QoS Provisioning in Wireless Multimedia Networks Sajal K. Das, Mainak Chatterjee and Naveen K. Kakani Center for Research in Wireless Computing (CReW) Department of Computer Science University of North Texas Denton, TX 76203-1366 E-mail: fdas,mainak,
[email protected]
Abstract |
The advent of powerful hand-held computers and the desire for communication on the move, are the driving forces behind an emerging technology called mobile computing. Observing the growing demands of roaming users, it has been predicted that the next generation wireless networks will be burdened with the bandwidth-intensive trac generated by personal multimedia applications. However, the available bandwidth for supporting these applications is still limited, and therefore its proper management is necessary to ensure the required quality of service (QoS) provisioning between the end-systems. In this paper we will rst present a survey of the existing literature on the QoS provisioning for wireless networks, which mainly focus on identifying the technological bottlenecks involved. Then we will propose a uni ed framework to provide a link layer as well as network layer solution for QoS provisioning. Our framework measures two important QoS parameters, namely the inter-packet delay and the data rate of transmission. Experimental results show as high as 21% improvement in the call admission probability and about 16% improvement in the hand-o call dropping probability. I. Introduction
The next generation wireless networks and hand-held terminals are expected to support a wide variety of multimedia services such as e-mail, fax, traveler's information systems, web browsing, video and news on demand, mobile oce system, stock market information, and so on. The characteristics of wireless links as well as the desire to maintain connectivity while on the move (i.e., mobility), o er signi cant challenges to provisioning quality of service (QoS) which is usually expressed in terms of such parameters as the end-toend delay, bandwidth, or jitter. The parameters vary signi cantly over a wide range for di erent classes of trac. Ecient and e ective QoS provisioning techniques are very important. Mobile computers will soon be expected to be connected to the Internet using radio or infrared communication technologies. Thus mobile nodes should be able to change their point of attachment from one (sub)network to another, without losing its IP address. Ensuring end-to-end quality of service is a distributed function to be realized at various layers of the protocol stack of the network. Each layer provides certain services and has a mechanism for connection establishment. In this paper, we propose an integrated framework for QoS provisioning at the link layer as well as network layer in wireless networks. This work is supported by the Texas Advanced Research Program grant TARP-003594-013 and a grant from Nortel Networks, Richardson, Texas.
II. Previous Work
Earlier work reported in [5], [3], [4], [8], [6], [7] focussed on guaranteeing QoS in cellular wireless networks. Analytical models such as [6] consider mixed classes of trac (e.g. pedestrians, automobiles) with di erent types of channel and other resource requirements. Most of the proposed models, hand-o calls are given priority over ordinary calls. Performance measures like carried trac, blocking and forced termination probabilities for each trac class and call type are numerically computed from the analytical models. Using the virtual connection tree concept, several QoS provisioning algorithms have been proposed in [3]. These algorithms use adaptive resource sharing policy among real-time and non-real-time classes of trac such that the former class has preemptive priority over the latter. The work presented in [8] identi ed two QoS parameters namely, graceful degradation of service and guarantee of seamless service. The rst parameter refers to reducing allocated bandwidth to the existing calls whereas the second refers to providing connectivity on the move. Based on the minimum requirement criteria provided by the user. A bandwidth reservation algorithm for guaranteeing QoS in cellular networks has been proposed in [5]. We have provided solutions in [9], [10], [11] to adjust the QoS o ered to each application based upon the network condition. In the following, we integrate several of these schemes into a uni ed framework, thus leading to QoS provisioning across protocol layer boundaries. III. The Proposed Framework
The carried trac in a wireless network can be increased by the graceful degradation of some or all of the existing services in the system. The quality of each connection deteriorates as data is discarded by the base station transmitter to adjust to the reduced bandwidth. It is possible that discarding of data results in the loss of some critical portions which may not be recoverable. The amount of bandwidth reserved in a cell is either a function of the number of real-time calls or the total bandwidth requested by all real-time connections therein. Although this simple mechanism guarantees QoS, it su ers from such drawbacks as redundant bandwidth reservation. The kind of solution we are looking for is an alternative to the xed service guarantee approach, by designing the multimedia applications in such a way that they can accept varying degrees of provisioning from the other layers.
