A simulation study on the performance of Mobile IPv6 in a WLAN-based cellular network

A simulation study on the performance of Mobile IPv6in a WLAN-based cellular network

Xavier P�eerez Costa *, Hannes Hartenstein

Network Laboratories, NEC Europe Ltd., Adenauerplatz 6, 69115 Heidelberg, Germany

Abstract

We performed a simulative evaluation of Mobile IPv6 (MIPv6) via ns-2 for a scenario comprising up to three access

routers and 30 mobile nodes that communicate in accordance with the IEEE 802.11 wireless LAN standard. We

compare standard MIPv6 to a fast handoff procedure and analyze route optimization issues. We present results with

respect to handoff latency, packet loss, end-to-end delay, signaling load, channel utilization, and bandwidth per station,

and show how various traffic types like UDP CBR, VoIP, and TCP are affected by the handoffs. While some simulation

results corroborate the intention of the protocol specification, other results give insights not easily gained without

performing simulations. For example, we learned that (i) the fast handoff mechanism almost fully eliminates packet

losses but only improves handoff latency in specific cases, (ii) the signaling load introduced by MIPv6 does not severely

affect the performance, and (iii) in a shared environment like IEEE 802.11, traffic type can affect the handoff rate since

in high-load situations router advertisements might get lost more frequently thereby ‘irritating’ the handoff decision

mechanism. As a challenge for future simulations we have identified the design of a random mobility model that allows

good control of the handoff rate.

Keywords: Mobile IP; IPv6; Handoffs; Simulations; Performance evaluation; ns-2

1. Introduction

The Internet is going mobile and cellular sys-tems are embracing IP technology. This trend hasstimulated work on protocol design for IP-basedmobility management during the last few years.The IETF working group on Mobile IP is pro-posing Mobile IPv4 (MIPv4) [1] and Mobile IPv6(MIPv6) [2] as the main protocols for supportingIP mobility. In order to improve the ‘QoS experi-

ence’ of a mobile user who moves from one accessrouter to another as well as to reduce the signalingload on the network, a large number of extensionsto Mobile IP for localized mobility managementand fast/seamless handoffs has been proposed, seefor example [3], and discussed heavily on the IETFMobile IP and Seamoby mailing lists. Main dis-cussion items are scalability, handoff latency andsignaling overhead of a protocol. However, it isnot an easy task to predict a protocol’s perfor-mance by only studying the protocol specification.For a deeper understanding as well as for assessingmore general system aspects, simulation is themost important tool.

Computer Networks 40 (2002) 191–204

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*Corresponding author. Tel.: +49-6221-13708-15.

E-mail address: [email protected] (X. P�eerez

Costa).

PII: S1389-1286 (02 )00274-8

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mail to: [email protected]

In this paper we study protocol performanceaspects of MIPv6, in particular effects of handoffsand route optimization. The intention is to providea thorough simulation study from which one canderive when or whether at all additional extensionsto the protocol are needed. Our main interest hasbeen to assess latency and packet losses introducedby ‘standard’ as well as ‘improved’ MIPv6 handoffprocedures, the effect of route optimization onend-to-end delay, and associated signaling costs.Moreover, the impact on channel utilization andbandwidth per station has been studied. Clearly,simulation results depend on the scenario usedand, thus, the question of ‘what is the right sce-nario’ arises immediately. A trade-off has to beconsidered between how general or system-specificthe simulation results should be. We have chosen abasic scenario consisting of up to three accessrouters and 30 mobile nodes that communicate inaccordance with the IEEE 802.11 wireless LANstandard. We focus not solely on MIPv6 protocolperformance but on system performance includingthe impact of a shared link on the performanceparameters. The scenario can also be used to formmore complex, e.g., hierarchical, settings. As themobility pattern for the mobile node, the randomway-point mobility model [4] is used. As datatraffic types we studied UDP-based, constant bit-rate traffic (UDP CBR), voice-over-IP traffic(VoIP), and TCP traffic. The simulation code usedfor the experiments was designed on top of Thi-erry Ernst’s MIPv6 [5] for ns-2 [6] implementation.

Previous work on simulative evaluations ofMobile IP exclusively dealt with IPv4 networks.Perkins and Wang [7] have used ns-1 to analyze theeffects of route optimization and buffering (smoothhandoff). Caneel and Lamprecht [8] have designedns-2 modules for Cellular IP, HAWAII, andTHEMA. The Columbia IP Micro-Mobility Suite[9] comprises ns-2 modules for Cellular IP, HA-WAII, and Hierarchical Mobile IP. An evaluationof Cellular IP is provided by Campbell et al. in[10]. Because of the significant differences betweenMIPv6 and MIPv4 as outlined in the followingsection, we have seen the need for a dedicatedstudy on MIPv6.

