TRIBLERCAMPUS: INTEGRATED PEER-TO-PEER FILE DISTRIBUTION IN COURSE MANAGEMENT SYSTEMS

Transcription

1 TRIBLERCAMPUS: INTEGRATED PEER-TO-PEER FILE DISTRIBUTION IN COURSE MANAGEMENT SYSTEMS M. Meulpolder 1, V.A. Pijano III 2, D.H.J. Epema 1, H.J. Sips 1 M.Meulpolder@tudelft.nl 1 Parallel and Distributed Systems Group Delft University of Technology Delft, The Netherlands 2 Holy Angel University Angeles City, The Philippines ABSTRACT: Course Management Systems (CMSs) are widely used in educational institutions around the world to manage course information and to distribute educational content. The existing facilities of CMSs can make them an ideal platform for distributing digital lectures and high-quality multimedia content within campuses and for distance learning. However, all major implementations of CMSs (e.g., Blackboard, Moodle) are based on a client-server architecture. Because of this, the performance of these systems is limited, especially regarding the distribution of large files to large numbers of students. We propose to solve this problem by integrating peer-to-peer (P2P) technology with present CMSs in a transparent way, so that videos and other large files can be distributed with high performance and as easily as regular text documents. In this paper, we present the design of TRIBLERCAMPUS, which offers an integration of the BitTorrent-based Tribler peer-to-peer technology with CMSs. Our main idea is to equip every participating campus machine with a small and lightweight P2P core, which runs in the background and takes care of the download process of large files when they are requested via the CMS. Due to the P2P technology, all participating computers automatically contribute bandwidth to the system, thereby hugely boosting the performance. We present the results of measurements and trace-based simulations of a prototype implementation of TriblerCampus based on the popular open-source CMS Moodle. We show that the performance of TriblerCampus consistently stays high, even when the demand in the system reaches peak levels, and we discuss the applicability of the system in a distance learning setting. 1. INTRODUCTION Course Management Systems (CMSs) are among the most popular e-learning applications that are currently used at educational institutions around the world. They provide a large number of facilities to publish course information and materials, often with interactive features like discussion boards and digital examinations. Some well-known CMSs are Blackboard ( WebCT ( and, more recently, the open-source alternative Moodle ( By now, large numbers of universities and schools use a CMS to manage and enhance the courses in their curriculum. In some cases, CMSs are also used as a platform to provide courses that

