Architecture of a Web Accelerator for Wireless Networks

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1 Architecture of a Web Accelerator for Wireless Networks Jian Song, Yanchun Zhang School of Computer Science and Mathematics, Victoria University Melbourne, Victoria 8001 Australia, Abstract With the continuous growth of mobile users and web-based wireless applications, the performance of accessing web services via wireless is becoming one of the key issues. Regular has many problems to tackle wireless connections. Especially for 2.5G or 3G mobile users, the bandwidth is always limited to access various applications. In this paper, we describe the design, implementation and evaluation of a web accelerator. Our proposed web accelerator increases the web pages retrieval speed and maximizes bandwidth utilization of / application to overcome the obstacles of wireless networks. This goal has been achieved by two solutions: first, replacing with Boosted Protocol (B) to improve the performance of over wireless; second, compressing the web content to make it efficient for various wireless devices.. Keywords: (Transmission Control Protocol), Web acceleration, Wireless Network, Compression. 1 Introduction As mobile users and web-based wireless applications continue to grow, the wireless accesses to a variety of web services through various devices such as laptop, PCs, PDAs, smart phones, etc., are becoming very popular today. However, as applications shift from the traditional transaction exchange to Internet/Intranet access, and its performance over wireless links are not successful as wired networks. Through researches and experiments, it is apparent that over wireless links results in many problems (George Xylomenos, G.C. Polyzos, Petri Mahonen and Mika Saaranen 2001). Characteristics of wireless link have significant effects on performance, including latency of physical layer, bandwidth oscillation, asymmetric uplink and downlink, delay spikes and intersystem handovers etc. Many features of wireless networks can result in various delays e.g. ( H. Inamura, G. Montenegro, R. Ludwig, A. Gurtov, and F. Khafizov 2003). One example in 2.5G/3G networks, a delay spike is an abrupt increase in the latency of the communication path. 2.5G/3G links are likely to experience delay spikes exceeding the typical round-trip-time (RTT) by several Copyright (c) 2007, Australian Computer Society, Inc. This paper appeared at the Thirtieth Australasian Computer Science Conference (ACSC2007), Ballarat, Australia. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 62. Gillian Dobbie, Ed. Reproduction for academic, not-for profit purposes permitted provided this text is included. times. It can cause spurious timeouts, unnecessary retransmissions and a multiplicative decrease in the congestion window size e.g. (F. Xin, A. Jamalipour 2005). Another example, in mobile networks, if multiple users want to transfer large amounts of data at the same time, the scheduler may have to repeatedly allocate and de-allocate resources for each user. Periodic allocation and release of high-speed channels can be referred to as Bandwidth Oscillation. Bandwidth Oscillation effects such as spurious retransmissions were identified e.g. (M. Scharf, M. Necker, and B. Gloss 2004 and Ludwig, R. and R. H. Katz 2000), as factors that degrade throughput. There are research studies such as (Khafizov, F. and M. Yavuz 2002 and Yavuz, M. and F. Khafizov 2002), which show that in some cases Bandwidth Oscillation can be the single most important factor in reducing throughput. Many modifications of have been pointed out to eliminate the degrading of performance over wireless networks, such as M- (K. Brown and S. Singh 1997), I- (Ajay Bakre, B.R.1995), W- (P. Sinha, N. Venkitaraman, R. Sivakumar, V. Bharghavan 1999), snoop and Freeze- (Goff T, Moronski J, Phatak DS. 2000). Whilst, narrow bandwidth, slow response and high resource utilization are main difficulties for wireless network users. In this paper, we propose a web accelerator which combines optimization and web content compression together to eliminate these obstacles. Firstly, we present a solution to address the limits of using Boosted (B). We replace the protocol with the B to enhance the transport layer performance in wireless environment. From the experiment results, wireless terminals could experience the advantage of optimized bandwidth conditions that increase five fold from the usual connection. Then we discuss the web content compression strategy based on the zlib algorithm (P. Deutsch, J.-L. Gailly 1996) (same algorithm used in the popular internet tool gzip (L. Peter Deutsch 1996), which benefits the mobile clients when the available bandwidth is scarce (e.g. GPRS or 1-2Mbps wireless radio links). Compression gains depend on the content that is transferred. The main contribution of this architecture is the combination of optimization and web content compression in wireless environment, aiming to maximize the web surfing experience of wireless users, especially for 2.5G or low speed wireless connections. This platform has been tested in China Mobile GPRS network in Beijing. The rest of paper is organized as follows. Section 2 presents the design of our web acceleration platform architecture. In the following two sections,