The paper is structured as follows. Section 2recalls the basics of Mobile IP. In Section 3 we

describe the simulation scenario in detail. Theperformance aspects subject of interest are given inSection 4. Simulation results are provided in Sec-tion 5. Finally, Section 6 presents some hints forfuture work and the summary.

2. Mobile IP

Mobile IP supports mobility of IP hosts by al-lowing them to make use of (at least) two IP ad-dresses: a home address that represents the fixedaddress of the node and a care-of-address (CoA)that changes with the IP subnet the mobile node iscurrently attached to. Clearly, an entity is neededthat maps a home address to the correspondingcurrently valid CoA.

In MIPv4 [1], these mappings are exclusivelyhandled by ‘home agents’ (HA). A correspondingnode (CN) that wants to send packets to a mobilenode (MN) will send the packets to the MN’shome address. In the MN’s home network thesepackets will be ‘intercepted’ by the home agentand tunneled, e.g., by IP-in-IP encapsulation [11],either directly to the MN or to a foreign agent towhich the MN has a direct link.

In MIPv6, home agents no longer exclusivelydeal with the address mapping, but each CN canhave its own ‘binding cache’ where home addressplus CoA pairs are stored. This enables ‘routeoptimization’ compared to the triangle routing viathe HA in MIPv4: a CN is able to send packetsdirectly to a MN when the CN has a recent entryfor the MN in its corresponding binding cache.When a CN sends a packet directly to a MN, itdoes not encapsulate the packet as the HA does,but makes use of the IPv6 Routing Header Option.When the CN does not have a binding cache entryfor the MN, it sends the packet to the MN’s homeaddress. The MN’s home agent will then forwardthe packet. The MN when receiving an encapsu-lated packet will inform the corresponding CNabout the current CoA.

In order to keep the home address to CoAmappings up-to-date, a mobile node has to signalcorresponding changes to its corresponding nodesand/or home agent when performing a handoff toanother IP subnet. Since in MIPv6 both, CN and

192 X. P�eerez Costa, H. Hartenstein / Computer Networks 40 (2002) 191–204

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HA, maintain binding caches, a common messageformat called ‘binding updates’ is used to informCN and HA about changes in the point of attach-ment. Additionally, MIPv6 allows a MN to send abinding update to a MIPv6 agent in the IP subnetpreviously visited by the MN. Then, packets sentby CNs that have not yet learned the MN’s newCoA will be tunneled from the previously visitedsubnet to the current point of attachment. Bindingupdates (BU) can be acknowledged by BU ACKs.In contrast toMIPv4, where signaling is done usingUDP,MIPv6 signaling is done in extension headersthat can also be piggybacked on ‘regular’ packets.To acquire a CoA in MIPv6, a mobile node canbuild on IPv6 stateless and stateful auto-configu-ration methods. The stateless auto-configurationmechanism is not available in IPv4. In our work, weassume stateless auto-configuration for all tests.For more details on MIPv6 see [2].

As mentioned above, the differences betweenMIPv4 and MIPv6 with respect to signaling anddata flow requires separate studies to evaluate over-all protocol performance. In this paper, we focuson MIPv6 specific features.

3. Simulation scenario

For the performance study of MIPv6, a basicscenario is necessary to analyze various aspectsseparately. The studied scenario (see Fig. 1) iscomposed of a group of correspondent nodes, onefor each mobile node, connected to one central

router (CR) through the ‘Internet’, the accessrouters (AR)––each one representing a different IPsubnet––connected also to the CR, and 10 mobilenodes per AR in the initial setup. The home agentof each mobile node is located in the access routerclosest to the mobile node when the simulationstarts.

The distance between the access routers is 450m and the transmission range 250 m. Thus, thecoverage areas of the access routers overlap, andthe mobile nodes always move randomly withinthe total coverage area. For the mobility pattern,we build on the random way-point mobility model[4] provided by [6]. This model has been previouslyused mainly for ad hoc network simulations. De-tails on the random way-point model are given inSection 5.

A 2 Mbps Wireless LAN 802.11 [12] using DCFis simulated. The number of mobile nodes has beenchosen with the aim of working close to saturationthroughput assuming sources sending about 75kbps. 1

The default link delay (ld ) between the CR andthe ARs is 1.8 ms. The link delay between the CRand CNs is fixed to 10.8 ms for all simulations. Inthe simulations, we have varied the ld value tomodel various ‘distances’ between the ARs andbetween CNs and MNs.

In this study, when differentiation between thekind of handoff (home link to foreign link (HL–FL), foreign to foreign link (FL–FL)) is neededthree access routers have been simulated, other-wise two access routers are considered.

While moving within the overlapping area, themobile nodes are able to send/receive data only viathe access router that corresponds to their currentcare of address. 2

Fig. 1. Simulations scenario.