2 are completely independent of regular classroom education. This approach is especially relevant in distance learning, where students must be able to complete courses without attending physical lectures. While institutions and their students are more and more able to access modern computers and high-speed infrastructures, there is a growing desire to utilize this technology to distribute high-quality multimedia content. Whereas a few years ago it was often the hardware and networking infrastructure that were inadequate for such needs, it now becomes more of an issue how the available infrastructure is utilized in an efficient manner. Efficient use of the infrastructure is a problem in CMSs, since all major systems are based on a client-server architecture. The limitations of this architecture regarding performance and scalability are well-known (Tanenbaum et al. 2002), and become especially relevant when large files have to be accessible for large numbers of users. As a result, current CMSs cannot be used in a scalable way to distribute multimedia content for course enhancement or distance learning. It is this problem that we address in this paper. In many areas of Computer Science, scalability limitations are overcome by applying distributed computing technology. In distributed computing, various techniques have been developed that combine the resources and computing power of multiple computers, in order to accomplish a common objective. One of the latest developments in distributed computing is the growing application of peer-to-peer technology and concepts. In peerto-peer (P2P) technology, every computer is regarded as an equal node acting both as a client and as a server. This technology is particularly suitable for content sharing among various members of a community and can offer huge advantages regarding performance and scalability. It offers more efficient ways to distribute large files, such as audio and video, to large numbers of computers. Several studies and articles have already pointed out that in e- learning P2P technology can solve current limitations, and can make it possible to adapt to the growing need for bandwidth and the sharing of content between students. Both regarding the technological advantages of distributing large files, as well as regarding the social nature of content sharing among students and teachers, peer-to-peer systems definitely seem promising and could very well turn out to be the key in solving many problems currently existing in the e-learning field (Derycke et al. 2003). As mentioned in (Kawamura et al. 2005), peer-to-peer systems have the potential of offering a decentralized, self-sustainable, scalable, fault tolerant, and symmetrical e-learning network providing an effective balancing of storage and bandwidth resources. Especially in campus environments, where many computers are available though relatively sparsely used, P2P technology can exploit the available resources to provide high-level learning services. However, until now only few initiatives have led to workable implementations and the tools that have been created are mostly small and very specific. In this paper, the design of a new platform is presented: TRIBLERCAMPUS. This platform aims to overcome the limitations of CMSs discussed above. Instead of designing a new and unknown scalable e-learning system, TriblerCampus is based on the transparent integration of the advanced Tribler peer-to-peer technology (Pouwelse et al. 2007) with present CMSs. Our prototype implementation is based on the highly popular open-source CMS Moodle. Even though Moodle is used in the current implementation, the core ideas and design of TriblerCampus are applicable to any web-based CMS. The Tribler technology itself is based on the BitTorrent P2P protocol, which is widely researched and shown to be very robust and scalable, and superior to other file sharing protocols. Due to the transparent integration, teachers and students can use the CMS in the regular way, without needing knowledge about the peer-to-peer mechanism on the background. In order to further improve the performance, we have extended Tribler with caching and replication mechanisms. First, active public computers in the campus cooperate in the process by sharing the contents of a local cache, thereby supplying bandwidth and storage. Secondly, a special kind of peers has been added (replicators) that replicate particular files. We show that in the resulting system, files are available with high speed even when the demand is very high. By utilizing present infrastructures more efficiently, TriblerCampus makes it possible to incorporate high-quality multimedia content distribution in CMSs. Combined with the existing facilities of CMSs, TriblerCampus offers a platform that provides course management, multimedia course enhancement, and distance learning, without additional hardware investments and with minimal user training.

3 2. RELATED WORK Various researchers in the fields of e-learning and computer science have been hinting at the possibilities of applying peer-to-peer technology and concepts to e-learning. Some go as far as (Zualkernan 2005) and state that peer-to-peer applications are being considered the future of e-learning. More and more people are attempting to combine peer-to-peer computing and e-learning aiming for business, academic, and individual use (Jin et al. 2004). In many of these cases only the didactical and social aspects of peer-to-peer content sharing are discussed. Educational content sharing among students is often referred to as peer-to-peer learning: an educational environment where information and resources are distributed and shared among all participants. However, this approach deals with the conceptual level of content sharing, regardless whether the underlying infrastructure is client-server based or distributed. Only few studies point out the advantages that peer-to-peer technology might have on a more technological level, in cases where large files have to be distributed to many students. The main idea behind all of the available initiatives is therefore clearly different from the application of P2P technology proposed in this paper. By far the largest of present developments is the LionShare project ( originally started at Penn State University, which aims to develop facilities for P2P collaborative learning among educational institutes around the world. Another initiative is that of Edutella (Nejdl et al. 2002, Qu et al. 2004), a framework for searching and annotating resources within an RDF-based P2P network, focusing on metadata. Smaller projects are SPLASH (Hatala et al. 2003), a heterogeneous P2P learning object repository; APEX (Leighton et al. 2004), a collaborative learning environment; and APPLE (Jin et al. 2004), a standalone P2P virtual classroom environment. All of these initiatives, except for APPLE, are utilizing P2P technology as a means to provide collaborative content sharing. 3. DESIGN AND ARCHITECTURE The main idea of TriblerCampus is to have peer-to-peer file distribution in the background of a regular Course Management System (see Fig. 1). The setup of the platform within a campus consists of a CMS server, and an arbitrary number of participating end-user computers. The CMS itself is still client-server based and can be accessed from online computers by a web browser. Furthermore, all participating computers are equipped with a lightweight background peer-to-peer client that automatically makes them part of the underlying peer-to-peer network. The resulting integration is transparent to the user, i.e., users such as teachers and students can use the already existing functionality of the CMS in the normal way. While regular communication and transfer of small files are still clientserver based, large files (>20 MB) are automatically distributed over the peer-to-peer network. Figure 1: The main idea of TriblerCampus

