Transcript

INTERNATIONAL JOURNAL OF NETWORK MANAGEMENTInt. J. Network Mgmt 2002; 12: 41–59 (DOI: 10.1002/nem.420)

A framework for the transmission of streaming mediato mobile devices

By Kevin CurranŁ and Gerard Parr

One interesting problem is the delay imposed upon mobile receivers whenswitching between wireless cells. We provide a solution to this in the formof an extension of Mobile IP’s handoff algorithm. Our solution involvesthe exploitation of mobility prediction to predict a mobile terminal’sfuture location based on its previous history (i.e. the last cell that it hasbeen in) and for the media stream to be already present and cached by nextcells base station ready for receiving by the mobile device. Copyright 2002 John Wiley & Sons, Ltd.

Introduction

M obile IP specifies enhancements thatallow transparent routing of IP data-grams to mobile nodes in the Internet.

In Mobile IP27 a Mobile Host always has a HomeAgent (e.g. the router of the subnetwork the hostusually is attached to). This Home Agent keepstrack of the current point of attachment of themobile host. Whenever the mobile host changesthe network it is connected to, it has to register anew care-of address (COA) with the Home Agent.This association of the Mobile Host’s home addressand the current care-of address is called bind-ing. The care-of address can either be the addressof a Foreign Agent (e.g. a wireless base stationnode) that has agreed to provide services for theMobile Host or the new IP address of the MobileHost itself. A care-of address can be acquiredeither through stateless or stateful address auto-configuration. Traffic to the Mobile Host is always

passed through the Home Agent, and then tun-nelled to the care-of address and in the case of aForeign Agent care-of address; forwarded to theMobile Host by the Foreign Agent. Out-going traf-fic from the Mobile Host does not need to gothrough the Home Agent but the host can directlycommunicate with Correspondent Hosts. By usinga Home Agent as an intermediary, CorrespondentHosts do not need to know the Mobile IP protocolor the current location of the Mobile Host. Theforwarding of packets to the current address of theMobile Host is transparent for other hosts.

The routing tables typically maintain the next-hop (outbound interface) information for eachdestination IP address, according to the numberof networks to which that IP address is connected.The network number is derived from the IP addressby masking off some of the low-order bits. Thus,the IP address typically carries with it informationthat specifies the IP node’s point of attachment.To maintain existing transport-layer connectionsas the mobile node moves from place to place,

Kevin Curran is a Lecturer at the University of Ulster, Magee College. His research is focused on the field of distributed computing especiallyemerging trends within wireless ad-hoc networks, distributed objects, dynamic protocol stacks, multimedia transport protocols and mobilesystems. He can be contacted at [email protected].

Gerard Parr is a Professor of Telecommunications at the University of Ulster, Coleraine. His research interests include ISDN Systems andStandards, Queueing Systems, Asynchronous Transfer Mode Switch Fabric and Communications networks protocols.

ŁCorrespondence to: Kevin Curran, Telecommunications and Distributed Systems Research Group, Northern Ireland Knowledge Engineering

Laboratory, University of Ulster, Magee Campus, Northern Ireland, BT48 7JL, UK.E-mail: [email protected]

Copyright 2002 John Wiley & Sons, Ltd.

42 K. CURRAN AND G. PARR

it must keep its IP address the same. In TCP(which accounts for the overwhelming majorityof Internet connections), connections are indexedby a quadruplet that contains the IP addressesand port numbers of both connection endpoints.Changing any of these four numbers will cause theconnection to be disrupted and lost. On the otherhand, correct delivery of packets to the mobilenode’s current point of attachment depends onthe network number contained within the mobilenode’s IP address, which changes at new pointsof attachment. To change the routing requires anew IP address associated with the new point ofattachment.

In Mobile IP the home agent redirects packetsfrom the home network to the care-of address byconstructing a new IP header that contains themobile node’s care-of address as the destinationIP address. This new header then shields orencapsulates the original packet, causing themobile node’s home address to have no effect onthe encapsulated packet’s routing until it arrivesat the care-of address. Such encapsulation is alsocalled tunneling, which suggests that the packetburrows through the Internet, bypassing the usualeffects of IP routing.

By using this architecture, a Mobile Host canroam between Foreign Agents and its HomeAgent. When the Mobile Host leaves the servicearea of its current Foreign Agent and registerswith a new Foreign Agent, the Home Agent hasto be informed about the change of address.This procedure is called handoff. During sucha handoff, it is possible that the Mobile Hostloses connectivity for a short period of time. Toprovide smooth handoffs and speed up the handoffprocess, the use of several care-of addresses ispossible where wireless service areas overlap.However, only one of those addresses can beregistered with the Home Agent (primary care-ofaddress).

The Mobile IP architecture is well suited forMobile Hosts that change their point of attachmentonly over relatively large time intervals. When fast-moving Mobile Hosts are forced to perform a largenumber of handoffs per time interval, registeringa care-of address with the Home Agent causes toomuch over-head and a too high delay, which inturn results in decreased protocol performance.Several approaches to solve this problem andto provide a more local, hierarchical form of

mobility management are discussed in references30 and 32.

—Mobile IP Handoff—

In Mobile IP all base stations advertise theirpresence by sending beacon messages at a pre-configurable time interval. Mobile Nodes store theaddresses of the base stations within range in alist. When no beacon message of a registered basestation is received for a certain amount of time, thelist entry times out and is removed. Mobile Nodesthat have to perform a handoff because they leftthe service range of their current Foreign Agentchose a base station from the list as their new For-eign Agent. If the list does not contain any entries,the Mobile Node sends an Agent Solicitation Mes-sage. Base stations that receive this message haveto send an advertisement, which then allows theMobile Node to register with them. The handoffis initiated with a Registration Request from theMobile Node. The base station then forwards therequest to the Home Agent of the Mobile Host. TheHome Agent updates the care-of-address (COA) ofthe Mobile Host and installs a so-called encapsula-tor to tunnel IP packets to the mobile host via thebase station. The Home Agent then sends a Regis-tration Reply Message to the base station and thebase station in turn informs the Mobile Node thatthe handoff was successful. From then on, the basestation acts as the Mobile Node’s Foreign Agent.

