Minimizing the Handoff Latency in Ad-Hoc Networks When Streaming Media to Mobile Devices

International Journal of Wireless Information Networks, Vol. 8, No. 3, July 2001 ( 2001)

1068-9605/ 01/ 0700-0177$19.50/ 0 2001 Plenum Publishing Corporation

177

Minimizing the Handoff Latency in Ad-Hoc Networks whenStreaming Media to Mobile Devices

Kevin Curran

The number of mobile devices connecting to networks independently of a fixed point of attachmentis increasing. These wireless networks differ in bandwidth, size and location of the coverage area,access costs and network characteristics. Mobile multimedia devices such as PDA’s, palmtops andlaptops will also vary greatly in size and processing power. The common denominator however, isthat all these devices will require the optimal delivery of networked multimedia data.

One interesting problem is the delay imposed upon mobile receivers when switching betweenwireless cells. We provide a solution to this in the form of an extension of Mobile IP’s hand-off algorithm. Our solution involves the exploitation of mobility prediction to predict a mobileterminal’s future location based on its previous history (i.e., the last cell that it has been in) and forthe media stream to be already present and cached by next cells base station ready for receivingby the mobile device.

We cater specifically for continuous media applications, which can be especially effected bysevere degradation in quality due to movement between cells. We present the results of a seriesof simulations of the Mobile IP++ protocol, which demonstrate the effectiveness of the ad-hocprotocol when mobile hosts move in predictable patterns between cells.

KEY WORDS: Ad-Hoc networks; media stream; Mobile IP++ protocol.

1. INTRODUCTION

An isochronous application (e.g. Streaming VideoPresentation) must include some time-critical elementsuch as a media stream, i.e. a continuous stream ofbits with strict time dependencies between those bits.Streamed applications are essentially one-way flows ofinformation such as broadcast or on-demand video andaudio services. Isochronous Internet applications havequality of service (QoS) requirements that must be con-sidered on an end-to-end basis. In taking an end-to-end perspective, end-system and network capabilitiesare equally imporrtant in delivering the QoS supportrequired at the application layer. For media requiring

1 Telecommunications & Distributed Systems Reserach Group, North-ern Ireland Knowledge Engineering Laboratory, University ofUlster, Magee Campus, Northern Ireland, BT48 7JL, UK. Email:[email protected]

timely guarantees, application designers are primarilyconcerned with temporal properties such as delay, jit-ter, bandwidth, synchronisation and reliability propertiessuch as error-free delivery, ordered delivery and fairness.

Mobile IP specifies enhancements that allow trans-parent routing of IP datagrams to mobile nodes in theInternet [27]. In Mobile IP, a Mobile Host always hasa Home Agent (e.g. the router of the sub network thehost usually is attached to) where the Home Agent keepstrack of the current point of attachment of the mobilehost. Whenever the mobile host changes the network itis connected to, it has to register a new care-of address(COA) with the Home Agent. This association of theMobile Host’s home address and the current care-ofaddress is called binding. The care-of address can eitherbe the address of a Foreign Agent (e.g. a wireless basestation node) that has agreed to provide services for theMobile Host or the new IP address of the Mobile Host

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itself. A care-of address can be acquired either throughstateless or stateful address autoconfiguration. Traffic tothe Mobile Host is always passed through the HomeAgent, and then tunnelled to the care-of address and inthe case of a Foreign Agent care-of address; forwarded tothe Mobile Host by the Foreign Agent. Out-going traf-fic from the Mobile Host does not need to go throughthe Home Agent but the host can directly communicatewith Correspondent Hosts. By using a Home Agent as anintermediary, Correspondent Hosts do not need to knowthe Mobile IP protocol or the current location of theMobile Host. The forwarding of packets to the currentaddress of the Mobile Host is transparent for other hosts.