2 implementation and evaluation of this system are reported. We draw the conclusion and the future work in the last section. 2 Architecture of the Web Accelerator Our web accelerator acts as a proxy server between clients and Internet. As shown in figure 1, the web accelerator could be placed in ISP (Internet Service Provider) side. Mobile users connect to Internet through BS (Base Station) by various wireless links (e.g. GSM, GPRS, CDMA, CDPD etc.). optimization occurs between mobile clients and BS, which will be discussed in following section 2.2. Processing of the web compression is presented in section 2.3. Clients Wireless BS Cache WEB Sever ISP server Web Accelerate Server DNS Server INTERNET Web Services Web Services Figure 1: The Web Accelerator resides in ISP s local network and performs the optimization and web content compression. 2.1 over Wireless Links was specifically designed as a flexible protocol that can operate on various links such as dial-up to Gigabit Ethernet LANs, however it is not optimal on any of these links. Experience with usage over wireless links proves that the performance and resource consumption of over a wireless link is unacceptable (George Xylomenos, G.C. Polyzos, Petri Mahonen and Mika Saaranen 2001). Slow Start. uses a congestion control algorithm to manage the volume data of the sender (W. Richard Stevens 1997). performs a detection process called Slow Start whenever a connection is made because is unaware of the link bandwidth. calculates the lowest possible bandwidth and increases exponentially until a packet loss is detected. In the wireless environment, the long round trip time implies a long period during which the link is under-utilized and perceived by the user as slow. Congestion Avoidance. assumes all packet loss is caused by congestion. Hence, there is a reduction in the current transmission rate by half. Also, the slow start algorithm is changed into a much slower acceleration. If the packet loss occurred due to link noise, or other transient conditions, will still react in this manner. The result is unused link capacity which means a slower data transfer. Receive Window Size. An application that sends data using is only allowed to send as many bytes that are explicitly allowed in the last packet seen from the intended destination. (This is to make sure the destination has enough space to store the bytes about to be sent.) This value is known as the Advertised Receive Window. Typically, this is set to about 8 Kbytes, which severely limits the top speeds that a connection can transfer data over a wireless link. The actual bandwidth can be calculated according to the RTT and the window size using the formula (1): Max BPS = RWIN / RTT (1) For example, consider a 1 Mbps wireless link with a 250ms delay and 4Kbytes window size -- only 128 Kbps will be sent on a 1 Mbps link. It will still limit s speed. 3-way Handshake. The three-way handshake requires three RTTs before there is an initiation of sending data. It adds extra time for each wireless connection. 2.2 B Basic Structure and Features The B is a -like reliable protocol that replaces over the path where performance optimization is needed. packets from a source location are transformed from to B and sent to the destination. There they are transformed back into and sent to the originally intended target. Web Accelerator manages both B and flow control and data queues to allow a full protocol conversion. Protocol conversion is illustrated in figure 2. Client Standard / Protocol Translator B Network Optimized Protocol Translator B Standard / Server Figure 2: The Web Accelerator replaces over the path of wireless links between mobile users and BS. To address the issues, our proposed B improves the performance by using following strategies. Pre-Tuned Parameters. B consistently operates at a high data rate in order to maximize the use of bandwidth resources. It can be optimized to the specific link in use to take into account bandwidth, delay, bit error ratio, and Maximum Transmission Unit (MTU) size. Immediate Transmission at Full Speed. Unlike, the B protocol does not need to perform Slow Start in order to discover available bandwidth. Transmission begins at the full rated link speed from the first byte. Changed Congestion Avoidance. Unlike, this slows data transfer dramatically after a lost packet is detected. B always assumes lost packets are due to BER and not congestion. Thus, it will always recover from lost packets using immediate and selective retransmission without reducing speed or bandwidth utilization. As a result, B can fill any wireless pipe regardless of latency or BER. No 3-way Handshake. The B protocol keeps a tunnel open between the Client and the Server,

3 eliminating the need for the standard 3-way handshake. 2.3 Web Content Compression A compression system directly reduces the amount of traffic that needs to be transported, saves bandwidth, speeds up response time and shortens transfer times despite the CPU time required for decompressing the responses. Our proposed web accelerator offers lossless compression based on the zlib algorithm (same algorithm used in the popular internet tool gzip, and other compression algorithms may be used, too). Compression gains depend on the content that is transferred. Average overall compression ratios are about 25%-30% for Web traffic, which depends on what kind of contents. The reason why we choose to use zlib is mainly because it is a good compression algorithm for which sources and specifications are easily available. Zlib supports compression level from 0 to 9, which means we could control the compression complexity and compression ratio between these 10 levels. socket from random port pool. Thread handles all out going traffic from accelerator to the Internet. Thread B Thread Client Architecture Proxy Aware App. Predefined Port Pool APP. API B to UDP socket Thread B Thread connections APP. Figure 4: Client and Server architectures Server Architecture API B Predefined working port/ Random port pool to UDP sockets 3 Implementation of the Web Accelerator In order to evaluate and validate the web accelerator, we deployed our Solaris-based accelerator server in real ISP s local backbone network (China Mobile, Beijing). The environment of the implementation is illustrated as figure 3. CommHub Web Accelerator Radius Server Web Servers GGSN Switch SGSN P C U GPRS/1xRTT Network China Mobile Backbone GPRS/1xRTT user Clients Accelerated Traffic tunnel Internet Figure 3: Implementation of Web Accelerator in ISP The GPRS mobile clients get wireless link from the nearest BS, and get through the GPRS network to China Mobile Backbone, then connect to Internet. The mobile users could be client program installed or clientless mode. The whole accelerated traffic occurs between mobile users and our web accelerator. The traffic flow and HTTP connection over B are shown in figure 4 and figure 5. From the client side, client listens on predefined ports, each of which support one protocol (e.g. Http 9090, A port 9876, FTP 9091, Free_ xxxx, SSL 9092). Thread handles all sockets from user applications to predefined ports. Then B thread handles all out going traffic to accelerator. In server side, Server receives new B connections on predefined working port, which are acknowledged on new Figure 5: HTTP connections over B 4 Evaluation of Performance Gain and User Experience In this section, we have evaluated the performance of the web accelerator by three different set of experiments. First, B and throughputs for various delays has been tested and compared. The following figure 6 shows a throughput comparison test for traffic transferred over GPRS link between and B. It is apparent that throughput reduces significantly during long round trip time, which means that the link is under-utilized and perceived by the user as slow. On the contrary, B only experiences a small decrease during same time.