However, the handoff algorithm itself is keptvery simple. Whenever the Mobile Node receivesa beacon message from a Base Station, it sends aRegistration Request and from then on uses theBase Station as a Foreign Agent. This results ina dropout until the new connection is establishedalthough the Mobile Node could still communicatewith the rest of the network over its current ForeignAgent. The method also works only when theMobile Node ‘hears’ a single Base Station. As soonas service areas of Base Stations overlap, the MobileNode constantly switches between Base Stationsand because of that often cannot establish anytransport connection at all. Since a handoff to anew Base Station generates a certain amount ofoverhead, the simple handoff algorithm producesan unnecessarily large amount of Mobile IP controlpackets.

Copyright 2002 John Wiley & Sons, Ltd. Int. J. Network Mgmt 2002; 12:41–59

TRANSMISSION OF STREAMING MEDIA TO MOBILE DEVICES 43

—Ad Hoc Network RoutingAlgorithms—

An ad hoc network is a collection of mobilenodes forming a temporary network withoutthe aid of any centralised administration orstandard support services regularly available onconventional networks. In this thesis, it is assumedthe mobile hosts use wireless RF transceivers astheir network interface, although many of thesame principles will apply to infra-red and wirebased networks. Some form of routing protocolis necessary in these ad hoc networks sincetwo hosts wishing to exchange packets may notbe able to communicate directly. One problemwith wireless network interfaces is they typicallyoperate at significantly slower bit rates than theirwire-based counterparts. Frequent flooding ofpackets throughout the network, a mechanismmany protocols require, can consume significantportions of the available network bandwidth. Adhoc routing protocols must minimise bandwidthoverhead at the same time as they enable properrouting to take place. Also, ad hoc networksmust deal with frequent changes in topology. Bytheir very nature, mobile nodes tend to wanderaround, changing their network location andlink status on a regular basis. Furthermore, newnodes may unexpectedly join the network orexisting nodes may leave or be turned off. Adhoc routing protocols must minimise the timerequired to converge after these topology changes.A low convergence time is more critical in adhoc networks because temporary routing loopscan result in packets being transmitted in circles,further consuming valuable bandwidth.

A n ad hoc network is a collection ofmobile nodes forming a temporary

network without the aid of any centralisedadministration or standard support servicesregularly available on conventionalnetworks.

For the purposes of this paper, an ad hoc rout-ing protocol is considered to fill the space betweentwo network extremes. At one extreme, the net-work topology is changing so rapidly the only

feasible routing mechanism is for every packetto be flooded throughout the network. At theother extreme, the network topology is sufficientlypermanent and static as to permit the use ofconventional routing mechanisms such as thoseemployed in the Internet. Ad hoc networks arenetworks which lack the support structure andpermanency of traditional networks, yet changesufficiently slowly as to permit the use of a rout-ing protocol to optimise transmission bandwidth.Some of the ad hoc routing algorithms in use atpresent include Destination-Sequenced Distance-Vector Routing (DSDV)26 which is an adaptationof a conventional routing protocol to ad hoc net-works. DSDV is based on the Routing InformationProtocol (RIP)14 used in parts of the Internet;Temporally-Ordered Routing Algorithm (TORA)20

is a distributed routing protocol based on a linkreversal algorithm. It is designed to discover routeson demand, provide multiple routes to a des-tination, establish routes quickly, and minimisecommunication overhead by localising the reac-tion to topological changes when possible; Ad HocOn-Demand Distance Vector (AODV)27 routing isessentially a combination of both DSR and DSDV.It borrows the basic on-demand mechanism ofroute discovery and route maintenance from DSR,plus the use of hop-by-hop routing, sequence num-bers, and periodic update packets from DSDV. Themain benefit of AODV over DSR is the source routedoes not need to be included with each packet.This results in a reduction of routing protocoloverhead. Unfortunately, AODV requires periodicupdates which, consume more bandwidth than issaved from not including source route informa-tion in the packets.7 Signal stability based adaptiverouting (SSA)11 is a variant of the AODV proto-col to take advantage of information available atthe link level. Both the signal quality of links andlink congestion are taken into consideration whenfinding routes. One important difference of SSAfrom AODV or DSR is that paths with strong sig-nal links are favoured over optimal paths. Whilethis may make routes longer, it is hoped discov-ered routes will survive longer; The cluster basedrouting protocol (CBRP)16 is a variation of the DSRprotocol. CBRP groups nodes located physicallyclose together into clusters. Unfortunately, CBRPdepends on nodes transmitting periodic hello pack-ets; a large part of the gains made by DSR arebecause DSR does not require periodic packets of

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44 K. CURRAN AND G. PARR

any kind; Optimised Link State Routing (OLSR)15

is a link state routing protocol. OLSR is an adap-tation of conventional routing protocols to workin an ad hoc network on top of IMEP.10 The novelattribute of OLSR is its ability to track and usemulti-point relays. The idea of multi-point relaysis to minimise the flooding of broadcast messagesin the network by reducing/optimising duplicatere-transmissions in the same region. Each node inthe network selects a set of nodes in its neighbor-hood that will re-transmit its broadcast packets.This set of selected neighbour nodes is called themulti-point relays of that node. Each node selectsits multi-point relay set in a manner to cover allthe nodes that are two hops away from it. Theneighbours that are not in the multi-point relay setstill receive and process broadcast packets but donot re-transmit them.

Mobility Prediction in WirelessNetworks

Many recent papers deal with mobility predic-tion in cellular networks. The tracking schemeproposed in reference 17 uses a Gauss-Markovmodel to predict a mobile’s future location for effi-cient paging. Based on the Gauss-Markov model, amobile’s future location is predicted based on theinformation gathered from the last report of loca-tion and velocity. An extension of the ResourceReservation Protocol (RSVP) for cellular networksis proposed in reference 2. The proposed schemeuses mobility prediction to reserve bandwidth andit is based on the same framework presented inreference 1. In this scheme, each datum of mobilityhistory information consists of a tuple whose ele-ments include the identity of the mobile station, thelast location visited, and a timestamp indicating thetime at which the current cell was entered. Basedon this historical data, a prediction can be madeon the most likely location of the mobile station.This knowledge can then be used for intelligentpre-allocation of resources.