The routing tables typically maintain the next-hop(outbound interface) information for each destination IPaddress, according to the number of networks to whichthat IP address is connected. The network number isderived from the IP address by masking off some ofthe low-order bits. Thus, the IP address typically car-ries with it information that specifies the IP node’s pointof attachment. To maintain existing transport-layer con-nections as the mobile node moves from place to place,it must keep its IP address the same. In Mobile IP thehome agent redirects packets from the home network tothe care-of address by constructing a new IP header thatcontains the mobile node’s care-of address as the destina-tion IP address. This new header then shields or encapsu-lates the original packet, causing the mobile node’s homeaddress to have no effect on the encapsulated packet’srouting until it arrives at the care-of address. Such encap-sulation is also called tunneling, which suggests that thepacket burrows through the Internet, bypassing the usualeffects of IP routing. By using this architecture, a MobileHost can roam between Foreign Agents and its HomeAgent. When the Mobile Host leaves the service area ofits current Foreign Agent and registers with a new For-eign Agent, the Home Agent has to be informed aboutthe change of address. This procedure is called handoff.During such a handoff, it is possible that the Mobile Hostloses connectivity for a short period of time. To providesmooth handoffs and speed up the handoff process, theuse of several care-of addresses is possible where wire-less service areas overlap. However, only one of thoseaddresses can be registered with the Home Agent (pri-mary care-of address).

The Mobile IP architecture is well suited for MobileHosts that change their point of attachment only over rel-atively large time intervals. When fast moving MobileHosts are forced to perform a large number of handoffs

per time interval, registering a care-of address with theHome Agent causes too much over-head and a too highdelay, which in turn results in decreased protocol per-formance. Several approaches to solve this problem andto provide a more local, hierarchical form of mobilitymanagement are discussed in [29, 31].

1.1. Mobile IP Handoff

In Mobile IP all base stations advertise their pres-ence by sending beacon messages at a preconfigurabletime interval. Mobile Nodes store the addresses of thebase stations within range in a list. When no beaconmessage of a registered base station is received for acertain amount of time, the list entry times out and isremoved. Mobile Nodes that have to perform a handoffbecause they left the service range of their current For-eign Agent chose a base station from the list as their newForeign Agent. If the list does not contain any entries,the Mobile Node sends an Agent Solicitation Message.Base stations that receive this message have to send anadvertisement, which then allows the Mobile Node toregister with them. The handoff is initiated with a Reg-istration Request from the Mobile Node. The base sta-tion then forwards the request to the Home Agent ofthe Mobile Host. The Home Agent updates the care-of-address (COA) of the Mobile Host and installs a so-called encapsulator to tunnel IP packets to the mobilehost via the base station. The Home Agent then sends aRegistration Reply Message to the base station and thebase station in turn informs the Mobile Node that thehandoff was successful. From then on, the base stationacts as the Mobile Node’s Foreign Agent.

However, the handoff algorithm itself is kept verysimple. Whenever the Mobile Node receives a beaconmessage from a Base Station, it sends a RegistrationRequest and from then on uses the Base Station as a For-eign Agent. This results in a dropout until the new con-nection is established although the Mobile Node couldstill communicate with the rest of the network over itscurrent Foreign Agent. The method also works onlywhen the Mobile Node “hears” a single Base Station.As soon as service areas of Base Stations overlap, theMobile Node constantly switches between Base Stationsand because of that often cannot establish any transportconnection at all. Since a handoff to a new Base Stationgenerates a certain amount of overhead, the simple hand-off algorithm produces an unnecessarily large amount ofMobile IP control packets.

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1.2. Ad Hoc Network Routing Algorithms

An ad hoc network is a collection of mobile nodesforming a temporary network without the aid of any cen-tralized administration or standard support services regu-larly available on conventional networks. Some form ofrouting protocol is necessary in these ad hoc networkssince two hosts wishing to exchange packets may not beable to communicate directly. One problem with wirelessnetwork interfaces is they typically operate at signifi-cantly slower bit rates than their wire-based counterparts.Frequent flooding of packets throughout the network, amechanism many protocols require, can consume signif-icant portions of the available network bandwidth. Adhoc routing protocols must minimize bandwidth over-head at the same time as they enable proper routing totake place. Also, ad hoc networks must deal with fre-quent changes in topology. By their very nature, mobilenodes tend to wander around, changing their networklocation and link status on a regular basis. Furthermore,new nodes may unexpectedly join the network or exist-ing nodes may leave or be turned off. Ad hoc routingprotocols must minimize the time required to convergeafter these topology changes. A low convergence timeis more critical in ad hoc networks because temporaryrouting loops can result in packets being transmitted incircles, further consuming valuable bandwidth.

