GATEWAY TRAFFIC COMPRESSION

Transcription

1 GATEWAY TRAFFIC COMPRESSION Name: Devaraju. R Guide Name: Dr. C. Puttamadappa Research Centre: S.J.B. Institute of Technology Year of Registration: May 2009 Devaraju R 1

2 1. ABSTRACT: In recent years with an explosive growth in the number of users on the Internet, bandwidth demand has grown tremendously. Various files are transferred across the network mainly from servers to client computers. Most existing network infrastructures cannot meet the bandwidth demand. This in turn increases the retrieval latency. In the corporate world where the sharing of data needs to be done at a faster rate and without any delay, they adopt the dedicated lines across their branches called Leased Lines. A leased line is a symmetric telecommunications line connecting two locations, these lines are very expensive based on the speed and bandwidth they offer. With Data Compression and Decompression techniques, the process of encoding the data using fewer bits uses specific encoding scheme. Compressed data communication works when both the sender and receiver of the information understand this encoding scheme. The design of data compression technique involve trade-offs between various factors like the degree of compression, the amount of distortion removed and the computational resources required to compress and decompress the data. Gateway device network traffic compression defines and implements how the compression/decompression daemon will intercept incoming ingress extract the network packet payload, compresses and routes the same to its egress, how it affects the retrieval latency, how it influences the traffic, reduces the collision across data packets, reduces the loss of Network packets containing some data in the payload. This project describes the Implementation of Lossless coding techniques. The objective of this project is to develop software architecture to incorporate the Gateway Network Payload Compression feature in a Core Layer Network Device. Devaraju R 2

3 The operating speed of the corporate LAN will depend on the link speed provided by the third party network service providers. But still sometimes this speed will not be always guaranteed or even if it is guaranteed will be affected by various reasons such as: Unwanted broadcasts packets or keep-alive packets. Malicious packets generated by the spy-ware software existing in the internal corporate LAN or the same pumped from an un-trusted outside network. Sudden bursty nature of the traffic. Less link speed than what is required. Improper routing/switching strategy. Nature of the packets (i.e) more data downloads/uploads. 2. OBJECTIVE: The objective of this project is to develop software architecture to build a WAN Network Traffic Acceleration Framework on a Linux Box implemented in C. The initial prototype version is written in user-space, but later the actual core mechanism would be supported in the kernel space. To control the same, a thin user-space application would be provided which provides both Command-Line-Interface (CLI) and Web based Graphical-User-Interface(GUI) to the users. The users can configure, fine-tune the operations in the actual Traffic Compressor kernel core modules using this user-space application also they can monitor the performance and possibly get the run-time statistics, charts/graphs of the Traffic Squeezer operation with the corresponding traffic which it optimizes and sends through it. Devaraju R 3

4 3. METHODOLOGY: To get connectivity between various branches of the organization, a corporate will need a leased line links to their terminating/edge gateways. The gateway devices connect to the service provider s leased line circuits and get connected to their remote branch offices. These Leased bandwidth prices are quite high, compared to dial up bandwidth of comparable size. Entry level annual port prices are also high, so that this access method is only feasible beyond a fairly high threshold level. Permanent connectivity to the Net exposes the organization to a variety of threats including hacking, malicious code including active vandals, viruses, Trojan Horses, macros, denial of service attacks etc. The Leased Bandwidth allotted for our corporate network is just 512kbps to 2Mbps. The data which is sent can be compressed in this scenario and sent through the same less capacity leased line. Since the payload is compressed, the user will get more effective use of the less available bandwidth. So, with this same link speeds the users will get a better performance. Typically, such a deployment looks as shown in the below picture. Network Service Provider (Leased Line) Network Payload [Site A] [Site B] Figure 1 Existing scenario Devaraju R 4

5 Network Service Provider (Leased Line) Compressed Network Payload Tunnel [Site A] Traffic Compression Device Traffic Compression Device [Site B] Figure 2 Scenario with Traffic Compression Device To achieve maximum compression ratio, Traffic Compressor proposes a design in which the compression of the network payload have been compressed with more than one loss-less compression algorithms. Since the current design includes couple of compression methods done in sequence, the design of this specific packet processing engine can be called as a Multi-Stage cascaded Compression/Decompression Engine. 3.1 Tools: LabVIEW, is a platform and development environment for a visual programming language from National Instruments. The graphical language is named "G". LabVIEW provides an extensive support for accessing instrumentation hardware. Drivers and abstraction layers for many different types of instruments and buses are included or are available for inclusion. These present themselves as graphical nodes. The abstraction layers offer standard software interfaces to communicate with hardware devices. The provided driver interfaces save program development time. Devaraju R 5

6 4. REFERENCES: 5.[1] Quanping Huang, Rongzheng Zhou and Zhiliang Hong, Low Memory and Low complexity VLSI Implementation of JPEG 2000 Codec, IEEE Transactions on Consumer Electronics, Vol. 50, May 2004, pp [2] Kishore Andra, Chaitali Chakrabarti and Tinku Acharya, A High-Performance JPEG 2000 Architecture, IEEE Transactions on Circuits and Systems for Video Techonology, Vol. 13, NO. 3, March2003, pp [3] D. D. Taubman and M. W. Marcellin, JPEG 2000 Image Compression Fundamentals, Standards and Practice, Kluwer Academic Publishers, [4] C. Christopoulow, A. Skodras and T. Ebrahimi, The JPEG 2000 Still Image Coding System: An Overview, IEEE transactions on Consumer Electronics, Vol. 46, No. 4, November 2000, pp [5] Majid Rabbani, Rajan Joshi, An Overview of the JPEG 2000 Still Image Compression Standard, Signal Processing: Image Communication, Vol. 17, 2002, pp [6] E. Ordentlich, D. Taubman, M. Weinberger, G. Seroussi, and M. Marcellin, Memory Efficient Scalable Line-Based Image Coding, Pmc. IEEE Data Compression Conference (Snowbird). March 1999, pp [7] JPEG 2000 Committee Drafts, available online at: Devaraju R 6