4 The server hosts a copy of every file that is uploaded to the CMS, so that availability of the files is assured. Furthermore, all peers manage a local cache that contains the files that are most recently downloaded. Every peer will share the files in its cache with the network, thereby contributing bandwidth and resources to the system. When a file is requested at a particular peer, pieces of the file are transferred as efficient as possible from all peers that are sharing or downloading the file. In TriblerCampus, the peer-to-peer core is based on Tribler ( which in its turn uses the BitTorrent protocol ( With this protocol, peers that are downloading the same file exchange pieces in a very efficient and scalable manner with minimal overhead. In order to further improve the performance of the system, dedicated peers can be added to the system (called replicators) that replicate a subset of the content. The details of this mechanism are outside the scope of this paper and are discussed in detail in (Meulpolder et al. 2007). Figure 2: The layered architecture of TriblerCampus. In order to integrate the peer-to-peer functionality, both the CMS server and the participating computers run a lightweight TriblerCampus application. The architecture is displayed in (Fig. 2) and consists of three layers: the CMS layer, which represents the regular CMS communication and traffic, the underlying Tribler P2P layer which is responsible for the actual file distribution, and the TriblerCampus layer that connects these two. At the CMS server, the CMS itself is extended with a module that can connect to the TriblerCampus Upload Interface. Whenever a large file is uploaded to the system, it will automatically become available in the peer-to-peer network. Instead of providing on its web pages a link to the file itself (as with regular content), the CMS will automatically provide a link to a small peer-to-peer metadata file that uniquely identifies the actual file. At the end-user computers, a small TriblerCampus client is running in the background, which automatically handles these metadata files when they are requested via the browser. The client will display a progress bar while downloading the corresponding file, and afterwards provide it to the user.

5 4. PERFORMANCE MEASUREMENTS AND SIMULATION We have performed a large number of measurements and simulations to assess the performance and scalability of the TriblerCampus system. The scalability of a single download is measured with real clients, while the performance of the full system is simulated using real-life traces of request behavior in an existing CMS at a large university. 4.1 Scalability of a single download In order to assess the scalability of a single download with many users at the same time, we have performed measurements in a lab room with a large number of machines. All machines have Pentium 1 Ghz processors with 256 MB of RAM, and run Windows XP. Each machine is connected to the campus network with a 100 Mbit/s adapter. One machine hosts the CMS server. We have executed simultaneous downloads of a file of 440 MB by 1, 2, 4, 16, and 40 downloaders, respectively. Before the start of the downloads, only the CMS server offers a copy of the file. All Figure 3: The download time of a 440 MB file with multiple simultaneous downloaders. downloads start at the same time. This represents a scenario in which for example a class is given where all students are required to download the same content simultaneously. The download times of both a TriblerCampus download and a client-server download are displayed in (Fig. 3). We can observe that with low numbers of downloaders, a client-server download still outperforms a TriblerCampus download. This is likely to be caused by the operating system, since running the application consumes more processing power and harddisk operations than a direct download from the server. However, for higher numbers of downloaders, TriblerCampus clearly outperforms a client-server system and shows very low overhead when the demand further increases. It is obvious that the downloaders benefit greatly from each other during the process. 4.2 Simulation of the full system In a real campus environment, request behavior is usually very dynamic and download processes for different files influence each other. In order to be able to compare the client-server performance with the TriblerCampus performance under real-life scenarios, we have built a trace-based simulator of a full system that would be operational at a campus. With this simulator, the performance of various system configurations is analyzed based on real-life request traces. In order to simulate realistic campus behavior, we have used extensive traces of requests in the Blackboard system at our university campus. The dataset covers the period of September 2005 up until August 2006 and contains information about the number of file requests per day, and the average number of file requests per hour of the day. From the available traces, the pattern of requests during an average weekday has been extracted. Based on the resulting distribution, samples have been generated of various sizes, which were used as input for the simulator. We compare three different configurations: (1) client-server; (2) plain BitTorrent; (3) TriblerCampus. We assume that all files in the system have a size of 500 MB, which is a reasonable size for approximately one hour of high-quality video (such as a digital lecture). We assume that after completing the download, the machine of a user will remain online for 30 minutes and share the recently downloaded file. This is a somewhat arbitrary value, based

