Title :
OpenStack Café: A Novel Time-Based User-centric Resource Management Framework in the Cloud
Author :
Tan, Alan Y. S. ; Ko, Ryan K. L. ; Ng, Grace P. Y.
Author_Institution :
Dept. of Comput. Sci., Univ. of Waikato, Hamilton, New Zealand
fDate :
June 27 2014-July 2 2014
Abstract :
Mechanisms used by many current state of the art cloud frameworks for managing users\´ access to cloud resources adopt an "authenticate-and-forget" approach, users with a valid account can access and use cloud resources for an indefinite amount of time. This arrangement introduces problems such as resource hogging in resource limited cloud setups (e.g. private clouds). Café is a novel time-based user-centric framework for managing resource usage. Café uses a timeslot approach to manage users\´ access to cloud resources. Café features: an interface for users to request time-slots to access cloud resources at specific times and manage their bookings, automatic management of user access rights, automatic releasing of used cloud resources back into the common resource pool. Through these features, Café can help administrators manage large groups of users with different requirements efficiently. More importantly, Café addresses issues such as resource hogging, thereby increasing the utilisation rate of cloud resources in resource limited cloud setups.
Keywords :
authorisation; cloud computing; public domain software; resource allocation; user interfaces; OpenStack Café; authenticate-and-forget approach; automatic used cloud resource release; automatic user access rights management; booking management; cloud frameworks; cloud resource utilisation rate; private clouds; resource hogging; resource hogging problem; resource limited cloud setups; resource usage management; time-based user-centric framework; time-based user-centric resource management framework; time-slot approach; time-slot request; user cloud resource access management; user interface; Access control; Cloud computing; Clouds; Electronic mail; Monitoring; Resource management; Virtual machining; Cloud computing; resource management; user access management;
Conference_Titel :
Big Data (BigData Congress), 2014 IEEE International Congress on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4799-5056-0
DOI :
10.1109/BigData.Congress.2014.68