Ad hoc networks are networks which lack the sup-port structure and permanency of traditional networks,yet change sufficiently slowly as to permit the use ofa routing protocol to optimize transmission bandwidth.Some of the ad hoc routing algorithms in use at presentinclude Destination-Sequenced Distance-Vector Routing(DSDV) [26] that is an adaptation of a conventional rout-ing protocol to ad hoc networks. DSDV is based on theRouting Information Protocol (RIP) [14], used in parts ofthe Internet. Optimized Link State Routing (OLSR) [15]is a link state routing protocol. OLSR is an adaptation ofconventional routing protocols to work in an ad hoc net-work on top of IMEP [10]. OLSR uses a scheme knownas multi-point relays to minimize the flooding of broad-cast messages in the network by reducing/ optimizingduplicate re-transmissions in the same region. Each nodein the network selects a set of nodes in its neighbourhoodthat will re-transmit its broadcast packets. This set ofselected neighbour nodes is called the multi-point relaysof that node. Each node selects its multi-point relay setin a manner to cover all the nodes that are two hopsaway from it. The neighbours that are not in the multi-point relay set still receive and process broadcast packets

but do not re-transmit them. Temporally-Ordered Rout-ing Algorithm (TORA) [20] is a distributed routing pro-tocol based on a link reversal algorithm. It is designed todiscover routes on demand, provide multiple routes to adestination, establish routes quickly, and minimize com-munication overhead by localizing the reaction to topo-logical changes when possible. Ad Hoc On-Demand Dis-tance Vector (AODV) [27] routing is essentially a combi-nation of both DSR and DSDV. It borrows the basic on-demand mechanism of route discovery and route main-tenance from DSR, plus the use of hop-by-hop rout-ing, sequence numbers, and periodic update packets fromDSDV. The main benefit of ADV over DSR is the sourceroute does not need to be included with each packet.This results in a reduction of routing protocol overhead.Unfortunately, AODV requires periodic updates which,consume more bandwidth than is saved from not includ-ing source route information in the packets [7]. Signalstability based adaptive routing (SSA) [11] is a variantof the AODV protocol to take advantage of informationavailable at the link level. Both the signal quality of linksand link congestion are taken into consideration whenfinding routes.

2. MOBILITY PREDICTION IN WIRELESSNETWORKS

Other research which deals with mobility predictionin cellular networks include a tracking scheme proposedin [17] which uses a Gauss-Markov model to predict amobile’s future location for efficient paging. Based onthe Gauss-Markov model, a mobile’s future location ispredicted based on the information gathered from thelast report of location and velocity. An extension of theResource Reservation Protocol (RSVP) for cellular net-works is proposed in [2]. The proposed scheme usesmobility prediction to reserve bandwidth and it is basedon the same framework presented in [1]. In this scheme,each datum of mobility history information consists of atuple whose elements include the identity of the mobilestation, the last location visited, and a timestamp indicat-ing the time at which the current cell was entered. Basedon this historical data, a prediction can be made on themost likely location of the mobile station. This knowl-edge can then be used for intelligent pre-allocation ofresources.

Another scheme that uses prediction to locate amobile in a cellular network is presented in [1]. Statis-tical search theory is used in this approach by maintain-

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ing a history of prior known mobility patterns of users.Based on this prior information, a vector of probabil-ity mass functions concerning the likely location of atarget station is first computed. These probability massfunctions are then used as input to a search strategy thatspecifies the manner in which a mobile terminal is to bepaged. In [9], a similar method to predict a mobile user’smovements in cellular networks is used to reserve band-width, but the amount of bandwidth to be reserved isdynamically adjusted according to the time-varying traf-fic pattern and the observed handoff dropping events. Anadaptive algorithm for controlling the mobility estima-tion time window to prevent over-reserving bandwidthis also used.