6 Figure 4: Performance of the client-server, BitTorrent, and TriblerCampus systems during a representative day at the campus. The histogram displays the number of requests that come in per 30 minutes. The main plot displays the average download bandwidth at that time over all active downloaders in the system. on the intuition that some people will watch the entire video as soon as it is completed, while others will for some reason or another not start to watch, or watch only a part of the video. We have used maximum upload and download speeds of 5 MB/s for all machines, based on the speeds observed during experiments in real labrooms. These speeds are lower than the theoretical maximum speed of 100 MBit/s, since they are affected by hardware and Windows XP operating system characteristics. The simulations are based on a full 24 hour interval, starting at 4:00 AM. This time period was chosen because the pattern of the Blackboard dataset repeats itself daily, with the lowest number of requests around 4:00 AM. 4.3 System performance The results of the simulations give a clear picture of the difference in performance characteristics for the various configurations. The average bandwidth in the system for a representative scenario is displayed in (Fig. 4). In this scenario, there are 400 requests simulated during one day. A histogram of the request arrivals is displayed with the corresponding average received bandwidth over all users. We can directly observe that during times of relatively few requests (before 9:00 and after 17:00) all configurations perform more or less the same, and the resulting bandwidths are close to the maximum available bandwidth. This is intuitive, since when the frequency of request arrivals is low, the number of users active in the system at the same time, will be low. In such a situation, each configuration, even the client-server configuration, will be able to handle each incoming request quickly. During the main peak of arrivals (9:00-17:00), the performance of the client-server configuration drops dramatically. The plain BitTorrent system performs slightly better, though the peaks in requests still cause a significant drop in performance. Yet, the performance of the TriblerCampus system consistently stays high. It hardly drops when peaks in request arrivals occur. In (Fig. 5), the average, the standard deviation range, and the maximum are plotted over all downloads that occurred during the day. While the client-server system leads to an average download time of approximately 20 minutes for the 500 MB file, the TriblerCampus system obtains an average download time of less than 3 minutes. The maximum download time in the client-server system is more than 50 minutes, while this is only about 10 minutes in the case of TriblerCampus.

7 4.4 System scalability In order to assess the scalability of the system, simulations have been performed for increasing numbers of requests per day. In (Fig. 6), the average download time over all downloads is displayed for the various configurations with varying numbers of requests during a simulated day. Not surprisingly, the download time for the client-server system explodes when the number of requests increases, which is clearly visible for more than 400 requests. This is theoretically predictable, since when there are many users in the system and their speeds are very low, they will naturally remain longer in the system, thereby further reducing the speeds of new requests. The number of active downloads therefore builds up, resulting in dramatically low performance. The download time with plain BitTorrent shows considerable increase as well, though the performance is far better than that of a client-server configuration for more than 200 requests. The curve grows flatter when the number of requests increases. TriblerCampus offers an almost constant download time. When there are many users, there are many cached copies of the files available. When the number of users is high enough with respect to the number of available files, it is likely that there are copies of every file available in the caches. Hence, a constant download time after some point can be expected. Figure 5: Download time statistics. Figure 6: The scalability of the configurations. 4.5 Distance learning With the simulations we have focused on the distribution of content within a campus. We will briefly address the behavior of the TriblerCampus platform when it is used for distance learning. In this case, the system is accessed online, by machines that can in principle be located anywhere. In general, the TriblerCampus platform with its current design and implementation is fully suitable to be used in a distance learning setting. Any machine connected to the internet that is running the client software is able to download the content that is offered by the CMS. The machine will benefit from the P2P performance and scalability advantages as soon as others are online that are sharing the desired content. The resulting situation is similar to the way BitTorrent technology is currently used all over the world to share music and movies (See for example (Pouwelse et al. 2005) for performance measurements). In this case, the goal is to maximize the utilization of the machine's Internet connection. P2P technology and TriblerCampus can offer a very significant increase in performance and scalability for distance learning. The resulting performance characteristics in a real situation are entirely dependent on the number of users, their bandwidths, and the shared content.