Another scheme that uses prediction to locate amobile in a cellular network is presented in ref-erence 1. Statistical search theory is used in thisapproach by maintaining a history of prior knownmobility patterns of users. Based on this priorinformation, a vector of probability mass functionsconcerning the likely location of a target station is

first computed. These probability mass functionsare then used as input to a search strategy thatspecifies the manner in which a mobile terminalis to be paged. In reference 9 a similar methodto predict a mobile user’s movements in cellularnetworks is used to reserve bandwidth, but theamount of bandwidth to be reserved is dynami-cally adjusted according to the time-varying trafficpattern and the observed handoff dropping events.An adaptive algorithm for controlling the mobilityestimation time window to prevent over-reservingbandwidth is also used.

We have extended the industry standard mobilearchitecture—Mobile IP and added an optimisedhandoff protocol which uses a motion predictionalgorithm to estimate which direction a mobiledevice is moving in by using information suchas signal strength or GPS. It then takes thisinformation and examines a database of nearbycells (wired, cellular, ad-hoc networks etc) and thenstreams multiple multicast multimedia streams(which the device is currently using) to the newnetwork—thereby having a cache of timely datawaiting for the mobile host upon connection tothe network. This handoff algorithm drasticallyimproves upon current handoff algorithms.

Chameleon—the middleware we discuss else-where21 – 25 utilises filter (or proxy) propagation.This approach to filtering allows a filter to movearound the network—thus ensuring that the filterperforms its functions at the optimum point inthe network. Mobile IPCC makes use of thefact that these filters-proxies exist in the networkalready to perform other tasks and uses thesefilters to perform congestion control for receiversat the end of poor links. The Team FilteringService Algorithm (TFS) is responsible for thisoptimisation.

Host mobility requires changing the stationarycomputers executing the service proxy in ourextension to Mobile IP. Let us assume that a usergoes out of his campus with the mobile host. In thecampus, a wireless LAN can be used to connect toservers on the Internet, but the wireless LAN is notavailable out of the campus. However, a cellularnetwork can be used for connecting to the Internetwhen the mobile computer is out of the campus.Figure 1 shows how the mobile computer continuesto connect to the Internet using the service proxy.While the user is within the campus, the mobilecomputer is connected to Proxy 1 using the wireless

Copyright 2002 John Wiley & Sons, Ltd. Int. J. Network Mgmt 2002; 12:41–59

TRANSMISSION OF STREAMING MEDIA TO MOBILE DEVICES 45

Streaming Video

10 MBConnection

Proxy 1

ColourFrames

Internet

Proxy n-1

ProtocolStack

Reconfigured

Laptop

Laptop

Move

Wireless LAN

B & W Frames withLow Frame rate

Figure 1. Host mobility

LAN. However, when the user goes out of thecampus, the service proxy that communicates withthe user’s mobile computer should be moved toProxy n-1 since Proxy 1 does not have an interfacedevice for the cellular network. Their object graphsare also changed according to the bandwidth ofthe cellular network. In this example, an object thatreduces the frame rate of a video stream is insertedin the object graph of the service proxy when theservice proxy is moved to Proxy n-1. When objectgraphs are recreated, the states of objects of the oldservice proxy are moved to the objects of the newservice proxy.

However, if the states of the object graph of theold service proxy are not necessary for buildingan object graph of the new service proxy, Proxyn-1 may need not to communicate with Proxy 1since sending a script from the mobile computercan create the object graph of the new serviceproxy.

Our approach adopts a similar protocol devel-oped in I-TCP3,4 for negotiating the mobile hostand service proxies when the service proxies aremoved. The details of this handoff from one net-work to another follow.

—Mobile IPYY Architecture—

Packets from a Correspondent Host to theMobile Host are routed to the corresponding Home

Agent. The Home Agent looks up the address ofthe Mobile Host and tunnels the packet. Since allpackets are sent over the Home Agent (unlessroute optimisation is used), the Home Agent canbe a performance bottleneck when the number ofMobile Hosts increases. In this case, a hierarchicalstructure of multiple Home Agents can improveperformance and scalability. Hierarchical HomeAgents can distribute the Mobile Hosts amongthemselves to balance the load.

The architecture aims to support multiple wire-less technologies and thus has to be able to usemultiple service providers. These service providersassume the role of the Foreign Agents. A MobileHost is assigned an IP address by its currentForeign Agent and can now be reached usingthat address. Thus, the care-of address is theaddress of the Mobile Host (co-located care-ofaddress).

The internal structure of the service providerswith routers and base stations is not modelled inFigure 2, since neither the Mobile Host nor theHome Agent need to know about it. The type ofmobility support (be it Mobile IP, Cellular IP or aproprietary protocol) used by the service provideris transparent for the Mobile Host. In other words,the framework only handles vertical handoffs fromone service provider to another without takinghorizontal handoffs within the service area of asingle provider into account.

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46 K. CURRAN AND G. PARR

Mobile Host

Mobile Host

Home Agent

Router x.xx.xx

Router x.xx.xx

Router x.xx.xx

Mobile Host

Foreign Agent

Router

LAN (Ethernet)

Wireless Antenna

Video Stream

Wireless ServiceProvider 2

Wireless ServiceProvider 3

Video Stream

Foreign Agent 1

Foreign Agent 2

Wireless ServiceProvider 1 Mobile device

with noconnectivity

InternetCorrespondent

Host

Mobile Host

Foreign Agent 3

Figure 2. Mobile IPCC overview

—Mobile IPYY Handoff Algorithm—

In a cellular network, a mobile user will travelfrom one access point to another. Therefore, the lasthop connection between a mobile terminal and itslocal base station is often rerouted. This reroutingprocess is called a handoff. When a mobile usertravels to a new cell, it is important that the networkcan provide an uninterrupted handoff for the activeconnection. In the case for an ad hoc network, theconnectivity between neighbouring nodes is verydynamic. This is due to the fact that all nodesare non-stationary. It is crucial for the routingprotocol to adapt quickly to such a fast-changingenvironment in order to reduce the amount ofdisruptions suffered by the link disconnections. Insuch an environment, it is also desirable to reducetransmission overhead and power consumptionbecause the bandwidth for a wireless channel islimited.

Typically, a mobile user’s travelling pattern isnot totally random (e.g. a car cruising on a road, a

person walking in a north-south direction, etc.). Byexploiting a mobile user’s non-random travellingpattern, it is possible to predict the future state ofa network topology and thus provide continuousaccess during period of topology changes. This partof the dissertation covers the topic of using mobilityprediction to minimise service disruptions incellular and ad hoc networks to the actual mediastream delivered to the mobile receiver. Mobilityprediction is used to lower handoff delays thatare common in cellular network handoffs. For adhoc networks, routing protocols are enhanced bymobility prediction to perform path reconstructionprior to topology changes.