We have extended the industry standard mobilearchitecture—Mobile IP and added an optimized hand-off protocol which uses a motion prediction algorithmto estimate which direction a mobile device is mov-ing in by using information such as signal strength orGPS. It then takes this information and examines adatabase of nearby cells (wired, cellular, ad-hoc net-works etc) and then streams multiple multicast mul-timedia streams (which the device is currently using)to the new network—thereby having a cache of timelydata waiting for the mobile host upon connection to thenetwork. This hand-off algorithm drastically improvesupon current hand-off algorithms. Chameleon—the mid-dleware we discuss elsewhere [21–25] utilizes filter (orproxy) propagation. This approach to filtering allows afilter to move around the network—thus ensuring thatthe filter performs its functions at the optimum point inthe network. Mobile IP++ makes use of the fact thatthese filters-proxies exist in the network already to per-form other tasks and uses these filters to perform conges-tion control for receivers at the end of poor links. Ourapproach adopts a similar protocol developed in I-TCP[3–4] for negotiating the mobile host and service proxieswhen the service proxies are moved. The details of thishand-off from one network to another follow.

2.1. Mobile IP++ Architecture

Packets from a Correspondent Host to the MobileHost are routed to the corresponding Home Agent. TheHome Agent looks up the address of the Mobile Host andtunnels the packet. All packets are sent over the HomeAgent therefore the Home Agent can be a performancebottleneck when the number of Mobile Hosts increases.In this case, a hierarchical structure of multiple HomeAgents can improve performance and scalability. Hier-

archical Home Agents can distribute the Mobile Hostsamong themselves to balance the load.

The architecture aims to support multiple wirelesstechnologies and thus has to be able to use multipleservice providers, which assume the role of the For-eign Agents. A Mobile Host is assigned an IP addressby its current Foreign Agent and can be reached usingthat address. Thus, the care-of address is the addressof the Mobile Host (co-located care-of address). Theinternal structure of the service providers with routersand base stations is not modelled in Figure 1, sinceneither the Mobile Host nor the Home Agent need toknow about it. The kind of mobility support used by theservice provider is transparent for the Mobile Host. Inother words, the framework only handles vertical hand-offs from one service provider to another without takinghorizontal handoffs within the service area of a singleprovider into account.

2.2. Mobile IP++ Handoff Algorithm

In a cellular network, a mobile user will travel fromone access point to another. The last hop connectionbetween a mobile terminal and its local base station isoften rerouted. This rerouting process is called a hand-off. When a mobile user travels to a new cell, it is impor-tant that the network can provide an uninterrupted hand-off for the active connection. In the case for an ad hocnetwork, the connectivity between neighbouring nodesis very dynamic. This is due to the fact that all nodesare non-stationary. It is crucial for the routing protocolto adapt quickly to such a fast changing environmentin order to reduce the amount of disruptions sufferedby the link disconnections. In such an environment, itis also desirable to reduce transmission overhead andpower consumption because the bandwidth for a wire-less channel is limited.

Typically, a mobile user’s travelling pattern is nottotally random. By exploiting a mobile user’s non-ran-dom travelling pattern, it is possible to predict the futurestate of a network topology and thus provide continuousaccess during period of topology changes. This part ofthe paper covers the topic of using mobility prediction tominimize service disruptions in cellular and ad hoc net-works to the actual media stream delivered to the mobilereceiver. Mobility prediction is used to lower handoffdelays that are common in cellular network handoffs.For ad hoc networks, routing protocols are enhanced bymobility prediction to perform path reconstruction priorto topology changes.


Fig. 1. Mobile IP++ overview.

