An investigation into the design and implementation of an internet-scale network simulator
- Authors: Richter, John Peter Frank
- Date: 2009
- Subjects: Computer simulation , Computer network resources , Computer networks , Internet
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4597 , http://hdl.handle.net/10962/d1004840 , Computer simulation , Computer network resources , Computer networks , Internet
- Description: Simulation is a complex task with many research applications - chiey as a research tool, to test and evaluate hypothetical scenarios. Though many simulations execute similar operations and utilise similar data, there are few simulation frameworks or toolkits that allow researchers to rapidly develop their concepts. Those that are available to researchers are limited in scope, or use old technology that is no longer useful to modern researchers. As a result of this, many researchers build their own simulations without a framework, wasting time and resources on a system that could already cater for the majority of their simulation's requirements. In this work, a system is proposed for the creation of a scalable, dynamic-resolution network simulation framework that provides scalable scope for researchers, using modern technologies and languages. This framework should allow researchers to rapidly develop a broad range of semantically-rich simulations, without the necessity of superor grid-computers or clusters. Design and implementation are discussed and alternative network simulations are compared to the proposed framework. A series of simulations, focusing on malware, is run on an implementation of this framework, and the results are compared to expectations for the outcomes of those simulations. In conclusion, a critical review of the simulator is made, considering any extensions or shortcomings that need to be addressed.
- Full Text:
- Date Issued: 2009
- Authors: Richter, John Peter Frank
- Date: 2009
- Subjects: Computer simulation , Computer network resources , Computer networks , Internet
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4597 , http://hdl.handle.net/10962/d1004840 , Computer simulation , Computer network resources , Computer networks , Internet
- Description: Simulation is a complex task with many research applications - chiey as a research tool, to test and evaluate hypothetical scenarios. Though many simulations execute similar operations and utilise similar data, there are few simulation frameworks or toolkits that allow researchers to rapidly develop their concepts. Those that are available to researchers are limited in scope, or use old technology that is no longer useful to modern researchers. As a result of this, many researchers build their own simulations without a framework, wasting time and resources on a system that could already cater for the majority of their simulation's requirements. In this work, a system is proposed for the creation of a scalable, dynamic-resolution network simulation framework that provides scalable scope for researchers, using modern technologies and languages. This framework should allow researchers to rapidly develop a broad range of semantically-rich simulations, without the necessity of superor grid-computers or clusters. Design and implementation are discussed and alternative network simulations are compared to the proposed framework. A series of simulations, focusing on malware, is run on an implementation of this framework, and the results are compared to expectations for the outcomes of those simulations. In conclusion, a critical review of the simulator is made, considering any extensions or shortcomings that need to be addressed.
- Full Text:
- Date Issued: 2009
Using semantic knowledge to improve compression on log files
- Authors: Otten, Frederick John
- Date: 2009 , 2008-11-19
- Subjects: Computer networks , Data compression (Computer science) , Semantics--Data processing
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4650 , http://hdl.handle.net/10962/d1006619 , Computer networks , Data compression (Computer science) , Semantics--Data processing
- Description: With the move towards global and multi-national companies, information technology infrastructure requirements are increasing. As the size of these computer networks increases, it becomes more and more difficult to monitor, control, and secure them. Networks consist of a number of diverse devices, sensors, and gateways which are often spread over large geographical areas. Each of these devices produce log files which need to be analysed and monitored to provide network security and satisfy regulations. Data compression programs such as gzip and bzip2 are commonly used to reduce the quantity of data for archival purposes after the log files have been rotated. However, there are many other compression programs which exist - each with their own advantages and disadvantages. These programs each use a different amount of memory and take different compression and decompression times to achieve different compression ratios. System log files also contain redundancy which is not necessarily exploited by standard compression programs. Log messages usually use a similar format with a defined syntax. In the log files, all the ASCII characters are not used and the messages contain certain "phrases" which often repeated. This thesis investigates the use of compression as a means of data reduction and how the use of semantic knowledge can improve data compression (also applying results to different scenarios that can occur in a distributed computing environment). It presents the results of a series of tests performed on different log files. It also examines the semantic knowledge which exists in maillog files and how it can be exploited to improve the compression results. The results from a series of text preprocessors which exploit this knowledge are presented and evaluated. These preprocessors include: one which replaces the timestamps and IP addresses with their binary equivalents and one which replaces words from a dictionary with unused ASCII characters. In this thesis, data compression is shown to be an effective method of data reduction producing up to 98 percent reduction in filesize on a corpus of log files. The use of preprocessors which exploit semantic knowledge results in up to 56 percent improvement in overall compression time and up to 32 percent reduction in compressed size. , TeX , pdfTeX-1.40.3
- Full Text:
- Date Issued: 2009
- Authors: Otten, Frederick John
- Date: 2009 , 2008-11-19
- Subjects: Computer networks , Data compression (Computer science) , Semantics--Data processing
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4650 , http://hdl.handle.net/10962/d1006619 , Computer networks , Data compression (Computer science) , Semantics--Data processing
- Description: With the move towards global and multi-national companies, information technology infrastructure requirements are increasing. As the size of these computer networks increases, it becomes more and more difficult to monitor, control, and secure them. Networks consist of a number of diverse devices, sensors, and gateways which are often spread over large geographical areas. Each of these devices produce log files which need to be analysed and monitored to provide network security and satisfy regulations. Data compression programs such as gzip and bzip2 are commonly used to reduce the quantity of data for archival purposes after the log files have been rotated. However, there are many other compression programs which exist - each with their own advantages and disadvantages. These programs each use a different amount of memory and take different compression and decompression times to achieve different compression ratios. System log files also contain redundancy which is not necessarily exploited by standard compression programs. Log messages usually use a similar format with a defined syntax. In the log files, all the ASCII characters are not used and the messages contain certain "phrases" which often repeated. This thesis investigates the use of compression as a means of data reduction and how the use of semantic knowledge can improve data compression (also applying results to different scenarios that can occur in a distributed computing environment). It presents the results of a series of tests performed on different log files. It also examines the semantic knowledge which exists in maillog files and how it can be exploited to improve the compression results. The results from a series of text preprocessors which exploit this knowledge are presented and evaluated. These preprocessors include: one which replaces the timestamps and IP addresses with their binary equivalents and one which replaces words from a dictionary with unused ASCII characters. In this thesis, data compression is shown to be an effective method of data reduction producing up to 98 percent reduction in filesize on a corpus of log files. The use of preprocessors which exploit semantic knowledge results in up to 56 percent improvement in overall compression time and up to 32 percent reduction in compressed size. , TeX , pdfTeX-1.40.3
- Full Text:
- Date Issued: 2009
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