Wireless technologies vary considerably inoffered bandwidth and changes of a few orders ofmagnitude are possible. Thus, it is necessary thatapplications adapt to changed network conditionsas fast as possible. When a handoff to a low band-width provider is necessary but it takes a StreamingVideo application several seconds until it adjust itsbandwidth from high quality audio with 64 KBit/s

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TRANSMISSION OF STREAMING MEDIA TO MOBILE DEVICES 47

to low quality voice with only 6 KBit/s, it is possi-ble that due to congestion no traffic at all can be sentfrom or to the Mobile Host for that period of time.When also Mobile IP control packets are lost (e.g.binding updates), performance can suffer for muchlonger than the time of congestion. In dealing withsuch situations, applications profit from additionalinformation that can be provided by the mobilenode. The mobile node has information about themaximum bandwidth as well as concurrent appli-cations, which allow an application to determineits optimal throughput. To provide this, a band-width manager is installed in each Mobile Host.The bandwidth manager has to ensure that MobileIP control packets are transmitted with a higherpriority than all other traffic and it can discardpackets of applications that excessively use scarcebandwidth even before they are passed down theprotocol stack.

W ireless technologies vary considerablyin offered bandwidth and changes of a

few orders of magnitude are possible.

Base stations have to announce their presence bysending periodic beacon messages. Upon receptionof a beacon message, a mobile node can requestForeign Agent services from that base station.When the mobile node leaves the service area ofthe base station it has to perform a handoff to a newbase station. A very basic handoff algorithm is tonegotiate Foreign Agent services with a new basestation as soon as the old base station becomesunavailable. The mobile node detects this whenit does not receive beacon signals for a certainamount of time. To prevent that base stationsare erroneously considered unreachable becausebeacon messages are lost, the timeout interval forbase stations should be a multiple of the beaconperiod. However, when the mobile node loses itscurrent base station and a handoff is necessary,the mobile node cannot communicate until thebase station timer expires and the mobile nodenegotiates Foreign Agent services with a new basestation. This results in a communication dropoutof up to a few seconds. The network architecturepresented in this report focuses on mobile nodes,

whether moving at walking pace or travellingin a vehicle. Location information, which can beobtained via a GPS system or direction of travelbetween wireless networks, can be used to optimisethe handoff algorithm for Mobile IP. By keepingtrack of its current location, the mobile node canpredict when a handoff is likely to happen andnegotiate Foreign Agent services with a new basestation beforehand. This effectively prevents acommunication dropout. When the mobile nodeis within a certain range of the border of thecoverage area, it tries to perform a handoff to abase station that is located closer to the mobilenode. The mobile node can obtain this informationin several ways:

ž The signal strength of the beacon messagescan be used to estimate how close the mobilenode is to the border of the service area. Whenit falls below a certain threshold value themobile node performs a handoff to the nearestbase station it can hear. During the handoff,the mobile node is still reachable via the oldbase station.

ž When base stations send information abouttheir maximum service range and their loca-tion in the beacon messages, the mobile nodecan compute its distance to the base station. Bycomparing the distance to the service range, itcan estimate the likeliness of leaving the basestations service range and perform a handoffin time should it be necessary.

ž Map information about base stations and theirservice ranges can be stored in a database at themobile node. When a mobile node identifiesa base station, it can look up its locationand service range and perform the samecalculations as described above. Additionalinformation of a car navigation system, suchas destination and the anticipated route canbe used to further optimise the algorithm.

Due to the previously discussed shortcomings,substantial changes to Mobile IP were necessary.The handoff procedure was redesigned to improveperformance in network environments with a highhandoffs frequency. Priorities can be assigned tobase stations to establish an order of preference.The Mobile Host always performs a handoff to thebase stations with the highest priority within range.This feature can be used to include bandwidth,cost, and provider preferences of the user (i.e. the

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48 K. CURRAN AND G. PARR

mobile node) into the simulations. As an additionaloption, the handoff protocol can take the distanceto base stations into account to reduce the numberof handoffs and to ensure a timely handoff in orderto prevent loss of connectivity.

When the Mobile Host receives a beacon mes-sage, it checks whether the corresponding basestation is already in the list of base stations withinrange. If yes, the entry is updated and the expi-ration time of the entry is adjusted. If the basestation is not in the list, a new entry is created.The Mobile Host then checks if it currently hasa care-of-address. If not, it immediately sends aRegistration Request to the base station that sentthe beacon message. If the advertisement was fromthe current Foreign Agent, the Mobile Node rereg-isters to refresh the binding to the Foreign Agent.Finally, a Registration Request is also sent whenthe priority of the beacon is higher than the prior-ity of the base station that is currently used as theForeign Agent.

The Mobile Host caches the addresses of all basestations to which is sends requests. The MobileHost only processes Registration Reply Messagesfrom base stations in the cache. Other ReplyMessages from nodes that the Mobile Host did notcontact are discarded. When a valid RegistrationReply arrives at the Mobile Host, it updates itscare-of-address as well as other parameters (e.g.priority of the current base station) and clearsthe cache. Thus, cache entries have a timeoutinterval in proportion to the beacon interval. Thehandoff procedure can be further optimised bytaking the distance to base stations into account.For each Mobile Hosts, base stations are divided

Far Near Unreachable

BaseStation

Figure 3. Coverage Area Boundary

into the categories near, distant, and unreachableas illustrated in Figure 3.

The ratio of near range to overall range is calledboundary parameter b. A b value of 0.2 for instance,means that the Mobile Host tries to performhandoff when its distance to the current basestation is longer than 80% of the total service range.The overall preference structure is as follows:

1. If base stations are within near range choosethe one with the highest priority. The HomeAgent is generally set to a higher prioritythan Foreign Agents to prevent unnecessarytunnelling of packets.