Wireless technologies vary considerably in offeredbandwidth and changes of a few orders of magnitude arepossible. Thus, it is necessary that applications adapt tochanged network conditions as fast as possible. Whena handoff to a low bandwidth provider is necessary butit takes a Streaming Video application several secondsuntil it adjust its bandwidth from high quality audio with64 KBit/ s to low quality voice with only 6 KBit/ s, it ispossible that due to congestion no traffic at all can besent from or to the Mobile Host for that period of time.When also Mobile IP control packets are lost (e.g. bind-ing updates), performance can suffer for much longerthan the time of congestion. In dealing with such sit-uations, applications profit from additional informationthat can be provided by the mobile node. The mobilenode has information about the maximum bandwidth aswell as concurrent applications, which allow an appli-cation to determine its optimal throughput. To providethis, a bandwidth manager is installed in each MobileHost. The bandwidth manager has to ensure that MobileIP control packets are transmitted with a higher prioritythan all other traffic and it can discard packets of applica-tions that excessively use scarce bandwidth even beforethey are passed down the protocol stack.

Base stations have to announce their presence bysending periodic beacon messages. Upon reception ofa beacon message, a mobile node can request ForeignAgent services from that base station. When the mobile

node leaves the service area of the base station it has toperform a handoff to a new base station. A very basichandoff algorithm is to negotiate Foreign Agent serviceswith a new base station as soon as the old base stationbecomes unavailable. The mobile node detects this whenit does not receive beacon signals for a certain amount oftime. To prevent that base stations are erroneously con-sidered unreachable because beacon messages are lost,the timeout interval for base stations should be a mul-tiple of the beacon period. However, when the mobilenode loses its current base station and a handoff is neces-sary, the mobile node cannot communicate until the basestation timer expires and the mobile node negotiates For-eign Agent services with a new base station. This resultsin a communication dropout of up to a few seconds. Thenetwork architecture presented in this report focuses onmobile nodes, whether moving at walking pace or trav-elling in a vehicle. Location information, which can beobtained via a GPS system or direction of travel betweenwireless networks, can be used to optimize the handoffalgorithm for Mobile IP. By keeping track of its currentlocation, the mobile node can predict when a handoffis likely to happen and negotiate Foreign Agent serviceswith a new base station beforehand. This effectively pre-vents a communication dropout. When the mobile nodeis within a certain range of the border of the coveragearea, it tries to perform a handoff to a base station thatis located closer to the mobile node. The mobile node

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can use the signal strength of the beacon messages toestimate how close the mobile node is to the border ofthe service area. When it falls below a certain thresholdvalue the mobile node performs a handoff to the nearestbase station it can hear. During the handoff, the mobilenode is still reachable via the old base station.

As soon as a Mobile Host leaves the near rangeof the current Foreign Agent, it performs a handoff ifthere is another near base station. The Mobile Nodedoes not perform a handoff when it receives a bea-con message from a closer base station, which has thesame range classification. During the transition from oneForeign Agent to another, the Mobile Node retains itsreachability via the old care-of-address (provided the oldBase Station is still within hearing range). Some videoframes may be lost during the movement of the serviceproxy since forwarding video frames from the old ser-vice proxy to the new service proxy may violate tim-ing constraints of the video frames. However, in ourapproach, a protocol that is similar to the protocol pre-sented in [28] is used to minimize the loss of videoframes. During the movement of the service proxy, a newstationary computer for executing the service proxy joinsinto the multicast group for receiving the video streamthat the mobile host want to receive. This means thatboth service proxies receive the same video stream dur-ing the handoff of the service proxy. These service prox-ies negotiate not to send the same video frames to themobile computer. If the handoff is completed, the old sta-tionary computer that executes the service proxy leavesfrom the multicast group.

2.3. Mobile IP++ Predictive Movement Algorithm

In reality, mobile terminals move according to thepresence of highways, streets, and roads. The mobile ter-minals do not move randomly and follow patterns thatare somewhat predictable. For example, a mobile usertravelling on a highway follows the direction of the high-way and he or she is not likely to change direction ran-domly. Therefore, it is possible to predict the movementof a mobile user in a particular area with the knowledgeof previous local mobility patterns. We will study thescheme that will predict the next cell a mobile will travelto based on the mobility information acquired in the cur-rent cell. Let i denote the cell that a mobile m is currentlyin, where i ∈ I and I is the set of all cells in the network.Assume each mobile keeps track of the last M cells thatit has travelled through. We define this sequence of cells

to be the mobility state of mobile m. Let the mobilitystate of a mobile be equal to j. We define S to be the setof all possible values of j such that j ∈ S,

j c { j1, j2, . . . , jm}, jk ∈ I, k c 1, 2, . . . , M

A general description of the algorithm would be as fol-lows: Whenever a mobile arrives in a cell, the current basestation predicts its next location based on the probabilityarray P associated with the particular state of the trackingbuffer and reserves the required bandwidth in the selectedcell. When the mobile leaves the current cell, the currentbase station updates the probability array Pj for state jbased on the next cell that it actually travels to.

