An intelligent fault tolerant multi-agent framework for automated node monitoring and software deployment

Manzoor, U

Abstract

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.

Citation

Manzoor, U. An intelligent fault tolerant multi-agent framework for automated node monitoring and software deployment. (Thesis). Salford : University of Salford

• Thesis Type: Thesis
• Deposit Date: Oct 3, 2012
• Award Date: Jan 1, 2011