IV. QoS Provisioning at Link Layer
Our framework provides a di erential treatment for the real-time (delay-sensitive) and non-real-time (delay-tolerant) multimedia applications. The mode of QoS provisioning involves: (i) development of ecient bandwidth reservation schemes; (ii) sorting the real-time and non-real-time packets; (iii) provision for packet marking; (iv) designing various priority scheduling techniques. Figure 1 depicts a framework for low layer QoS provisioning in wireless multimedia systems. Let us assume that during the call setup period, the application speci es the following parameters to the system : (i) average bandwidth required, (ii) minimum bandwidth required, and (iii) whether it is delay-tolerant (non-real-time) or delay-sensitive (real-time). The user can use an RSVP-like signaling protocol to convey to the system of its requirement pro le (RP) consisting of the above three parameters. The admission controller allocates one or more channels matching the speci ed bandwidth requirements, if certain tracrelated conditions are satis ed.
compaction to maximize utilization of available channel resources; and (v) radio resource usage monitoring. These concepts are explained in detail in [13]. A. Call Admission Algorithm The call admission algorithm is presented as a owchart in Figure 2. As discussed earlier, the originator of the request speci es a requirement pro le, The call admission criteria will be di erent for each class. For real-time users, admission is primarily based on the availability of bandwidth and compaction may have to be resorted to. The real-time user is classi ed as local or departing based on the location prediction scheme. If the user is departing, bandwidth reservation is initiated in the predicted destination cells [12]. If these reservations are successful, then only the call is admitted. The call of a local user is admitted based on the bandwidth availability in the current cell only. For non-real-time users, the admission is primarily based on the availability of bu er space in the non-real-time packet queue. user requirement profile
Real time packet queue s
Traffic Packets
Packet Sorter Admission decision
Requirement Profile
Admission Controller
QoS Sublayer
... Radio link Frame
Non-Real time packet queues
N Y
requested BW < available BW?
Y
Buffer available < threshold
Scheduling Degradation Reservation Compaction
N Do partial BW compaction
Call Control Block
Link Layer
request = real-time?
Y
N
Queue information
Control information
Higher Layers
. .
Radio Resource Adaptation Sub-Layer
Admit request Y N
Fig. 1. A framework for ow control providing QoS
If bandwidth is available, a xed amount which we call a bandwidth page, is allocated to each non-real-time trac on a time-sharing basis, otherwise they are bu ered. Real-time trac, on the other hand, cannot be delayed beyond a certain duration and is assumed blocked or dropped if the minimum speci ed bandwidth of a call which we call a bandwidth segment, is not available. When a real-time call request arrives and nds all channels occupied, it may, under certain circumstances, force one (or more) ongoing non-real-time calls to be temporarily bu ered so that the released channel can be used to admit the real-time request. Once the admission controller admits the call (in the cell), it passes the requirement pro le of the user to the packet sorter. The packet sorter looks into the packet and puts it into the real-time packet queue (RTQ) or the non-real-time packet queue (NRTQ) according to their priority. The packets are then classi ed by setting certain bit patterns in their headers to distinguish them further, such that the scheduler (and also the radio resource manager in the system) can treat them di erentially while allocating radio resources. The call control block (Figure 1) is mainly responsible for various policy-driven schemes like (i) scheduling di erent classes of packet; (ii) call degradation or reducing bandwidth allocation to degradable applications in face of scarcity of available radio channels; (iii) bandwidth reservation for delay-sensitive, high priority applications; (iv) bandwidth
requested BW < new available BW? Reject request Classify user Departing?
Y Send message to destination cells to reserve BW N
N
Admit request
Ack. received? Y
Fig. 2. Flowchart of the call admission algorithm
There is a QoS monitor function as part of the call admission controller. Its function is to monitor the QoS parameters a ecting system-wide performance, e.g., interference level in the cell, number of hand-o drops etc., and also to provide feedback to the call admission controller to help it make certain policy-based call admission decisions. These policies will be determined largely by the network operators. In case of a fully loaded system (a sector/cell with all channels occupied), there is a provision for admitting nonreal-time calls by \stealing" channel capacity from the realtime users. During the period of inactivity of the application source, the real-time user is not using the channels assigned to it, therefore, the channel can be used to transmit packets for non-real-time users. The real-time user will have true ownership of a channel, while the non-real-time users sharing the same channel will have a restricted ownership. This implies that a real-time user sharing a channel with another
