Reliability Management Framework and Recommender System for Hyper-converged Infrastructured Data Centers

Author(s):  
Ayesha Nasir ◽  
Tahir Alyas ◽  
Muhammad Asif ◽  
Muhammad Naeem Akhtar
1995 ◽  
Vol 7 (5) ◽  
pp. 7-15 ◽  
Author(s):  
Charles Tennant

Rover Group is the UK’s largest automotive manufacturer employing 35,000 people which designs, develops and manufactures vehicles in the small, medium, executive and specialist four‐wheel‐drive sectors. Describes the processes deployed at Rover to ensure that quality and reliability are designed into the product through the new product introduction process, in order to achieve the company quality strategy milestones. The quality and reliability processes have been developed as a project management framework, known internally as “common business environment”. Describes the product programme milestone philosophy and supporting processes such as design methodology, reliability management, cost management and programme timing synthetics. The processes are deployed into all project teams at Rover Group through a learning methodology called focused learning. Measurement of common business environment implementation is carried out at project Q&R reviews, which are based on the European Foundation for Quality Management self‐assessment criteria.


2013 ◽  
Vol 373-375 ◽  
pp. 1202-1207
Author(s):  
Quan Feng Yan ◽  
Yue Bin Wang ◽  
Zi Hua Qiu ◽  
Xu Huai Hu

In this paper, we propose a context-awareness based personalized recommender system in the pervasive application space. The recommender system comprises the personalized recommender engine and the distributed context management framework. With a hybrid approach, the personalized recommender engine combines those contexts into the decisions on recommendations to get more comprehensive recommendation effectiveness. In contrast with existing middleware of context-awareness, the recommender system has an ability of user-centric recommendation. At the end of this paper, an emphasis is put on the metrics of the effectiveness of the recommender system.


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