1 The transmission range in the simulator is 250 m and the

interference range is 550 m. Therefore, when two access routers

are used, the saturation throughput for both access routers is

around 1.5 Mbps, since their transmission and interference

ranges overlap. Note that 20 mobile nodes sending or receiving

75 kbps over the wireless medium produce 1.5 Mbps.2 Technologies like IEEE802.11 allow the mobile nodes

gathering information about the neighboring access routers, but

do not allow to receive IP flows with different destination

addresses simultaneously from two access routers except for

particular cases like having an additional wireless interface.

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In the initial setup, in each access router fivemobile nodes receive data from five correspondentnodes and the other five mobile nodes send data toanother five correspondent nodes. The scenariohas been chosen to simulate a realistic case where amobile node will receive packets from the sharedaccess router queue and where a mobile node willalso compete with other mobile nodes and with anaccess router to access the channel. The corre-spondent nodes sending to the mobile nodes in-troduce delay in the access router queue and themobile nodes sending to the correspondent nodesintroduce delay in the wireless link.

It is important to note the following fact thatresults from using a shared access: whenever wework close to the maximum throughput of thechannel, the mobile nodes that will first experiencea reduction in their throughput will be the onesreceiving from the correspondent nodes. The rea-son is that these stations receive all the packetsfrom the same station, i.e., the access router,sharing the access queue to the wireless channel,while the other mobile nodes sending to the cor-respondent nodes do not share their access queueto the channel.

In our simulations different types of traffic willbe simulated. UDP CBR sources provide constanttraffic where no acknowledgements are required.This kind of traffic is usually generated by real-time applications. In the study, we simulate trafficsources sending at the following rates: 40, 50 and75 kbps. In the case of 40 or 50 kbps the load inthe channel is below the saturation throughput,while in the case of 75 kbps the load in the channelis close to the saturation throughput in a scenariowith two access routers.

TCP is the most widely used transport protocol.We simulate endless FTP sources to understandthe impact of IP mobility on the congestion con-trol mechanism of TCP.

One of the applications expected to be usedwith MIPv6 is VoIP. We have implemented aVoIP model based on [13]. The model assumessilence suppression and models each voice sourceas an on–off Markov process. The alternating ac-tive on and silence off periods are exponentiallydistributed with average durations of 1.004 and1.587 s. As recommended by the ITU-T specifica-

tion for conversational speech [14], an average talkspurt of 38.57% and an average silence period of61.47% is considered. A rate of 88 kbps 3 in onperiods and 0 kbps in off periods is assumed for avoice source that generates CBR traffic.

4. Aspects to be studied

We analyze handoff performance of MIPv6with respect to handoff latency, packet lossesduring handoffs, signaling load, channel utiliza-tion and obtained bandwidth per station. Theseparameters are explained in more detail below.Furthermore, we investigate how a fast handoffmechanism improves above mentioned measure-ments. We have implemented a fast handoff pro-cedure (FHO) inspired by [3]: we use statelessaddress auto-configuration and send the BU withthe newly formed CoA via the old access routerinstead of sending it via the new one. By doingthis, redirection of the traffic to the MN will beprocessed directly at the receiving access router.The MN then switches to the new access routerand waits for the redirected packets to come.

In addition, we study route optimization, whichis embedded in MIPv6 while it is only an extensionin MIPv4. The avoidance of triangle routing viathe HA is a clear advantage of route optimizationwith respect to end-to-end delay. However, theincrease in signaling load produced by route op-timization as well as the increase in performance ofonly some parameters under specific circumstanceslead to the question on whether the price in sig-naling load is worth paying.

In the following, we define the parameters in-vestigated in the simulations.

4.1. Handoff latency

Handoff latency is defined for a receiving MNas the time that elapses between the last packet

3 Assume 8 KHz 8 bits/sample PCM codec was used with 20

s frame per packet. With 12 byte RTP header, 8 byte UDP

header and 40 byte IP header, the size of each voice packet is

220 bytes. The bandwidth required will be ð220� 8Þ=20 ¼ 88

kbps.


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received via the old route and the arrival of thefirst packet along the new route after a handoff.Latency is an important parameter for delay-sen-sitive applications like VoIP that could suffer froma period with a higher rate of packet drops due toa long latency time. This packet drop period wouldresult in a noticeable disruption in the voicetransmission. We study handoff latency for variousvalues of lds as well as for HL–FL and FL–FLhandoffs. A differentiation between the latency dueto a handoff between the home link and a foreignlink and the handoff between two foreign links isneeded. When performing a handoff between thehome link and the foreign link, the mobile nodedoes not send a BU to the CN since it does notmaintain a BU list while the mobile node is athome. The first packet received from a CN to amobile node after a HL–FL handoff will produce alatency proportional to the round-trip time neces-sary by a BU to arrive from the foreign link to thehome link. The FL–FL handoff case differs in thatthe latency is proportional to the minimum timerequired by a BU to arrive either at the agent onprevious access router, HA or the CN.

4.2. Packet loss

Packet loss is defined for a receiving MN as thenumber of packets lost during the handoff. Whileusually one assumes that packet losses are directlyproportional to latency, it will be made clear thatthis is generally not true, particularly not for theFHO. We study handoff latency for various valuesof lds as well as for HL–FL and FL–FL handoffs.