non-real-time user, will have preemptive priority over the latMRUP operates in the following steps: ter and will continue packet transmission when the source is When a mobile node requests a guaranteed data ow conactive again. nection with an MA, the MA checks if enough free resources are available in its subnetwork. If so, the requested resources V. Network layer solution set to in-use and the request is accepted. Otherwise, the We propose a simple and scalable resource reservation are mobile node's request is denied. scheme that allocates resources to a currently ongoing data If a request the MA sends a Reserve Re ow of the mobile node in all the neighboring subnets. This source messageistoaccepted, all its neighboring MA's (as discovered is implemented through two protocols, called the Neighbor by NMADP). The Reserve Resource contains the amount of Mobility Agent Discovery Protocol (NMADP) and the Mo- resources requested by the mobile. bile Reservation Update Protocol (MRUP). These protocols When a mobile node requests a guaranteed data ow concan be easily incorporated into the existing Internet rout- nection with a mobile agent (MA), the MA checks if enough ing protocols such as the Open Shortest Path First (OSPF) free resources are available in its subnetwork. If so, the reprotocol and the Mobile IP [2], [1], and are adaptable with quested resources set to in-use and the request is acboth intserv and di serv architectures since their scopes are cepted. Otherwise,are the mobile node's request is denied. If restricted to a leaf subnet only. a request is accepted, the MA sends a Reserve Resource An important assumption for the e ective functioning of message (containing the amount of resources requested by our proposed protocols (NMADP and MRUP) is that dur- the mobile) to all its neighboring MAs as discovered by the ing the lifetime of a connection, the mobile node will move NMADP. from a subnet to a geographically adjacent subnet. This is Once an MA has initiated a reservation for a mobile node, it a very reasonable assumption since a user cannot hop from sends Reservation Refresh messages to its neighone subnet to a non-neighboring subnet with an open con- periodically boring MA's, it realizes that the mobile node is no nection. Accordingly, we consider the Internet architecture longer present until in its subnetwork through the link or lower as shown in Figure 3, in which Ri for 1 i 5 is a router. layers. A geographic area has to be covered by several wireless local area networks (WLANs) or a similar wireless networking An MA, upon reception of a Reserve Resource message, technology, for a mobile node to truly communicate on the changes the state of a certain amount of resources from free move. This architecture is similar to the public land mo- to reserved. The amount of resources for which the state bile telephony system (PLMTS), where a geographical area change is made, is equal to or less than the the amount of is partitioned into cells which are analogous to the subnets resources requested by the mobile node. When an MA receives a registration request from a mobile in our architecture. node, it checks if there is a resource reservation for the mobile node. If so, the MA changes the state of the resources from reserved to in-use. The MA also initiates a reservation as in Token-Ring Ethernet step 2. A detailed description of the protocols is presented in [11]. R5 R1 R2 VI. Simulation experiments and Results
p.q.r.s
Wireless LAN-1
e.f.g.h
R3
X.25
R4 a.b.c.d
Wireless LAN-2 Wireless LAN-3
: Mobile Hosts / Agents (MA) Ri : Router a.b.c.d, e.f.g.h, p.q.r.s : IP addresses
Fig. 3. A Subnet Architecture
NMADP operates in the following steps:
Each MA (a router that is a home or a foreign agent) peri-
odically sends a Neighbor Mobility Agent (NMA) message to its neighboring routers with the IP address of the interface on which it is an MA. If the receiver router of a Neighbor Mobility Agent (NMA) message is also an MA, the receiver-MA records the senderMA as being mobility handling router in its routing table, and returns an acknowledgment back to the sender-MA indicating its own mobility handling capability. Otherwise, the sender-MA's Neighbor Mobility Agent message is discarded.
In this section, we provide details of our simulation model and the experimental results that are obtained from the simulation. Our simulation experiments are divided into two sections. The rst section explains the simulation of the link layer frame work and the results obtained and the second section presents the simulation of the network layer and the results obtained. A. Simulation Model of the Link layer Our simulation consists of applications that generate requests and data packets, the admission controller (AC) that admits these requests, the packet sorter (PS) that sorts the data packets, the queue manager (QM) that keeps track of the length of the real-time and non real-time queues, the compaction manager (CM) that performs compaction on a frame, and the scheduler that schedules packets onto a frame. Hand-o control and reservation messaging for hand-o calls are taken care of by the call control manager (CCM).
Our scheduling mechanism is adapted from the FRAMES radio interface proposal [14].
Our scheduling algorithm considers the time slots of a frame indexed by increasing time. A unit frame is represented as St0 ; St1 ; : : : ; Stn . Two indices are maintained while populating a frame. These indices indicate the last time slot index (Stmin ) occupied before the \hole", and the rst slot index (Stmax ) occupied at the end of the \hole", respectively [13]. Application
AC
QM
CCM
CM
PS
PAR
Seq. No.