2. If several base stations fall into this categorychoose the nearest of them.

3. If no base station within near range thenchoose distant base station with highestpriority.

4. If several base stations fall into this categorychoose the nearest of them.

5. If no base station is reachable send a Solicita-tion Message

Thus, as soon as the Mobile Host leaves the nearrange of the current Foreign Agent, it performsa handoff if there is another near base station.The Mobile Node (Figure 4) does not performa handoff when it receives a beacon messagefrom a closer base station, which has the samerange classification. During the transition fromone Foreign Agent to another, the Mobile Noderetains its reachability via the old care-of-address(provided the old Base Station is still withinhearing range).

Some video frames may be lost during themovement of the service proxy since forwardingvideo frames from the old service proxy to thenew service proxy may violate timing constraintsof the video frames. However, in our approach, aprotocol that is similar to the protocol presentedin reference 29 is used to minimise the loss ofvideo frames. During the movement of the serviceproxy, a new stationary computer for executingthe service proxy joins into the multicast groupfor receiving the video stream that the mobilehost want to receive. This means that both serviceproxies receive the same video stream during thehandoff of the service proxy. These service proxiesnegotiate not to send the same video frames to themobile computer. If the handoff is completed, the

Copyright 2002 John Wiley & Sons, Ltd. Int. J. Network Mgmt 2002; 12:41–59

TRANSMISSION OF STREAMING MEDIA TO MOBILE DEVICES 49

PHY

MAC

IFQ

LL

Antenna

ARP

Addr

RPM

Modulation SchemePropagation Model

Port

Source/Sink

RTAgent

Mobile IP++

Demux

Wireless channel

arptable

sendtarget

recvtable sendtarget

recvtarget

recvtarget sendtarget

Channel

entry

Addr demux

Ip addr

Port demux

LL_(0)

Figure 4. Structure of a Mobile IPCC Node

old stationary computer that executes the serviceproxy leaves from the multicast group.

—Mobile IPYY Predictive MovementAlgorithm—

In reality, mobile terminals move accordingto the presence of highways, streets, and roads.The mobile terminals do not move randomly andfollow patterns that are somewhat predictable. Forexample, a mobile user travelling on a highwayfollows the direction of the highway and he orshe is not likely to change direction randomly.Therefore, it is possible to predict the movementof a mobile user in a particular area with theknowledge of previous local mobility patterns.We will study the scheme that will predict thenext cell a mobile will travel to based on themobility information acquired in the current cell.In the following sections we will first describe thegeneral framework used for predicting a user’s

future location. This is followed by the discussionof different bandwidth reservation schemes.

I n reality, mobile terminals move accordingto the presence of highways, streets, and

roads.

Let i denote the cell that a mobile m is currentlyin, where i 2 I and I is the set of all cells in thenetwork. Assume each mobile keeps track of thelast M cells that it has travelled through. We definethis sequence of cells to be the mobility state ofmobile m. Let the mobility state of a mobile beequal to s. We define S to be the set of all possiblevalues of s such that s 2 S,

s D fs1, s2, . . . , smg, sk 2 I, k D 1, 2, . . . , M

Let N denote the number of access areas for cell i(6 in a hexagonal cell configuration). We define the

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50 K. CURRAN AND G. PARR

set of transition probabilities, or the likelihood thatthe mobile will move to each of the neighbouringcells, for state s to be Ps. We then have

Ps D fPs1, Ps

2, . . . , PsNg, s 2 S, Ps

k � 1, k D 1, 2, . . . , N

andN∑

K D1

Psk D 1

Assume 1 � J � N, Psj will be the probability that

mobile m will travel to cell j given that its mobilitystate is s and it is currently in cell i. A generaldescription of the algorithm is given as follows:

ž For each mobile that arrives in the currentcell, the current base station predicts its nextlocation based on the probability array Passociated with the particular state of thetracking buffer and reserves the requiredbandwidth in the selected cell.

ž When the mobile leaves the current cell, thecurrent base station updates the probabilityarray Ps for state s based on the neighbourlocation it actually ends up travelling to.

The base station for each cell establishes connec-tions to each of its neighbours. These connections

1

2

3

4

5

6

Active Base Station

Mobile HostRoad

Figure 5. Mobile within a cell

1

2

3

4

5

6

Active Base Station

ReplicatedVideo Stream

Figure 6. Mobile moving toward next cell

only send control traffic, which is used to informthe base station associated with the mobile’s pre-vious cell. The previous base station then updatesits probability array P accordingly. Using the con-nections between base stations instead of allowingthe mobile host to send the reservation informa-tion message will alleviate the wireless bandwidth.An example of how the algorithm works is illus-trated above. As we can see in Figure 5, themobile arrives in cell 2 through cell. Based onthe probabilistic information base station 2 accu-mulated about all previous mobiles that arrivedthrough cell 1, it replicates the current streamthat the mobile host is receiving and forwardsthis stream to base station for cell 4 (Figure 6).In Figure 7, we can see that the mobile actu-ally arrives in cell 4 where the stream has beencached awaiting retrieval with minimal handofflost packets. Base Station 4 now has responsi-bility for streaming data to the mobile host andindeed implementing the next stage of the predic-tion algorithm. Throughout this procedure, eachbase station will accumulate the statistics and

Road

Active BaseStation

1

2

3

4 5

6

Figure 7. Mobile Host receiving video in ‘new’ cell

Copyright 2002 John Wiley & Sons, Ltd. Int. J. Network Mgmt 2002; 12:41–59

TRANSMISSION OF STREAMING MEDIA TO MOBILE DEVICES 51

updates its predictive movement probability infor-mation.

Simulation EvaluationThe basis for our work is the LBL Net-

work Simulator, ‘ns’, developed by the Net-work Research Group at the Lawrence BerkeleyNational Laboratory.12,19 Ns provides a frameworkfor inspecting the dynamic behaviour of networktraffic, congestion, and other network characteris-tics. We are primarily interested in the issue of ratecontrol, however, as we are working on a best effortnetwork, we assume that the underlying networkintroduces data loss and error into our transmis-sions. We also assume that data can be deliveredout of order to a receiver.