4.3. Signaling load

We study the signaling load due to sending ofBUs and BACKs. The number of BUs and BACKssent will be the same for MIPv6 and the FHO anddifferent for MIPv6 with/without route optimiza-tion. We study the signaling load for various hand-off rates (number of handoffs per minute).

4.4. Channel utilization

We measure the channel utilization in order tosee the effects of mobility on the overall through-

put. We study the impact of mobility on channelutilization for different traffic source types underincreasing mobility of the mobile nodes.

4.5. Bandwidth per station

We study the probability to obtain the requiredbandwidth and the corresponding expected vari-ance for an increasing number of handoffs andvarious traffic types.

4.6. End-to-end delay

To assess the effect of route optimization, wemeasure the end-to-end delay between CNs andMNs for MIPv6 with and without route optimi-zation.

5. Performance evaluation and discussion of results

In this section, we present the results of our ns-2simulation study on the parameters as explained inSection 4 for the scenario described in Section 3.We build two sub-scenarios, one for measuringaspects from a single node’s perspective and an-other one for measurements concerning the overallsystem.

Sub-scenario 1 (SS1): The MN for which mea-surements are taken follows a deterministic paththrough the coverage area, while all other nodesfollow the random way-point mobility model.

Sub-scenario 2 (SS2): All MNs follow therandom way-point mobility model.

Both sub-scenarios, SS1 and SS2, might be usedwith either 2 or 3 ARs and 20 or 30 MNs, re-spectively. Three access routers are only simulatedwhen differentiation between the type of handoff isneeded otherwise two access routers are simulatedfor computing time reasons.

The mobile nodes move according to a slightlymodified ns-2 random way-point model. With therandom way-point mobility model of ns-2, a nodeselects a target location and a speed (sampleduniformly from an interval ½0; vmax�) and moveslinearly towards the target location with the se-lected speed until a specific timer fires. When the


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timeout occurs, the mobile node restarts the pro-cedure. The ns-2 random way-point model hasbeen modified in two ways: (i) the mobile nodes donot perform a change of direction and speed all atthe same time after a fixed amount of seconds butaccording to a uniform random value distributedbetween 1 and 60 s which is different for each node,(ii) this value is not the same during the wholesimulation, but recomputed for each change ofdirection and speed. This modification has beenintroduced to obtain a more realistic model thatde-synchronizes the changes of direction and speedbetween the mobile nodes. When no other value isindicated, all the simulations have been performedwith a maximum speed of 5 m/s.

All simulations have a duration of 125 s with a5 s warm-up phase, and the option of sending aBU to the agent on the previous access router isalways set.

Averages in the following graphs represent theaverage of 100 simulations. In the case of histo-grams they have been obtained by performing1000 simulations.

5.1. Standard MIPv6 (with route optimization)

5.1.1. Handoff latencyFor handoff latency evaluation we have chosen

sub-scenario SS1. The single MN following a de-terministic path performs a handoff from the homelink to a foreign link and from a foreign link toanother foreign link. In total, we employ 3 ARsand 30 MNs. Moreover, the data traffic in thissimulation has to be continuous in order to obtainthe whole latency time. The data rate of the UDPCBR sources has been chosen taking in accountthe interference range of 550 m. The access routerin the center interferes and is interfered by twoaccess routers. Thus, to obtain a significant trafficload value below the saturation throughput wehave chosen a data rate of 40 kbps.

In Figs. 2 and 3, the instantaneous bandwidthfor two different link delay values (1.8 and 1000.8ms) between the ARs and the CR are representedcomparing the results for the above mentionedscenario with the one for a static ‘mobile node’.The integration time to compute the instantaneousbandwidth was set to 200 ms. Note that a smaller

integration time would increase the ‘variance’ ofthe measurements, while a larger value wouldmake the curve smooth such that details (like thespike in Fig. 2) would not be seen any more.

When the transmission time of a BU betweenthe MN via the new AR to HA and/or CN has alower value than the inter-arrival packet time, thelatency is nearly not perceptible as it can be seen inFig. 2. On the other hand, when the transmissiontime is above the inter-arrival packet time then thegap is noticeable (see Fig. 3). The first latency isproduced due to a HL–FL handoff and the second

Fig. 2. Instantaneous bandwidth measurements of UDP CBR

data traffic are shown for a static node as well as for a mobile

node that performs a HL–FL handoff at time 20 s and a FL–FL

handoff at time 40 s. The ld was set to 1.8 ms.


data traffic are shown for a static node as well as for a mobile

node that performs a HL–FL handoff at time 20 s and a FL–FL

handoff at time 40 s. The ld was set to 1000.8 ms.