The base station for each cell establishes connec-tions to each of its neighbours. These connections onlysend control traffic, which is used to inform the base sta-tion associated with the mobile’s previous cell. The pre-vious base station then updates its probability array Paccordingly. Using the connections between base stationsinstead of allowing the mobile host to send the reser-vation information message will alleviate the wirelessbandwidth. An example of how the algorithm works isillustrated above. As we can see in Figure 2, the mobilearrives in cell 2 through cell. Based on the probabilisticinformation base station 2 accumulated about all previ-ous mobiles that arrived through cell 1, it replicates thecurrent stream that the mobile host is receiving and for-wards this stream to base station for cell 4 (Figure 3).In Figure 4, we can see that the mobile actually arrivesin cell 4 where the stream has been cached awaitingretrieval with minimal handoff lost packets. Base Station4 now has responsibility for streaming data to the mobilehost and indeed implementing the next stage of the pre-diction algorithm. Throughout this procedure, each basestation will accumulate the statistics and updates its pre-dictive movement probability information.

Fig. 2. Mobile within a cell.


Fig. 3. Mobile moving toward next cell.

3. SIMULATION EVALUATION

The basis for our work in the LBL NetworkSimulator, “ns,” developed by the Network ResearchGroup at the Lawrence Berkeley National Laboratory[19, 12]. Ns provides a framework for inspecting thedynamic behaviour of network traffic, congestion, andother network characteristics. We are primarily interestedin the issue of rate control, however, as we are workingon a best effort network, we assume that the underlyingnetwork introduces data loss and error into our transmis-sions. We also assume that data can be delivered out oforder to a receiver.

3.1. Predictive Movement Algorithm

A real-time flow is a connection that delivers datapackets with a rigid timing requirement such as thetransmission of a video stream. Since the topology ofan ad hoc network is very dynamic, real-time connec-tions are subject to frequent disruptions. During topol-ogy changes, routes can be broken abruptly resulting inreal-time packets being dropped. Hence we propose anextension of the On-Demand Multicast Routing Proto-col (ODMRP) [13], which uses the mobility informa-

Fig. 4. Mobile host receiving video in “new” cell.

tion obtained from the mobile hosts to predict topologi-cal changes. The scheme performs rerouting for a real-time flow before a path becomes invalid. This is doneusing a mechanism we refer to as “multi-hop handoff.”Our goal is to minimize disruptions of real-time sessionsdue to mobility.

The simulation model consists of a cluster ofbetween 4 to 30 cells in each of the simulations. Thebase station for each cell resides in the centre of a cell.The cells are wrapped around so the topology of the sim-ulated wireless networks represents a sphere. This meansthat the handoff rates in all the cells are approximatelysimilar. We assume the arrival rates of call attempts inall cells to be Poisson with an average value equals to l.The call duration for each mobile is exponentially dis-tributed with rates equal to m. The direction that eachmobile travels is random (between 0 and 360 degrees)with each mobile travelling with velocity n . Simulationruns were conducted for the default algorithm (when nobandwidth is reserved) and for the various schemes withpredictive reservation. The diameter of a cell is approx-imately 100 meters and n is equal to 5 meters/ sec forall mobiles (micro/ pico cell environment). m is exponen-tially distributed with an average value of 300 seconds.Each base station has a capacity of 10 Mbps and eachCBR connection requires 1 Mbps. Therefore, each basestation can support up to 10 mobiles at the same time.

