • Each node is capable of transmitting, receiving, and routing packets of information. • The network has no fixed backbone (such as with the Internet and cellular phones) • The nodes are able to enter, leave, and move around the network independently and randomly
G D H I A B E F C Mobile Ad Hoc Path Search Y X
G G D Y D A H H X I A X Y B F B E E C F I C Same MANET After a While
Types of Packets • Control Packets – • RREQ’ s and RREP’s – Used to establish communication links between the source and destination nodes. There are numerous protocols that have been proposed for their “optimal” use in finding reliable links at minimal bandwidth • ACK’s – Used to ascertain the quality of a link and ensure successful communication. The destination node sends an acknowledgement (ack) packet back to the source after each successful data packet transmission. • Data Packets • Contain the actual information that is to be communicated broken up into “packets” of uniform size • Data packets are much larger than control packets
Single channel protocols uniform Destination based topology-based Non-uniform reactive proactive AODV TORA ABR proactive DSDV WRP reactive GSR DSR partitioning CEDAR CBRP Neighbor selection ZRP OLSR Protocol Taxonomy
MANET Models • Current MANET Models • Received power is a deterministic function of distance • Node communication (preceived pmin) is flawless within a nominal range, r0, and is not possible (preceived pmin) beyond this range • In actuality, the received power process is highly stochastic due primarily to shadowing and fading
Field Measurements: Current Assumption: Rec. Power is a deterministic function of distance p(r) From Neskovic 2002 – Fig. 2 Current vs. Observed
Evaluating Protocols • The deterministic power assumption is the default of most simulation software (OpNet, NS2, NAB) used to evaluate protocol performance • The stochastic problem is typically viewed as a minor (and unimportant) nuisance by the CS and EE communities that design these protocols
Rayleigh Fading • The instantaneous received voltage in an inefficient, low power, and complex RF environment often follows a Rayleigh distribution • As a result, it follows that received power is exponentially distributed • Further, we assume power exponentially decays with distance
Findings • Not all packets within nominal range are transmitted successfully • Not all packets outside the range are unsuccessful
Relay Source Dest. Scenario Two – DSR Protocol
RF Propagation Distances Relay Source Dest.
End-to-End Delay Delay = 0.004 sec In no-fading model
Route Discovery Time One Route discovery In no-fading model
Transmit Buffer Size Buffer size is 2.0 In no-fading model
Hops per Route 1.5 hops average A-B: 1 hop A-C: 2 hops In no-fading model
The Basic Problem Relay Source Dest.
0.005 p2 = 50p1 0.75 0.995 0.25 Ping - Pong A B C A B C 1 - 0.46 0.4 1-hop 2-hop 0.2 0.6 p2 = 2p1 0.8
Findings • Only through accurate stochastic simulations can • The true performance of existing protocols be evaluated • The parameters of these protocols be optimized for robust performance • New robust protocols be developed • Parameters not significant in deterministic models (such as packet retry) are important in stochastic models
Robust MANET Design • RSM may be used to optimize the performance of established protocols for the controllable parameters (F, number of TX tries, etc.) over the uncontrollable parameters (c, TX rate, etc.) • As an example, consider optimizing the number of TX tries (1,2,3,4) over 2 levels of TX rate (71.5,143 in packets/sec) using throughput as a measure of performance
Questions ? John Mullen jomullen@nmsu.edu Tim Matis tmatis@nmsu.edu Center for Stochastic Modelling http://engr.nmsu.edu/~csm