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one due to a FL–FL handoff. The difference be-tween the instantaneous bandwidth received whilethe mobile node moves in the home link and theone after performing a handoff is due to an en-capsulated packet or the routing header. The twoshort periods where the MN obtained doublebandwidth are due to the fact that the previousagent is still forwarding while the CN is alreadydirectly sending packets.

In Fig. 4 we can observe the variation of thelatency depending on the link delay between theAR and the CR for both kinds of handoffs. Fromthe graph we can deduct for our scenario that theHL–FL handoff will always result in a higher orsimilar latency value compared to the FL–FL case.This is because in the case of a HL–FL handoff themobile node will only send a BU to the HA andnot to the CN. This will result in a higher latencytime than in the case of FL–FL because fromMN’s perspective at the foreign AR, the HA isfarther away than the CN in our scenario for highvalues of ld. The consequence is clear when weobserve the points for large link delays in Fig. 4.What we can observe from Fig. 4 as well is that thelatency time remains almost constant until the linkdelay reaches the value of 10 ms. This means thatthe wireless delay is much bigger compared to thewired one until this point, so any improvementthat we could make to decrease the wired delaywill not show an effect in scenarios where the wireddelay is below this value.

5.1.2. Packet lossWe consider the experiment for handoff latency

evaluation (Section 5.1.1) and focus now on thecorresponding packet loss. With the 40 kbps UDPCBR traffic, a packet is sent every 200 ms. Fig. 5presents the number of packets lost because ofhandoffs. The result shows that for a link delayvalue below 100 ms we can expect an average num-ber of packet losses per handoff below or around 1mainly depending on the difficulty in accessing thewireless medium. For higher ld values the packetlosses increase significantly due to the increase inlatency. We see that there are nearly no differenceswith respect to packet losses for the HL–FL andFL–FL handoff cases despite the differences inlatency. In both cases, the packet losses are pro-portional to two link delays. This becomes clearwhen one notes that a number of packets propor-tional to one ld is lost while the new BU travelsfrom the new AR to the CR. When it arrives there,there is another number of packets proportional tothe ld on the link between CR and old AR. Allthese packets will be lost as well.

5.1.3. Channel utilizationFor the analysis of channel utilization we use

sub-scenario SS2 with 2 ARs and 20 MNs. Westudy the impact of the number of handoffs onchannel utilization with different traffic sourcesand under saturation or no saturation conditionsin the wireless channel. UDP CBR sources are

Fig. 4. Average handoff latency varying with the link delay for

UDP CBR data traffic.

Fig. 5. Average packet loss per handoff depending on the link

delay for standard MIPv6.


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studied to determine the impact of handoffs over acontinuous data flow with no required acknowl-edgement. The behavior of bursty sources underan increasing number of handoffs is examined viathe VoIP traffic. Endless TCP FTP sources aresimulated to investigate the result of handoffs overthe congestion control mechanism. UDP CBRsources sending at a rate of 75 kbps and endlessTCP FTP sources represent the saturation case.The no saturation case is represented by the 50kbps UDP CBR and VolP bursty sources.

In order to increase the average number ofhandoffs per minute, we vary the maximum speedof the nodes (see Fig. 6). A discussion on the re-lation between maximum speed and averagenumber of handoffs for the various traffic types ispresented below. In Fig. 7 we observe that channelutilization is almost not affected by an increasingnumber of handoffs in the case where the trafficload of the channel is below the saturationthroughput. On the other hand, in the saturationcase, the impact of the handoffs on the experiencedthroughput is quite significant. This is becausefrom an expected overall throughput of 1500 kbpsachievable in a static scenario, for the case of UDPCBR 75 kbps, we experience a maximum around1400 kbps. Thus, the increase in mobility andsignaling on top of an already saturated channelleads to significant performance penalties.

Endless TCP FTP sources always have a packetto transmit. For a small number of handoffs per

minute, the congestion control suffers the well-known problem of TCP not being adapted to thewireless medium and achieves a channel utilizationquite below the saturation throughput. On theother hand, when the number of handoffs in-creases, TCP increases the achieved bandwidth aswell. On nodes not performing a handoff, TCPtakes advantage of the higher leftover bandwidthdue to the increase of mobile nodes suffering fromthe latency time. Thereby TCP’s channel utiliza-tion can benefit from an increase in the numberof handoffs, however, this comes with the priceof ‘discriminating’ handoff-performing nodes. Weobserved this effect studying the instantaneousbandwidth for a ‘static’ and a handoff-performingnode. These graphs are not included in the paperbecause of space restrictions.

To better understand the above mentioned re-sults, we have to show the dependencies betweenmaximal speed of the nodes and the handoff ratefor the various traffic types. Fig. 6 shows the re-lationship between the speed limit and the averagenumber of handoffs per minute per simulation andconsidering different traffic sources. We can ob-serve that the number of handoffs per minute in-creases according to an increase in the speed limitas expected. 4

Fig. 6. Relation between maximal speed and average number

of handoffs per minute per simulation.

