The field of Cloud Computing is relatively new branch of Information Technology in which various services are devolved from a centralised local location to a de-centralized remote Intranet/Internet environment. It has recently experienced rapid growth and acceptance with academia and industry, presenting new challenges worthy of fundamental research. Some of the largest challenges today revolve around achieving higher levels of sustainability and infrastructure performance. This work investigates an optimised and novel approach to an Autonomous Virtual Server Management System in a ‘Cloud Computing’ environment through designing and building an Autonomous Management Distributed System (AMDS). The AMDS helps reduce hardware power consumption through autonomously moving virtual servers around a network to balance out hardware loads, as well as being easily configurable and extendable, made possible by its software infrastructure. Through use of an internally configured Cloud Computing test -bed rig, the AMDS makes use of several physically and logically defined networks to communicate with all devices that are a part of the cloud infrastructure. Once connected, the AMDS monitors these devices and issues optimisation commands accordingly. Experimental results show an overall power consumption reduction of up to 8%, which in a typical datacentre of several thousand servers translates into a significant cost reduction. This work also presents an initial design, along with proof-of-concept implementation as an AMDS module, of a Botnet heuristic detection algorithm. Experimental results show an overall malicious data packet detection rate of 52%, a significant figure for only 5000 data samples analysed by the module. Another strength is that this design allows an abstract software model to be constructed, which can then be implemented using a multitude of programming languages. This research shows how the carbon footprint of a Cloud Computing datacentre can be reduced and reveals a significant impact on issues of sustainability with respect to both energy efficiency and economic viability. It also shows how datacentre security can be enhanced by detecting Botnet activity and preventing the disruption of day-to-day operations through a highly scalable, flexible, and autonomous software implementation.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:723265 |
| Date | January 2015 |
| Creators | Dinita, Razvan-Ioan |
| Publisher | Anglia Ruskin University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://arro.anglia.ac.uk/702122/ |
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