Applications and Services

CH03.fm Page 83 Monday, March 1, 2004 3:31 PM C HAPTER 3 Applications and Services he cdma2000 wireless networks provide users with a wide range of applications, such as T voice, Web browsing, and email. As illustrated in Chapter 2, “Network Architecture,” different applications may require different services. For example, a user requests circuit-switched voice service by pressing the send button after dialing the number of the calling party. After end- to-end service is established, the caller and the calling party begin using the voice application. Activating a packet data service for a Web browsing application, however, requires activation of a different set of functions that are not invoked when circuit-switched voice service is established. Due to the limitation of the available spectrum, it is important that the frequency bandwidth is efficiently utilized. It is therefore necessary that the provided service closely matches the needs of the application. For example, email application requires reliable radio connection, but it is delay-tolerant. Hence, the efficiency of the air interface can be maximized at the expense of delay. For that purpose, Radio Link Protocol (RLP)1 and link adaptation techniques are commonly employed. Voice application is delay-intolerant, so RLP and link adaptation techniques are not acceptable. However, voice application is to some extent error-tolerant, and the air efficiency can be increased at the expense of higher error probability. The availability of a particular application is not only what users care about. Quality of Service (QoS) is also important, because QoS directly impacts user perception about the useful- ness of the application. 1. RLP is described in more detail in Chapter 5, “IS-2000 Layer 2 (Media and Signaling Link Access Control Lay- ers)”. 83 CH03.fm Page 84 Monday, March 1, 2004 3:31 PM 84 Chapter 3 • Applications and Services 3.1 Applications The cdma2000 wireless networks allow for a wide range of applications. The requirements that they impose to the service range from real-time to non-real time and from error-tolerant to error- intolerant. The service provided to an application takes into account its general traffic characteristics. To understand the rationale for the available services, in this section we describe the traffic characteristics of the most common applications. 3.1.1 Conversational Voice Voice application requires real-time service because conversational voice cannot tolerate delay. If the voice traffic is delayed by more than 200 ms, it can produce an annoying effect of users speaking simultaneously. λ Voice call arrivals can be modeled as a Poisson process. Denote the arrival rate with v. µ The call duration fits well into an exponential distribution with mean holding time of 1/ v. For wireless cellular networks, a typical mean holding time is between 1 and 2 minutes. Speech waveforms contain a high degree of redundancy. The cdma2000 networks exploit that redundancy and perform speech coding before transmitting the encoded signal over the air. The coding process significantly reduces the data rate necessary to carry speech signal, which directly increases system capacity or the number of users that can be simultaneously served over a given bandwidth. The rate at the output of the speech coder is variable, and it depends on many factors such as voice activity and nature of speech. Even after compression, voice traffic can tolerate occasional errors. Typically, a frame error rate (FER) of 1% to 3% is acceptable. The voice traffic characteristics are summarized in Table 3.1. Table 3.1 Voice Traffic Characteristics λ µ Arrival rate, λv Call duration, 1/µv Several calls per user per day 60–120 s 3.1.2 Internet Applications Many applications use the Internet. Most were originally designed for high-bandwidth wired networks and each has different traffic characteristics. What is common for most of them is that they are much more susceptible to errors than are voice applications. However, they do not have as stringent delay requirement as voice. The traffic characteristics differ from one application to another. In the text that follows, we provide the traffic models, adopted in [1], for a Web browsing session using HyperText Transfer Protocol (HTTP) [2], file download/upload using File Transfer Protocol (FTP) [3], Wireless Application Protocol (WAP) traffic [4], and video steaming [5]. These traffic models are extensively used in the industry for the air interface system-level simulations. They are rela- CH03.fm Page 85 Monday, March 1, 2004 3:31 PM Applications 85 tively simple, yet they reasonably accurately represent the corresponding traffic. Note that quantitative values for some parameters used to represent the traffic depend on many factors. Some of them are user-dependent, and some are external network-dependent. Hence, the quantitative values reported in this section should be considered as exemplary. 