Fig. 7. Channel utilization for standard MIPv6 depending on

speed of nodes and data traffic type.

4 We increased the speed but not the average number of

changes of direction per minute. Adapting the latter one

according to the speed limit will increase the handoff rate even

more.


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The average number of handoffs per minute persimulation changes depending on the traffic con-sidered. A priori we would expect minor differ-ences, but in Figs. 6 and 8 we can see that thedifferences are not negligible. The reason for thisdifference is that loss probabilities of a router ad-vertisement (RAds) depend on the simulated trafficand rate. When a mobile node enters into theoverlapping coverage area of two access routers,at some point of time it receives a router adver-tisement from the new access router. The mobilenodes maintain an AR list with the ARs fromwhich they received router advertisements. When amobile node enters or stays in an overlappingcoverage area, and if it receives a router adver-tisement from an access router that it is not in theaccess router list, the mobile node starts the pro-cess to attach itself to the new access router. If therouter advertisement received is from an accessrouter that is already in the access router list thenthe lifetime entry for this access router is refreshedin the access router list. In this way, a handoff pereach received router advertisement from a differentaccess router while the mobile node moves withinan overlapping coverage area is avoided. Theproblem arises when due to congestion in thewireless channel some router advertisements aredropped. In this case the loss of some router ad-vertisements could lead to the situation of unnec-essary handoffs due to the lack of refreshment ofthe access router list. Fig. 9 shows that a higher

data rate produces a higher average number ofdropped router advertisements.

5.1.4. Bandwidth per stationThe previous section has shown the handoff

impact on channel utilization. In this section westudy the handoff impact over the achieved band-width per station which is the impact that the userperceives. Using the same scenario as in Section5.1.3 we have performed an experiment computingthe bandwidth achieved per station. The result of1000 simulations are represented in Figs. 10 and 11.The kind of representation chosen is a histogram

Fig. 8. Histogram of average number of handoffs per station

for various traffic types and a maximal speed of 5 m/s. Fig. 9. Average number of dropped RAds per simulation de-

pending on the maximal speed of nodes.

Fig. 10. Histogram showing how often a specific bandwidth per

station is achieved depending on the traffic type.


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in order to obtain an idea of the probability ofobtaining the desired bandwidth. A higher numberof occurrences corresponds to a lower number ofhandoffs.

In Figs. 10 and 11 we can observe that UDPCBR 75 kbps, TCP/FTP and VoIP sources resultin a wider histogram than UDP CBR 50 kbpssources and, therefore, a more variable service. Incontrast, for a static scenario and for the case ofUDP CBR the nodes will achieve the requested bitrate with almost no variance. UDP CBR 75 kbpsand VoIP sources have a wider histogram due totheir higher probability of suffering collisions. Thishigher probability of suffering collisions in the caseof UDP CBR 75 kbps sources is due to a globaldata rate close to the saturation throughput andfor the VoIP sources due to the produced burstytraffic. TCP/FTP sources present a wider histo-gram due to the rate adaptation to the channelconditions.

5.1.5. Signaling loadAn increasing number of handoffs produces a

higher signaling load. Considering the same sce-nario as in Section 5.1.3, the experiment shows theslope of this increment and the relevance of thesignaling load compared to the channel capacity.In Fig. 12, we have plotted the amount of signalingdata sent over the air. The points in the graphrepresent the total signaling load in the wirelesschannel during the simulation. The computed

signaling are binding updates and binding ac-knowledgments. When not performing a handoff,a MN sends BU periodically every 10 s. As we cansee in the figure, the signaling load over the air forour scenario is lower than 10 kbps for UDP CBRand bursty sources. The TCP FTP case shows asignaling load below 20 kbps. The signaling load ishigher due to the TCP acknowledgements. Thus,mobile nodes sending to the CNs now also receiveTCP acks and therefore these mobile nodes haveto send BU/BACKs as well while in the case ofUDP traffic this is not necessary.

However, even for a high mobility of the mobilenodes and a large number of stations the signalingload due to binding updates and acknowledge-ments remains below 1% of the channel capacity inthe worst case.

5.2. Mobile IPv6 without route optimization

An important feature of MIPv6 is route opti-mization. We analyze gains as well as potentialdisadvantages of route optimization by comparingthe standard MIPv6 case with the case where routeoptimization is disabled.

5.2.1. Handoff latencyWhen we perform the experiments of Section

5.1.1 now without route optimization, how willhandoff latency be affected?

Fig. 11. Histogram showing how often a specific bandwidth per

station is achieved for the case of TCP traffic.

Fig. 12. Signaling load of standard MIPv6 depending on the

speed of nodes and traffic types.