To assess the improvements of using mobility pre-diction, we created a series of simulations where thespeed of the mobile device was varied with speeds from0 km/ hr to 72 km/ hr. A multicast group of size 10 withone sender is used and each sender sends data at the rateof 10 packets per second. Mobile IP++’s refresh intervalis set to 1.5 seconds, while the minimum refresh intervaland maximum refresh interval for Mobile IP++ are set to1.5 seconds and 60 seconds respectively. The metrics ofinterest include packet delivery ratio, number of controlbytes transmitted per data byte delivered, and number oftotal packets transmitted per data packet delivered.

The packet delivery ratio as a function of the mobil-ity speed is shown in Figure 5. As speed increases, therouting effectiveness of Mobile IP degrades rapidly com-pared to Mobile IP++. Mobile IP++ has very high deliv-ery ratios of over 90% regardless of speed. As the routesare reconstructed in advance of topology changes, mostdata are delivered to multicast receivers without beingdropped. In Mobile IP (using ODMRP), however, JoinRequests and Join Tables are transmitted periodicallywithout adapting to mobility speed and direction. At high

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Fig. 5. Packet delivery ratio.

speed, routes that are taken at the Join Request phasemay already be broken when Join Tables are propagated.

The number of total packets (i.e., Join Requests,Join Tables, Join Data, Data, and active acknowledg-ments) transmitted per data packet delivered is presentedin Figure 6. This measure indicates the channel accessefficiency. As we can see from Figure 6, the numberfor Mobile IP remains relatively constant after an initialincrease. Since the number of data packets delivered andthe amount of control bytes transmitted both decreaseas mobility increases, the number for Mobile IP remainsalmost unchanging. The measures for Mobile IP++ grad-ually increase with mobility speed. Since Mobile IP++delivers a high portion of the data to destinations regard-less of speed, more control packets must be sent in orderto adapt to the increasing speed. Thus the total numberof packets transmitted increases with speed. Also, sinceMobile IP++ uses longer, more stable routes comparedto Mobile IP’s ODMRP, Mobile IP++ sends data overa longer hop length than ODMRP, and therefore, moredata packets are transmitted.

We have neglected the issues of system cost in thispaper. Obviously there is an overhead involved in the pre-diction movement algorithm being implemented withineach base station and end host. We have performed aseries of simulations using a mobility prediction algo-rithm. The predictive movement is accomplished by accu-mulating statistics about mobility patterns in a particular

Fig. 6. Avg no of total packets sent per data packet delivered.

area. Results from simulation indicate that by using pre-dictive movement algorithms we can obtain an improve-ment in quality of service for the connections withoutwasting significant amount of bandwidth.

3.2. Mobile IP++ Streaming Media Throughput

In this set of simulations, we focus on the actualthroughput of streaming media streams over varioustopologies and bandwidths. We experiment with a vari-ety of packet sizes and bottlenecks etc and we comparestandard UDP streams with the actual Mobile IP++ pro-tocol. The total simulation time varies from 140–300seconds. The topology consists of between 20 and 40base stations within a large coverage area, between 10and 20 base stations within a medium coverage area, andbetween 1 and 10 base stations within a small cover-age area. The base stations and the movement pattern ofthe Mobile Host are arranged so that the Mobile Hoststarts out with a base station with a small coverage areaand a high bandwidth (1 MBit/ s). After 100 seconds, theMobile Host starts to move and as a consequence has toswitch to a medium size base station with a bandwidth of512 KBit/ s. When it leaves the service range of that sec-ond base station it is forced to switch to the base stationwith the largest coverage area and the lowest bandwidth(128 KBit/ s). It performs a sequence of handoffs (i.e.


Fig. 7. Streaming media 100K (standard).

first to the large base station, then to the medium basestation, and then to the small base station).

The traffic used in the simulations was medium—low bandwidth streaming media (UDP flows) with rawdata rates of 100 KBit/ s (i.e. maximum throughput ona perfect network with no loss or congestion would be100 kBit/ s).