—Predictive Movement Algorithm—

A real-time flow is a connection that deliversdata packets with a rigid timing requirementsuch as the transmission of a video stream.Since the topology of an ad hoc network isvery dynamic, real-time connections are subjectto frequent disruptions. During topology changes,routes can be broken abruptly resulting in real-time packets being dropped. Hence we propose anextension of the On-Demand Multicast RoutingProtocol (ODMRP)13 which uses the mobilityinformation obtained from the mobile hosts topredict topological changes. The scheme performsrerouting for a real-time flow before a pathbecomes invalid. This is done using a mechanismwe refer to as ‘multi-hop handoff’. Our goal is tominimise disruptions of real-time sessions due tomobility. Note that in an ad hoc network, the lostof data packets can cause significant throughputdegradation even for non real-time data such asTCP31 traffic. Here we only focus on real-timeflows although the concept of our scheme can stillbe applied to non real-time data. Also the randomMAC layer turnaround time in transmission overa multi-hop wireless network induces large jitterin the packets.5 However, we only deal withjitter caused by routing stability problems in thisthesis.

The simulation model consists of a cluster ofbetween 4 to 30 cells in each of the simulations. The

base station for each cell resides in the center of acell. The cells are wrapped around so the topologyof the simulated wireless networks represents asphere. This means that the handoff rates in allthe cells are approximately similar. We assume thearrival rates of call attempts in all cells to be Poissonwith an average value equals to �. The call durationfor each mobile is exponentially distributed withrates equal to �. The direction that each mobiletravels is random (between 0 and 360 degrees) witheach mobile travelling with velocity �. Simulationruns were conducted for the default algorithm(when no bandwidth is reserved) and for thevarious schemes with predictive reservation. Thediameter of a cell is approximately 100 metersand � is equal to 5 meters/sec for all mobiles(micro/pico cell environment). � is exponentiallydistributed with an average value of 300 seconds.Each base station has a capacity of 10 Mbps andeach CBR connection requires 1 Mbps. Therefore,each base station can support up to 10 mobiles atthe same time.

To assess the improvements of using mobilityprediction, we created a series of simulationswhere the speed of the mobile device was variedwith speeds from 0 km/hr to 72 km/hr. A multicastgroup of size 10 with one sender is used and eachsender sends data at the rate of 10 packets persecond. Mobile IPCC’s refresh interval is set to1.5 seconds, while the minimum refresh intervaland maximum refresh interval for Mobile IPCC areset to 1.5 seconds and 60 seconds respectively. Themetrics of interest include packet delivery ratio,number of control bytes transmitted per data bytedelivered, and number of total packets transmittedper data packet delivered.

The packet delivery ratio as a function of themobility speed is shown in Figure 8. As speedincreases, the routing effectiveness of MobileIP degrades rapidly compared to Mobile IPCC.Mobile IPCC has very high delivery ratios ofover 90% regardless of speed. As the routes arereconstructed in advance of topology changes,most data are delivered to multicast receiverswithout being dropped. In Mobile IP (usingODMRP), however, Join Requests and Join Tablesare transmitted periodically without adapting tomobility speed and direction. At high speed,routes that are taken at the Join Request phasemay already be broken when Join Tables arepropagated.

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52 K. CURRAN AND G. PARR

0

0.2

0.4

0.6

0.8

1

10 20 30 40 50 60 70

Mobility Speed (Km/Hr)

Pac

ket

Del

iver

y R

atio

Mobile IP++ Mobile IP

Figure 8. Packet delivery ratio as function ofmobility speed

0

0.5

1

1.5

2

2.5

0 10 20 30 40 50 60 70

Mobility Speed (Km/Hr)

Avg

No

of t

otal

pac

kets

tra

nsm

itte

d pe

r da

ta p

acke

tde

liver

ed a

s fu

ncti

on o

f m

obili

ty s

peed

Mobile IP++ Mobile IP

Figure 9. Avg No of total packets sent per datapacket delivered as function of mobility speed

The number of total packets (i.e. Join Requests,Join Tables, Join Data, Data, and active acknowl-edgments) transmitted per data packet deliveredis presented in Figure 9. This measure indicatesthe channel access efficiency. As we can see from

Figure 9, the number for Mobile IP remains rel-atively constant after an initial increase. Sincethe number of data packets delivered and theamount of control bytes transmitted both decreaseas mobility increases, the number for Mobile IPremains almost unchanging. The measures forMobile IPCC gradually increase with mobilityspeed. Since Mobile IPCC delivers a high por-tion of the data to destinations regardless of speed,more control packets must be sent in order toadapt to the increasing speed. Thus the total num-ber of packets transmitted increases with speed.Also, since Mobile IPCC uses longer, more stableroutes compared to Mobile IP’s ODMRP, MobileIPCC sends data over a longer hop length thanODMRP, and therefore, more data packets aretransmitted.

We have neglected the issues of system costin this thesis. Obviously there is an overheadinvolved in the prediction movement algorithmbeing implemented within each base station andend host. There is also the issue of updates pass-ing between nodes. There is also the issue ofthe replicated stream using up precious band-width. To justify our assumptions, we presumethat there is sufficient bandwidth available for thereplicated stream and that the benefits of shorterhandoff delays outweigh the additional complex-ity and bandwidth usage. From a wireless serviceprovider’s standpoint, it is important to maintainlow handoff delays and high bandwidth utiliza-tion in order to maximise revenue. From a user’spoint of view one would like to minimise handoffdropping probabilities and call termination prob-abilities. In addition to the performance results inthe simulation runs, in real life scenarios we canexpect our proposed scheme to perform better thansimulation due to the fact that in our simulation weassume a mobile can move in any direction, whichis not the case in real life scenarios as mentionedpreviously.

We have performed a series of simulations usinga mobility prediction algorithm. The predictivemovement is accomplished by accumulating statis-tics about mobility patterns in a particular area.Results from simulation indicate that by using pre-dictive movement algorithms we can obtain animprovement in quality of service for the con-nections without wasting significant amount ofbandwidth.

Copyright 2002 John Wiley & Sons, Ltd. Int. J. Network Mgmt 2002; 12:41–59

TRANSMISSION OF STREAMING MEDIA TO MOBILE DEVICES 53

—Mobile IPYY Coverage AreaBoundary—

The coverage area boundary parameter for thehandoff protocol greatly influences the perfor-mance of the handoff. If set to a too low value, itcannot guarantee a smooth handoff without packetloss. If however it is set to a too high value, perfor-mance is decreased by the overhead caused by toomany unnecessary handoffs. The following simu-lations compare protocol performance for differentboundary parameter values and are aimed to findan optimal value.