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The results for the scenario used in Section 5.1.1but without route optimization is given in Fig. 13.First of all, for the HL–FL handoff there will be nodifference since even in the case of route optimi-zation the MN does not maintain a Bu list for CNswhile at home. However, we can observe a differ-ence at approximate time 26 s in the Figs. 3 and 13that is due to the fact that in a HL–FL handoff,with route optimization, there is a period of timewhere the MN receives the packets ‘on the fly’already sent to the HA and the new ones sent bythe CN directly. When the delay between the CNand the HA is small this effect is not noticeable(Fig. 2). On the other hand, for the FL–FL linkhandoff we have in both cases (with and withoutroute optimization) the same effect of receivingpackets from two entities during a short period oftime. This is because, even in the case of not usingroute optimization, the mobile node performingthis kind of handoff sends a BU to an agent on theprevious access router.

Latency times for route and no route optimi-zation for various link delay values are presentedin Fig. 14. For values of ld below 10 ms there is nosignificant difference between route optimizationand no route optimization. However, for largervalues of ld route optimization outperforms noroute optimization in the FL–FL case. With routeoptimization, the latency is proportional to theminimum round-trip time between the mobilenode and its home agent or its previous access

router or its correspondent node while withoutroute optimization it is proportional to the round-trip time between the mobile node and its homeagent.

Our simulations on packet losses directly cor-respond to the HL–FL packet losses investigationof Section 5.1.2, so we do not include the resultshere.

5.2.2. End-to-end delayThe main purpose of route optimization is to

reduce end-to-end delay by avoiding trianglerouting. With an SS2 scenario with 2 ARs and 20MNs, we measured the end-to-end delay betweenCN and MN for MNs that are attached to a for-eign link and analyze the effect of route optimi-zation. The results for various link delays arepresented in Fig. 15.

In the case of no route optimization, the end-to-end delay is composed of the wireless delay plusthe delay from the CN to the HA and from the HAto the current AR. In the graph we can observethat for delay values under 10 ms there is no dif-ference between route and no route optimizationsince the wireless delay is the dominating factor.When the wired delay is much larger compared tothe wireless one, we have a direct relation betweenthe link delay and the end-to-end delay of threetimes the link delay for the case of no route opti-mization and one link delay for the case of routeoptimization.


for the case of ‘no route optimization’ and ld ¼ 1000:8 ms.

Fig. 14. Average handoff latency for UDP CBR data traffic

comparing the case of ‘no route optimization’ with standard

MIPv6.


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5.2.3. Signaling loadFor the case of signaling load, we can observe in

Fig. 16 that usually there is a slightly higher sig-naling load for the case of route optimization,as expected. The measurements were taken fromsimulations with a SS2 scenario with 2 ARs and 20MNs. However, the differences are not significant.As a side note, we would like to point out thataccess efficiency will suffer when the number ofsignaling messages per data packet is increasedunless piggybacking is used.

5.3. Fast handoff procedure

In this section we will evaluate the FHO ex-plained in Section 4 by comparing it with standardMIPv6.

5.3.1. Handoff latencyIn Fig. 17, we compare the latency obtained via

the FHO with the one obtained with standardMIPv6 as explained in Section 5.1.1. The resultshows some advantage of using the FHO. In theextreme case of one second link delay, we savearound two seconds of latency for the HL–FLhandoff. When the value of the link delay increases,the importance of saving in the HL–FL case twolink delays in the round-trip time of the bindingupdate to the previous access router increases, too.

When we compare Fig. 18 with Fig. 3 relative tothe instantaneous bandwidth we can observe thesmaller latency time.

Fig. 16. Signaling load as a result of route optimization/no

route optimization for the case of UDP CBR traffic sources.

Fig. 17. Average handoff latency comparing the FHO with

standard MIPv6.Fig. 15. Impact of route optimization on end-to-end delay.


data traffic for the case of a mobile node that makes use of the

FHO.


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5.3.2. Packet lossWith the FHO, latency and packet losses are

fully ‘separated’. Since packet redirection takesplace when a BU sent by the MN reaches the MNscurrent AR, there is almost no time to lose apacket (see Fig. 19).

In this way two wired ‘link delays’ are saved inorder to keep up to date either the HA or theprevious access router with the correspondingsaving in packet losses due to a forward to anoutdated CoA. When the wired delay increases,the packet losses decrease because the transmissiontime necessary for a data packet to arrive at thenew access router is bigger and when the packetsarrive the mobile node has had more time tocomplete the handoff process.

6. Summary and future work

In this paper we presented a study on the per-formance of MIPv6 in a WLAN-based cellularnetwork by means of simulation with ns-2. Theemployed simulation scenario corresponds to the‘real world’ case where IEEE 802.11 access pointsare attached to various existing IP subnets in away such that the WLAN cells overlap but thevarious IP subnets might not be close to each otherwith respect to ‘number of hops’. These distanceshave been modeled as a single ‘link delay’ whosevalue is varied for this study.

Our main focus was on the evaluation of thehandoff performance of standard MIPv6 in com-parison with a fast handoff mechanism as well ason investigating route optimization. In particular,we showed that the fast handoff mechanism clearlyeliminates packet losses. Additionally, we checkedother QoS-relevant parameters of the system (e.g.,bandwidth per station) and how they were affectedby mobility.