Throughput results for a standard 100K UDP flowscenario is shown in Figure 7. Figure 8 however depictsthe same flow using mobile IP++. The graph clearlydemonstrates that Mobile IP++ causes the mobile deviceto receive a “near complete” stream with no dips inperformance throughout the 140 seconds whereas thestandard “non predictive” algorithm drops the connec-tion totally from times 0–8 seconds, 31–39 seocnds, andagain from 48–51 seconds.

4. RELATED WORK

The GTS protocol [18] attempts to address the prob-lems that face computers that are only intermittentlyattached to a network (mobile). GTS builds a hierar-chy as receivers join the multicast group. Servers located

Fig. 8. Streaming 100K mobile IP++.

at each site are connected to other servers higher inthe hierarchy, and eventually to the source. Each serverknows of its children, whether they are receivers or otherservers. Delivery from a server to its child is unicast,using any existing reliable protocol the two hosts agreeto. GTS facilitates this flexibility by specifying commu-nication end-points as URLs, including a “ticket” indi-cating the multicast channel. When disconnected hostsare unavailable, the server must spool the message untilit can be delivered. Thus, GTS is not prompt in its deliv-ery, but robust. It is more useful for replicated databasesor software distribution than multimedia. Further, sincesenders must contact the single sequencer server directly,only a limited number of senders can be supported.

Campbell [8] describes a protocol called QoS-Athat distributes multicast data through carefully selectednodes in a hierarchy, which are equipped to filter multi-media streams to reduce their demands on the receiver’shardware. For example, an audio stream broadcast froma radio station containing stereo CD-quality sound couldbe reduced to a stream containing only mono CD-qual-ity sound or even telephony-quality sound to meet therestrictions of bandwidth and audio hardware availableto the receiver. Similarly, an MPEG-2 stream could be

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reduced to an MPEG-1 stream, or MPEG-1 could bereduced to contain only l-frames, or to contain onlyaudio for mobile computers with very low bandwidthand essentially no continuous video capabilities. Thereis much overlap between QOS-A and Mobile IP++ how-ever an obvious difference is that in Mobile IP++, end-users can explicitly state their capabilities.

In [32], a stream is decomposed into two connec-tions, and an intermediate computer connects the twoconnections. When the bandwidth of a wireless networkbecomes low, an intermediate stationary computer filtersdata from a high-speed network before sending the datato a mobile computer. The intermediate computer filtersthe data according to the content such as reducing thesize of each video frame may degrade video data. Thesolution answers the problem caused by drastic changesof network bandwidth, however it fails to solve the prob-lem when network bandwidth is changed dynamicallyduring the execution of applications.

5. CONCLUSION

We have outlined an extension to Mobile IP, whichserves as a vehicle communication architecture. Direc-tional movement information of the mobile host is usedto predict which cell the host will move to. To over-come the inherent delays in cellular handover—we havethe replicated stream cached in the new cell awaitingretriveal by the mobile host with minimal delay. Addi-tional location information available via GPS can beused to optimize the handoff process. Mobile IP++ con-trol packets are given priority in order to ensure thesmoothness of the protocol.

The objective of the experiments was to inves-tigate the performance of wireless access methods ina simulated media-streaming environment where someof the moving participants are receiving a media feedfrom a server. In a wireless environment, it is veryimportant to maximize the use of the limited, avail-able bandwidth while, at the same time, minimizingthe propagation delay and delay variation of time sen-sitive information over the wireless link. Our experi-ments validate our expectation that given the typicalprocessing power of platforms today and the relativelylow bandwidth of the internet, the overhead of applica-tion adaptation is rewarded by the reduction in trans-mission time over the a wide area network alongsidethe implementation of movement prediction algorithmswithin filters/ transcoders within the network.

6. REFERENCES

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Kevin Curran is a Lecturer at the University of Ulster, MageeCollege. He is currently completing a Ph.D. in Computer Sciencewith the University of Ulster. His research interests include dis-tributed computing especially emerging trends within wireless ad-hoc networks, distributed objects, dynamic protocol stacks, multime-dia transport protocols and mobile systems. He can be contacted [email protected].

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Minimizing the Handoff Latency in Ad-Hoc Networks When Streaming Media to Mobile Devices