New call RP (avg bw, min bw, class) 1
1:1 1 0:9 0:8 0:7 0:6 0:5 0:4 0:3 0:2
QLenQuery()
b
+
b
+
b
+
+
3 BWAvlResponse (current bw)
0
0:02
0:04 0:06 0:08 Arrival rate of users
1 05 :
4
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CompactionResponse (bw savings)
(accept, reject)
TABLE I
0 85
Packet source DIB RTQ 1 RTQ 0 RTQ 0 NRTQ NRTQ -
A.1 Simulation parameters Admitted requests act as bursty sources of data, with inter-arrival time of the bursts being exponentially distributed with mean 1 . Call arrival is a Poisson process with inter-arrival time exponentially distributed with mean 1 . The call holding time is also programmed1 as a exponentially distributed random variable with mean . The number of hand-o requests is an exponentially distributed random variable with mean 1h . No di erentiation is made between real-time and non real-time users for hand-o calls. In order to classify the users correctly, we need to model the signal strength received by the base station from the user. Since actual signal strengths cannot be generated, we overlay on each cell a grid of size 100 100. A user position within a cell is given by a pair of co-ordinates (x; y) in this grid.
with compaction b without compaction + +b +b
:
:
08 :
Packet # Packet size (bytes) 1 100 2 170 3 3 4 20 5 40
0:1
+
ANR
09
Example of a traffic mix
b
:
P
Fig. 4. Admission Control Messaging
Table I shows a random mix of trac packets.
b
0 95
5 6
b
+b
CompactionInvoke()
NewCall(uid, class)
+
Fig. 5. Call admission probability (PAR ) for real-time users versus call arrival rate for queue size = 100 and service rate = 0:03
BWAvlQuery()
Admission Decision
b
+
2 QLenResponse (RTQ length, NRTQ length)
with compaction b without compaction +
b
+ 20
30
40
50
60 70 80 Queue Length
90
100
110
Fig. 6. Call admission probability for non-real-time users versus queue size for arrival rate = 0:08 and service rate = 0:03
Figure 6 demonstrates the call admission probability with varying queue sizes with and without compaction. The admission probability for non-real-time users is observed to be higher with compaction at small queue lengths over that without compaction. Note that, at some threshold queue size, the bene t of compaction is lost. This implies that, given an average call arrival and service rates, there exists a queue size beyond which the compaction algorithm should not be executed, as compaction is generally very computation intensive. Figure 7 shows that the hand-o dropping probability also decreases with compaction. The observed improvement is around 17% for a hand-o rate of h = 0:001 and 11% for a rate of 0.009. 0:5
with degradation+ b without degradation b +
0:45 0:4
A.2 Simulation Results and Conclusions 0:35 + 0:3 The simulation results are shown in Figures 5 - 7. From Figure 5, we observe that the system capacity is fully utilizedPCD 0:25 0:2 only when compaction technique is used. With arrival rate + 0:15 less than the service rate, the call admission probability is 0:1 approximately unity when the compaction is used. Without 0:05 compaction, some incoming requests are blocked due to in0 sucient bandwidth in the left-over "holes". The observed 0 0:2 0:4 0:6 0:8 1 improvement varies from 21% for an arrival rate of 0.03 to Hando rate h 100 about 4% for an arrival rate of 0.07. Fig. 7. Hand-o call drop probability (PCD ) versus hand-o rate for b
b
queue size = 100, service rate = 0:01 and call arrival rate = 0:1
B. Simulation model of the Network layer To simulate the behavior of the proposed reservation mechanism and measure the performance, we model the arbitrarily shaped subnets as hexagonal cells. We assume each subnet is serviced by a single MA, and this corresponds to a base station serving a cell. In a single cell, we assume that a new call request event and a hand-o (into the cell) event are mutually exclusive.
B.2 Simulation Results and Conclusions Our primary parameter of interest is the call dropping probability, with and without reservation. Since we simulated a single cell, the hand-o calls are treated as a subset of new call requests. Unsuccessful hand-o of non-real-time calls from the current cell to an adjacent cell does not contribute to the total number of dropped calls. 1
0.9
Call dropping probability
0.8
0.7
0.6
0.5
λ (reserved) = 0.01 hand−off λhand−off (reserved) = 0.05 λhand−off (reserved) = 0.1 λhand−off (unreserved) = 0.01 λhand−off (unreserved) = 0.05 λ (unreserved) = 0.1
0.4
0.3
0.2
hand−off
0.1
0
1
2
3
4
Request rate of calls ( λreq × 10)
5
Fig. 8. Call Dropping Probability
6
req is scaled by a factor of 10 in Figures 8-9. As expected, the call dropping probability increases with an increase in the call arrival rate in both the reservation and non-reservation cases. When using the reservation mechanism, we observe that the call dropping rate decreases as hand?off increases this is in contrary to the performance obtained when we do not use the reservation scheme. In fact the reservation scheme improves the performance (call admission probability) by 25% for a hand-o rate of 0.1 but deteriorates the performance by 25% for a hand-o rate of
Hand−off call dropping probability
B.1 Simulation Parameters In simulation experiments we xed the bandwidth available in each cell to 50 channels, and no call is allowed to request more than 8 channels. Simulation was carried out for one cell. For the simulated cell and its six neighbors, there can be at most one call request and one call hand-o in each simulation cycle. A Poisson process governs the arrival of a new call (req ) and hand o call requests (hand?off ). The service rate is assumed to be a Poisson process with mean 0.5. The simulation model assumes that the type of a new call can be real-time or non-real time with equal probability. For an hexagonal shaped cell, the ratio of the probability of call arrival, service rate, and hand-o rate in the current cell to the corresponding probabilities in the neighboring cells is 1:6.