In addition to the quantitative results provided,the simulations gave us the following insights: (i)differences with respect to latency between HL–FLand FL–FL handoff can occur, (ii) handoff latencyand packet losses might not be directly related toeach other, in particular (iii) the fast handoffmechanism eliminates packet loss but does notimprove latency for the FL–FL handoff case, (iv)traffic type can have an impact on handoff rate dueto shared access, and (v) the signaling load evenwith route optimization only contributes a mar-ginal part to the overall rate.

For future work, the study showed the need fora better (e.g., analytical) understanding of a mo-bility model’s parameter’s relation with the result-ing handoff rate. Furthermore, the FHO latencycan clearly be improved by packet bicasting and anenhanced handoff decision algorithm: for example,the MN can estimate the point in time when thefirst packet will arrive at the new AR and––whenpermitted by the MN’s position––stay with itscurrent AR until this point in time.

Acknowledgements

This work has been supported in part by theIST project Moby Dick [15]. The authors wouldlike to thank Thierry Ernst for his work as well asfor his help when developing the code necessaryfor this paper. We also thank the members of theNEC Mobile Internet Group for their helpfulcomments.

References

[1] C. Perkins, IP Mobility Support, RFC 2002, October 1996.

[2] D.B. Johnson, R. University, C. Perkins, Mobility Support

in IPv6, Internet Draft, work in progress, July 2000.

Fig. 19. Average number of packet losses per handoff for the

case of the FHO and standard MIPv6.


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[3] G. Tsirtsis, A. Yegin, C. Perkins, G. Dommety, K. El-

Malki, M. Khalil, Fast Handovers for Mobile IPv6,

Internet Draft, work in progress, July 2001.

[4] J. Broch, D.A. Maltz, D.B. Johnson, Y.-C. Hu, J. Jetcheva,

A performance comparison of multi-hop wireless ad hoc

network routing protocols, MOBICOM, 1998.

[5] Mobiwan: ns-2 extensions to study mobility in Wide-Area

IPv6 Networks, http://www.inrialpes.fr/planete/mobiwan.

[6] Network Simulator (ns). version 2, http://www.isi.edu/

nsnam/ns.

[7] C.E. Perkins, K.-Y. Wang, Optimized smooth handoffs in

mobile IP, ISCC, 1999.

[8] R. Caneel, R. Lamprecht, Simulation von Mobile/Cellular

IP mit Betrachtung von QoS-Aspekten, Technical Report,

ETH Zurich, October 1999.

[9] Columbia IP Micro-Mobility Suite, http://www.comet.co-

lumbia.edu/micromobility.

[10] A.T. Campbell, J. Gomez, S. Kim, A.G. Valko, C.-Y. Wan,

Z.R. Turanyi, Design, implementation, and evaluation of

cellular IP, IEEE Personal Commun. (August 2000).

[11] C. Perkins, IP encapsulation within IP, RFC 2003, October

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[12] IEEE, Wireless LAN Medium Access Control (MAC) and

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[13] R.H. Katz, C.-N. Chuah, L. Subramanian, A. Joseph, QoS

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[14] Recommendation ITU-T p.59, Artificial conversational

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[15] Mobility and Differentiated Services in a Future IP

Network, IST-2000-25394, 2000.

Xavier P�eerez Costa received his B.Sdegree in Telecommunications Engi-neering from the Polytechnic Univer-sity of Catalonia (UPC) in 2000. Hedid his master thesis at NEC NetworkLaboratories Europe Ltd in Heidel-berg on a topic related to QoS in IEEE802.11 wireless LAN and is now aResearch Staff Member within theMobile Internet Group. His main re-search interests are communicationnetworks, mobile networking, andquality of service.

Hannes Hartenstein received the dip-loma degree in mathematics in 1995and the Ph.D. degree in computer sci-ence in 1998, both from Albert-Lud-wigs-Universit€aat, Freiburg, Germany.He was Erasmus Scholar with theUniversity of East Anglia, Norwich,U.K., in 1991–1992 and received theCapocelli Award from the IEEE DataCompression Conference 1997 (withM. Ruhl) for the paper ‘‘Optimalfractal coding is NP-hard’’. He joinedNEC Network Laboratories Europe in1999 and is now a Senior Research

Staff Member with the Mobile Internet Group. He currentlyfocusses on IP-based mobility management as well as on ad hocrouting. His general research interests include mobile commu-nications, networking, multimedia, image/video processing, andtheoretical computer science.


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http://www.inrialpes.fr/planete/mobiwan

http://www.isi.edu/nsnam/ns

http://www.isi.edu/nsnam/ns

http://www.comet.columbia.edu/micromobility

http://www.comet.columbia.edu/micromobility

A simulation study on the performance of Mobile IPv6 in a WLAN-based cellular network

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