4 Download Byte Count Throughput (% of maximum) 100.0% 80.0% 60.0% 40.0% 20.0% B and Throughput Vs. Delay 0.0% Round Trip Time (ms) B Fig. 6. B throughput compared with throughput for various delays In the second experiment, we evaluated the HTTP performance over B and without compression. For each page retrievable with B the browser starts with the unavoidable RTT as for the first object. After that the user will receive constant data stream at high rate much like FTP transfer of the object. This results in faster page retrieval. Table 1 lists some web sites of test done on GPRS link. URL Download time (sec) B Table 1: Comparison of download time for B and In the third experiment, we compared the web browsing of a few typical websites in three situations: standard, B and B plus web content compression. Figure 7 visualizes the bandwidth savings achieved with different situations. We realized maximum savings through the reduction of overhead required by Slow Start, congestion avoidance and web content compression. But, it will be noted that the savings in download bytes varied widely from site to site. The savings is based on the nature of the site. For example, the CNN ( site is mostly text and therefore can be compressed very efficiently. The NASA ( site is mostly images that are already compressed (GIF or JPEG), therefore, fewer saving is realized. KBytes Standard B B + Compression 0 cnn altavista goldmansachs netscape NASA Standard B B + Compression Fig. 7: Bandwidth savings of some websites with or without B and compression 5 Conclusions and future work In this paper, we presented the design, key points of the architecture, implementation and evaluation of a web accelerator. Our accelerator has been deployed and tested in a typical ISP s backbone to improve the performance of web browsing for GPRS users. As the results of experiments showed, mobile users benefited from our B and content compression. We concluded that B is useful to cope with the problems of over wireless connections, and web content compression could optimize the utility of the bandwidth. Combining two solutions is a good way for wireless web browsing, but the performances differ from site to site, for they are based on the contents of the site. The text-based sites can be compressed more efficiently than picture-based sites. In the current work, the lossy algorithm has not been incorporated in our accelerator, which can reduce the data size and the quality of compressed pictures (e.g. JPEG, GIF). In the future, we will continue the work with lossy compression. Another concern about our web accelerator is the additional CPU time and resource requirements for both client and server sides, which will decrease the performance under high demand situations. 6 References George Xylomenos, G.C. Polyzos, Petri Mahonen and Mika Saaranen (2001): Performance Issues over Wireless Links, IEEE Communications Magazine. H. Inamura, G. Montenegro, R. Ludwig, A. Gurtov, and F. Khafizov (2003): over second (2.5G) and third (3G) generation wireless networks. In RFC F. Xin, A. Jamalipour (2005): performance in wireless networks with delay spike and different initial congestion window sizes. In Computer Communications xx (2005) 1-8 M. Scharf, M. Necker, and B. Gloss (2004): The sensitivity of to sudden delay variations in mobile networks. In Springer LNCS series, Proc. Networking 2004, Athens, Greece. Ludwig, R. and R. H. Katz (2000): The Eifel Algorithm: Making Robust Against Spurious Retransmissions. ACM Computer Communication Review 30(1).

5 Khafizov, F. and M. Yavuz (2002): Running over IS Proc. of IEEE ICC. Yavuz, M. and F. Khafizov (2002): over Wireless Links with Variable Bandwidth. Proc. of IEEE Vehicular Technology Conference. K. Brown and S. Singh (1997): M-: for Mobile Cellular Networks, ACM Computer Communications Review, vol27, no.5. Ajay Bakre, B.R. Badrinath (1995): I-: Indirect for Mobile Hosts, Tech Rep., Reuters university, l. P. Sinha, N. Venkitaraman, R. Sivakumar, V. Bharghavan (1999): W: a reliable transport protocol for wireless wide-area networks, Proc. of ACM Mobicom 99, Seattle, WA, pp Goff T, Moronski J, Phatak DS. (2000): Freeze-: A true end-to-end enhancement mechanism for mobile environments. In Proceedings of the IEEE INFOCOM, March. P. Deutsch, J.-L. Gailly (1996): ZLIB Compressed Data Format Specification version 3.3, RFC1950. L. Peter Deutsch, (1996): GZ file format specification version 4.3, RFC1952. W. Richard Stevens (1997): slow start, congestion avoidance, fast retransmit, and fast recovery algorithms, IETF RFC 2001.

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