For the simulations, we used the scenarioparameters in Table 1 and Table 2 and alongwith the two basic scenario topologies depicted

T he coverage area boundary parameter forthe handoff protocol greatly influences

the performance of the handoff.

in Figure 10. Scenario 1 has only a small numberof base stations with large service areas, while inscenario 2 the number of base stations is muchhigher and the base station range is smaller.This results in different time intervals betweenconsecutive handoffs. For each simulation run,these topologies were populated with 10 MobileHosts located at random positions. Throughout thesimulations, the hosts moved to a random location

No. Address Radius # Base Stations Base Stat Range Priority Colour

1 2.0.0 50 1 3.0 1 DarkGreen

2 3.0.0 20 12 20.0 1 LightGreen

3 4.0.0 40 12 5.0 2 Yellow

4 5.0.0 10 3 5.0 2 Black

5 6.0.0 80 2 5.0 2 LightBlue

6 7.0.0 30 1 5.0 2 Orange

7 8.0.0 100 35 20.0 1 Red

8 9.0.0 50 20 30.0 1 DarkGreen

9 10.0.0 40 5 5.0 1 Yellow

10 11.0.0 80 45 50.0 1 Blue

11 12.0.0 60 8 15.0 1 Violet

Table 1. Scenario Parameters 1

No. Address Radius # Base Stations Base Station Range Priority Colour

1 2.0.0 45 1 3.0 1 Yellow

2 3.0.0 20.0 49 3.6 1 Green

3 4.0.0 8.0 5 6.0 2 LightGreen

4 5.0.0 30.0 29 8.0 1 Black

5 6.0.0 20.0 13 8.0 1 DarkGreen

6 7.0.0 5.0 5 3.0 1 Blue

7 8.0.0 5.0 5 3.0 1 LightBlue

Table 2. Scenario Parameters 2

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54 K. CURRAN AND G. PARR

FA 4.0.0 FA 3.0.0 FA 2.0.0 FA 5.0.0

Scenario 1: Large range - Small no. of BS's Scenario 2: Small ranges - Large no. of BS's

1.0.0

1.1.0

HA 0.0.0

FA 6.0.0 FA 7.0.0

MH 0.0.5 1.0.0HA 0.0.0

MH 0.0.2

FA 2.0.0

MH 0.0.7

FA5.0.0

MH0.0.3

FA 6.0.0

MH 0.0.9

MH 0.0.1

FA 7.0.0FA 8.0.0

1.1.0

FA 3.0.0MH 0.0.4

MH 0.0.0

MH 0.0.5

MH 0.0.10

FA 4.0.0

Figure 10. Scenarios for coverage area boundary simulations

4000

5000

6000

7000

8000

9000

10000

0.02 0.05 0.1 0.15 0.2 0.3 0.4 0.5

Coverage Area Border Size (%)

Tot

al n

umbe

r of

pac

ket

drop

s (K

B)

Packet drops

Figure 11. Number of packet drops with different service area boundaries

at a random speed, thus creating a large numberof different connectivity and handoff patterns.

We ran simulations with a boundary parameter bof 0.02, 0.05, 0.1, 0.2, and 0.5. Multiple simulationswere conducted for each setting and the resultswere averaged to reduce the impact of outliers.The results are depicted in Figures 11–13.

The total number of handoffs increases inproportion to the boundary parameter from 112(b D 0 : 02) to 187 (b D 0 : 5). Also the overallthroughput of the Mobile Hosts is proportionalto the size of the coverage area boundary forsmaller boundary parameter values. Handoffs areperformed well before the Mobile Host leaves the

coverage area and handoff related packet dropsare rare. The highest throughput is achieved forb D 0 : 2. For higher values of b, the throughputdecreases again, caused by a very high number ofhandoffs and the resulting overhead. Thus, optimalvalues for b are in the range of 0.1 to 0.2, dependingon the actual overhead a handoff causes in a realenvironment. (Figure 14).

—Mobile IPYY Streaming MediaThroughput—

In this set of simulations, we focus on theactual throughput of streaming media streams

Copyright 2002 John Wiley & Sons, Ltd. Int. J. Network Mgmt 2002; 12:41–59

TRANSMISSION OF STREAMING MEDIA TO MOBILE DEVICES 55

020406080

100120140160180200220240

0.02 0.05 0.1 0.15 0.2 0.3 0.4 0.5

Coverage Area Border Size (%)

Num

ber

of H

ando

ffs Handoffs

Figure 12. Number of handoffs with different service area boundaries

4000

5000

6000

7000

8000

9000

10000

0.02 0.05 0.1 0.15 0.2 0.3 0.4 0.5

Coverage Area Border Size (%)

Ove

rall

Thr

ough

put

(KB

)

Throughput

Figure 13. Overall throughput with different service area boundaries

0500

100015002000250030003500400045005000550060006500700075008000850090009500

10000

0.02 0.05 0.1 0.15 0.2 0.3 0.4 0.5

Coverage Area Border Size (%)

Com

pari

son

of H

ando

ffs,

Pac

ket

loss

and

Thr

ough

put

HandoffsThroughputPacket drops

Figure 14. Handoffs, packet loss and throughput for various area boundaries

over various topologies and bandwidths. Weexperiment with a variety of packet sizes andbottlenecks etc and we compare standard UDPstreams with the actual Mobile IPCC protocol. Thetotal simulation time varies from 140–300 seconds.The topology consists of between 20 and 40 base

stations within a large coverage area, between 10and 20 base stations within a medium coveragearea, and between 1 and 10 base stations withina small coverage area. The base stations and themovement pattern of the Mobile Host are arrangedso that the Mobile Host starts out with a base

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56 K. CURRAN AND G. PARR

No. Address Radius # Base Stations Base Station Range Priority Colour

1 2.0.0 — 1 3.0 1 DarkGreen

2 3.0.0 20.0 49 3.6 1 Green

3 4.0.0 8.0 5 6.0 2 LightGreen

4 5.0.0 30.0 29 8.0 1 Blue

5 6.0.0 20.0 13 8.0 1 DarkGreen

6 7.0.0 5.0 5 3.0 1 LightBlue

7 8.0.0 5.0 5 3.0 1 LightBlue

Table 3. Traffic types scenario parameters

FA4.0.0

FA3.0.0

FA2.0.0

FA5.0.0

FA6.0.0

FA7.0.0

FA 0.0.0

1.0.0

1.2.01.1.0

FA 2.0.0

FA0.0.0

1.1.0

1.0.0

FA 3.0.0

MH 0.0.1

FA 4.0.0

FA 2.0.0MH 0.0.1

FA 3.0.0

FA 4.0.0

HA0.0.0

1.0.0

1.1.0

FA 5.0.0

FA 6.0.0

FA 7.0.0

(a) (b) (c)

Figure 15. Scenarios for FTP/TCP streaming media flows throughput

station with a small coverage area and a highbandwidth (1 MBit/s). After 100 seconds, theMobile Host starts to move and as a consequencehas to switch to a medium size base station witha bandwidth of 30 KBit/s. When it leaves theservice range of that second base station it isforced to switch to the base station with thelargest coverage area and the lowest bandwidth(10 KBit/s). The Mobile Host completely losesconnectivity from time to time. After regainingconnectivity, it performs a similar sequence ofhandoffs in reverse order (i.e. first to the largebase station, then to the medium base station, andthen to the small base station).

