Manzoor, U 2011, An intelligent fault tolerant multi-agent framework for automated node monitoring and software deployment , PhD thesis, Salford : University of Salford.
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Computer networks today are far more complex than in 1980s and managing such networks is a challenging job for network management team. With the ever growing complexity of computer networks and the limitations of the available assistance softwares / tools, it has become difficult, hectic, and time consuming for the network management team to execute the tasks such as traffic monitoring, node monitoring, performance monitoring, software deployment etc over the network. To address these issues, researchers as well as leading IT companies have moved towards a new paradigm called Autonomic Computing whose main is the development of self- managing systems. Autonomic system makes decision autonomously, constantly optimizes its status and adapts itself to the changing conditions. This research proposes a new autonomic framework based on multi-agent paradigm for autonomous network management. In this study, we particularly focused on monitoring node activities and software deployment, the aims were 1) to minimize the human interaction required to perform these tasks which optimizes the task processing time and reduces human resource requirement, and 2) to overcome some of the major problems (such as autonomous monitoring, autonomous installation for any type/kind of software, etc) related to these tasks. The proposed framework is fully autonomous, has an effective mechanism for achieving the said tasks and is based on Layered architecture. Once initialized with given rules / domain knowledge, it accomplishes the task(s) autonomously without human interaction / intervention. It uses mobile agents for task execution and fault / failure can affect the performance of the system; therefore, to make the system robust fault tolerance mechanism is incorporated at different levels of the system. The framework is implemented in Java using Java Agent Development (JADE) framework and supports platform independence; however, it has been tested and evaluated only on Microsoft Windows environment. In this research, the major challenges faced were 1) capturing unknown malicious applications running over the network, 2) development of generic approach which works for any type / kind of software set, 3) automatic generation of events required in software deployment process and 4) development of efficient approach for application setup transfer over network. The first challenge was related to monitoring node activities which was catered by analyzing the application content (i.e. text, image and video) using text analysis / image processing algorithms. Domain specific ontology was developed and populated using known malicious applications content for categorization purpose. The concepts extracted using the content analysis phase were mapped to domain specific ontology concepts and assigned score. The application was assigned the ontology class (if any) which has the highest score. The other challenges were related to software deployment which were catered by lunching application setup autonomously and for each step, window content (i.e. text, controls) were extracted, filtered using text processing algorithm and classified using rule based classifier. After classification, the appropriate window event was generated autonomously. The reason of using rule based classifier was that software deployment process is standardized and every installer follows the same standard. Furthermore, exponential file transfer algorithm was incorporated in the framework to transfer the application setup smartly and efficiently over the network. We have run this system on experimental basis at the university campus having seven labs equipped with 20-300 number of PCs running Microsoft Windows (any version) in various labs. For automated node monitoring evaluation, initially one hundred volunteers were selected for experimentation in these labs and all of them were told about the system. After initial experimentation, we announced about the system on the university blackboard, walls/doors of the labs etc and open the labs for all users. The announcement clearly states that "Your activities will be monitored and the collected data will be used only for educational/research purpose". The activities were monitored for one month and the monitored data was stored in database for analysis. For Software Deployment evaluation some of the popular softwares (such as Microsoft Office, Adobe Reader, FireFox etc) were deployed. The proposed framework has been tested on different scenarios and results prove that the overall performance of the proposed approach in terms of efficiency and time is far better than existing approaches / frameworks.
|Item Type:||Thesis (PhD)|
|Schools:||Schools > School of Computing, Science and Engineering|
|Depositing User:||Institutional Repository|
|Date Deposited:||03 Oct 2012 13:34|
|Last Modified:||28 Jun 2016 11:08|
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