8 5. IMPLICATIONS AND CONCLUSIONS In this paper, we have argued that due to the client-server architecture of currently available major CMSs, such systems suffer from a lack of performance and are not scalable. These systems are therefore not well suited to distribute high-quality multimedia course content to many students without requiring huge investments in additional hardware. Peer-to-peer technology offers efficient, scalable ways of distributing content to large numbers of users, and is therefore ideal to solve the problems of performance and scalability of CMSs. We present TriblerCampus that transparently integrates the advanced Tribler peer-to-peer software with existing CMSs. The resulting system offers an integrated e-learning infrastructure in which high-quality multimedia content can be published as easily as any other content. Due to the scalability of the underlying peer-to-peer protocols, the TriblerCampus platform offers a performance that makes it feasible to download large files with many users within a very small timeframe. Our analysis shows that the performance consistently stays high, both at times when system demand is low as when system demand is high. The TriblerCampus platform is highly scalable. It can serve large numbers of requests, and large numbers of files with high performance, thereby making it feasible to use the system at large institutes. The TriblerCampus platform is as well applicable in a distance learning setting, where the efficiency of present day file sharing protocols can greatly increase the obtainable download speed. By enabling CMSs to distribute high-quality multimedia with high speed, TriblerCampus can significantly enhance teaching, collaborating, and sharing at educational institutions around the world. REFERENCES (Derycke et al. 2003) (Hatala et al. 2003) (Jin et al. 2004) (Kawamura et al. 2005) (Leighton et al. 2004) (Meulpolder et al. 2007) (Nejdl et al. 2002) (Pouwelse et al. 2005) A. Derycke, F. Hoogstoel, X. le Pallec. The Reciprocity Project: A P2P Approach to Collaborative Environments for Life-Long Learning. In Proc. of the 33 rd ASEE/IEEE Frontiers in Education Conference, pages 5-10, November M. Hatala, G. Richards. SPLASH: A Heterogeneous Peer-to-peer Learning Object Repository. In Proc. of the 12 th International World Wide Web Conference (WWW 03), H. Jin, Z. Yin, X. Yang, F. Wang, J. Ma, H. Wang, J. Yin. APPLE: A Novel P2P Based E-learning Environment. In Proc. of the International Workshop on Distributed Computing (IWDC 04), pages 52-62, T. Kawamura, T. Nakatani, K. Sugahara. P2P E-learning System and its Squeak-based User Interface. In Proc. of the 3 rd International Conference on Creating, Connecting and Collaborating through Computing (C5 05), pages 57-62, January G. Leighton, T. Müldner. APEX: A P2P-Based Collaborative Learning Environment. Technical Report TR ( Acadia University, August M. Meulpolder, D.H.J. Epema, H.J. Sips. Replication in Bandwidth-Symmetric BitTorrent Networks. To appear in Proc. of the 13 th Annual Conference of the Advanced School for Computing and Imaging (ASCI 07), June W. Nejdl, B. Wolf, S. Staab, J. Tane. Edutella: Searching and Annotating Resources within an RDF-based P2P Network. In Proc. of the 11 th International World Wide Web Conference (WWW 02), Hawaii, USA, May J. Pouwelse, P. Garbacki, D. Epema, H. Sips. The BitTorrent File-Sharing System: Measurements and Analysis. In Proc. of the 4 th International Workshop on Peer-to- Peer Systems (IPTPS 05), February 2005.

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