0.45
0.4
0.35
0.3
0.25
0.2
λhand−off = 0.01 λhand−off = 0.05 λhand−off = 0.1
0.15
0.1
0
1
2
3
4
Request rate of calls ( λreq × 10)
5
6
Fig. 9. Hand-o Dropping Probability
0.01, relative to the performance of no-reservation scheme. While using the reservation scheme although there is a reduction in the number of new call requests accepted, we obtain an improvement between 12% to 38% in the the number of hand-o calls dropped. References D. B. Johnson, C. Perkins. Mobility Support in IPv6. Internet-Draft, draft-ietf-mobileip-ipv6-03.txt, July 1997, Work in progress. C. Perkins, Editor. IP Mobility Support. Internet Request for Comments 2002, October 1996. A. S. Acampora, M. Naghshineh. Control and Quality-of-Service Provisioning in High-Speed Microcellular Networks. IEEE Personal Communications Magazine, Vol. 1, No. 2, Second quarter 1994, pp. 36-43. [4] M. Naghshineh, M. Schwartz, A. S. Acampora. Issues in Wireless Access Broadband Networks. Wireless Information Networks, Edited by J. M. Holtzman, Kluwer Academic Publishers, 1996. [5] C. Oliveira, J. B. Kim, T. Suda. Quality-of-Service Guarantee in High-Speed Multimedia Wireless Networks. Proceedings IEEE International Communications Conference 1996, Dallas, Texas, pp. 728-734. [6] S. Rappaport, C. Purzynski. Prioritized resource assignment for mobile cellular communication systems with mixed services and platform types. IEEE Transactions on Vehicular Technology, Vol. 45, No. 3, August 1996, pp. 443-457. [7] M. Schwartz. Network Management and Control Issues in Multimedia Wireless Networks. IEEE Personal Communications Magazine, June 1995. [8] S. Singh. Quality of Service Measures in Mobile Computing. Journal of Computer Communications , Vol. 19, 1996, pp. 359-371. [9] R. Jayaram, Naveen K. Kakani, Sajal K. Das and S. K. Sen, Call Admission and Control for Quality-of-Service (QoS) Provisioning in Next Generation Wireless Networks, Proceedings of the Fifth International Workshop on Mobile Multimedia Communication (MoMuc'98), Berlin, Germany, pp. 121-129, Oct 1998. [10] S. K. Sen, S. K. Das, K. Basu, and J. Jawanda, Quality of Service Degradation Strategies in Multimedia Wireless Networks, Proceedings of the IEEE Annual Vehicular Technology Conference (VTC'98), Ottawa, Canada, pp. 1884-1888, May 1998. [11] S. K. Das, N. K. Kakani, R. Jayaram, and S. K. Sen, \Reservation Mechanisms for Mobile Nodes in the Internet," Proceedings of the IEEE Vehicular Technology Conference (VTC'99), Houston, May 16-20, 1999, to appear. [12] S. K. Das, S. K. Sen, R. Jayaram. Call Admission and Control for Quality-of-Service Provisioning in Cellular Networks. Proceedings of IEEE International Conference on Universal Personal Communications (ICUPC), San Diego CA, October 1997, pp. 103-113. [13] R. Jayaram, N. K. Kakani, S. K. Das, and S. K. Sen, Call Admission and Control for Quality-of-Service (QoS) Provisioning in Next Generation Wireless Networks, to appear in the ACM/Baltzer Journal on Mobile Networks (Guest Editor: R. Rao), 1998. [14] E. Nikula, A. Toskala, E. Dahlman, L. Girard, A. Klein, \FRAMES Multiple Access for UMTS and IMT-2000", IEEE Personal Communications Magazine, April 1998.
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