3.1.2.1 Web Browsing A packet trace of a typical Web browsing session is shown in Figure 3.1. As can be seen from the figure, the data arrival is bursty. The session can be divided into an interval in which the content of the Web page is being downloaded—referred to as packet data call period—and the user reading time. A typical Web page is written in eXtensible HyperText Markup Language (XHTML) [6] and consists of a main page and a bunch of embedded objects. By typing a Universal Resource Location (URL) address and sending the request to the server, a user triggers a download of the main page. On reception of the main object, the client software, residing at the mobile station, parses the main page for additional references regarding the embedded image files. Each embedded object generates a new request. The HTTP server, on receiving each of the requests, sends the embedded objects to the client. Web browsing applications are to some degree sensitive to the delay. What matters is the time from the instant the user requests a page download until the page with all the embedded objects is downloaded. The download time varies depending on the radio conditions, system load, and the size of a page. It could be as low as few seconds, but it could take 10 seconds or more. In Figure 3.2 we illustrate a typical call flow between a mobile station (MS) and the HTTP server during a Web browsing packet data call. Packet data session Packet data call Packet data call Packet data call . Main Reading time page Embedded objects Figure 3.1 Packet trace of a typical Web browsing session. CH03.fm Page 86 Monday, March 1, 2004 3:31 PM 86 Chapter 3 • Applications and Services HTTP server MS HTTP Request (URL) HTTP Response HTTP Requests - Embedded objects HTTP Response - Embedded objects Figure 3.2 HTTP call flow. The traffic model for the Web browsing session, as described in [1], can be characterized in terms of the following parameters: • Size of the main object • Size of the embedded objects in the Web page • Number of embedded objects in the Web page • Reading time • Parsing time for the main page • Size of the HTTP request The main object size can be modeled as a truncated lognormal random variable, X, as 1 −−()ln x µ 2 fx()=≥exp ,x 0 (3.1) X 2 2πσx 2σ σ σ µ µ with the parameters = m = 1.37, = m = 8.35, the minimum size of the main page of 100 bytes, and the maximum size of 2 Mbytes. The size of the embedded objects can also be mod- σ σ µ µ eled as a truncated lognormal variable, with the parameters = e = 2.67, = e = 6.17, the minimum main page size of 50 bytes, and the maximum size of 2 Mbytes. The number of CH03.fm Page 87 Monday, March 1, 2004 3:31 PM Applications 87 embedded objects per main page, Ne, can be modeled as follows. Generate a truncated Pareto random variable, Y: α α k fy()=≤<, kym Y α +1 y (3.2) α fy()== Y ()km/ , ym α α with the parameters = Ne =1.1, k = kNe = 2, and the maximum m = mNe = 55. Subtract k from Y; that is, Ne = Y – k. The reading time and parsing time can both be modeled as exponentially distributed variable, Z: −λz fz()=≥λ (3.3) Z ez,0 λ λ λ λ For the reading time, that arrival rate is = r= 0.033, while for the parsing time, it is = p = 7.69. Note that the reading time is a heavily user-dependent parameter, and it can vary significantly. The HTTP requests can be modeled as fixed size, 350-byte packets. Table 3.2 summa- rizes the traffic model for a Web browsing session. Table 3.2 HTTP Traffic Model Characteristics Component Distribution Parameters Main object size Truncated lognormal Mean = 10.71 kbytes Std. dev. = 25.032 kbytes Embedded object size Truncated lognormal Mean = 7.758 kbytes Std. dev. = 126.168 kbytes Number of embedded Truncated Pareto Mean = 5.64 objects Max. = 53 Reading time Exponential Mean = 30 s Parsing time Exponential Mean = 0.13 s Request size Deterministic* 350 bytes * In practice, HTTP request can significantly vary in size. CH03.fm Page 88 Monday, March 1, 2004 3:31 PM 88 Chapter 3 • Applications and Services 3.1.2.2 File Download/Upload The traffic characteristics of a file download or upload are quite different from Web browsing traffic characteristics. A commonly used protocol for file transfer is FTP. The length of the file can vary greatly. The FTP applications are even less sensitive to delay than are Web browsing applications.

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