The traffic used in the simulations wasmedium–low bandwidth streaming media (UDPflows) with raw data rates between 100 KBit/s and5.2 KBit/s. We created three scenarios (Figure 15),

all of which use UDP traffic as well as MobileIPCC Control packets. In the first scenario, nostreaming media traffic is used and in the secondscenario there is an additional flow of streamingmedia traffic with a bandwidth of 100 KBit/s anda packet size of 60 Bytes. The third scenario has aflow with a bandwidth of 5.2 KBit/s and a packetsize of 30 Bytes.

Throughput results for a standard 100 K UDPflow scenario is shown in Figure. 16. Figure 17,however, depicts the same flow using mobileip backoff. The graph clearly demonstrates thatMobile IPCC causes the mobile device to receivea ‘near complete’ stream with no dips in per-formance throughout the 140 seconds whereas thestandard ‘non-predictive’ algorithm drops the con-nection totally from times 0–8 seconds, 31–39 sec-onds, and again from 48–51 seconds.

Copyright 2002 John Wiley & Sons, Ltd. Int. J. Network Mgmt 2002; 12:41–59

TRANSMISSION OF STREAMING MEDIA TO MOBILE DEVICES 57

200

100

Thr

ough

put (

KB

it/s)

00 20 40 60 80

Time (s)100 120 140

node 5

Figure 16. Streaming media 100 K (standard)

200

100

Thr

ough

put (

KB

it/s)

00 20 40 60 80

Time (s)100 120 140

node 5

Figure 17. Streaming 100 K Mobile IPCC

Related WorkThe GTS protocol18 attempts to address the prob-

lems that face computers that are only intermit-tently attached to a network (mobile). GTS buildsa hierarchy as receivers join the multicast group.Servers located at each site are connected to otherservers higher in the hierarchy, and eventuallyto the source. Each server knows of its children,whether they are receivers or other servers. Deliv-ery from a server to its child is unicast, using anyexisting reliable protocol the two hosts agree to.GTS facilitates this flexibility by specifying com-munication end-points as URLs, including a ‘ticket’indicating the multicast channel. When discon-nected hosts are unavailable, the server must spoolthe message until it can be delivered. Thus, GTS isnot prompt in its delivery, but robust. It is moreuseful for replicated databases or software dis-tribution than multimedia. Further, since senders

must contact the single sequencer server directly,only a limited number of senders can be supported.

Reference 8 describes a protocol called QoS-A that distributes multicast data through care-fully selected nodes in a hierarchy, which areequipped to filter multimedia streams to reducetheir demands on the receiver’s hardware. Forexample, an audio stream broadcast from a radiostation containing stereo CD-quality sound couldbe reduced to a stream containing only mono CD-quality sound or even telephony-quality soundto meet the restrictions of bandwidth and audiohardware available to the receiver. Similarly, anMPEG-2 stream could be reduced to an MPEG-1stream, or MPEG-1 could be reduced to containonly I-frames, or to contain only audio for mobilecomputers with very low bandwidth and essen-tially no continuous video capabilities. To facilitatefeedback, the protocol allows both clients and fil-ters to notify upstream filters of their limitations.If all the clients of a filtering node have a com-mon limitation, for example, all can display onlymonochrome video, the limitation is passed up thehierarchy towards the source. Filters are expectedto reduce the bandwidth of a stream until it barelymeets the limitations of a destination.

There is much overlap between QOS-A andChameleon. The most obvious difference is thatin Chameleon, end-users can explicitly state theircapabilities. A client capable of only monochromevideo can indicate such to upstream filters. Thefilter can then remove colour, and reduce therequired bandwidth without a noticeable impactat the client. QoS-A has no similar mechanism.

In references 28 and 33 a stream is decomposedinto two connections, and an intermediate com-puter connects the two connections. When thebandwidth of a wireless network becomes low,an intermediate stationary computer filters datafrom a high-speed network before sending thedata to a mobile computer. The intermediate com-puter filters the data according to the content. Forinstance, video data may be degraded by reducingthe size of each video frame. The solution answersthe problem caused by drastic changes of net-work bandwidth, but it does not solve the problemwhen network bandwidth is changed dynamicallyduring the execution of applications. Also, the sys-tem does not provide programming supports forcreating intermediate filters systematically.

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58 K. CURRAN AND G. PARR

ConclusionWe have outlined an extension to Mobile

IP, which serves as a vehicle communicationarchitecture. Directional movement informationof the mobile host is used to predict whichcell the host will move to. To overcome theinherent delays in cellular handover—we havethe replicated stream cached in the new cellawaiting retrieval by the mobile host with minimaldelay. Additional location information availablevia GPS can be used to optimise the handoffprocess. Mobile IPCC control packets are givenpriority in order to ensure the smoothness of theprotocol.

The objective of the experiments was to inves-tigate the performance of wireless access meth-ods in a simulated media-streaming environ-ment where some of the moving participantsare receiving a media feed from a server. Ina wireless environment, it is very important tomaximise the use of the limited, available band-width while, at the same time, minimising thepropagation delay and delay variation of time-sensitive information over the wireless link. Ourexperiments validate our expectation that giventhe typical processing power of platforms todayand the relatively low bandwidth of the inter-net, the overhead of application adaptation isrewarded by the reduction in transmission timeover the a wide area network alongside theimplementation of movement prediction algo-rithms within filters/transcoders within the net-work.

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