SLA based profit optimization in autonomic computing systems

Author(s):  
Li Zhang ◽  
Danilo Ardagna
2005 ◽  
Vol 19 (3) ◽  
pp. 213-221 ◽  
Author(s):  
Rob Barrett ◽  
Paul P. Maglio ◽  
Eser Kandogan ◽  
John Bailey

2006 ◽  
Vol 21 (3) ◽  
pp. 195-204 ◽  
Author(s):  
ROY STERRITT ◽  
DAVE BUSTARD

Like the autonomic responses in the human body, autonomic computing systems recognize their own health problems and, where possible, respond to correct them. Failing that, external help is required. The purpose of this paper is to consider how autonomic systems might be structured to facilitate health monitoring. The approach uses a ‘pulse’ monitor for each autonomic element, which provides a reflex reaction facility and basic information on the current state (health) of that element. The pulse mechanism extends the NASA beacon monitor concept. The different ways that pulse information might be communicated and used are examined. The discussion is illustrated with a personal computing example.


Author(s):  
RAVI KUMAR G ◽  
C. MUTHUSAMY ◽  
A.VINAYA BABU

High performance is always a desired objective in computing systems. Managing performance through manual intervention is a well-known and obvious mechanism. The attempts to self-manage performance with minimal human intervention are predominant in the recent advances of research. Control Systems theory is playing a significant role in building such intelligent and autonomic computing systems. We are investigating in building Intelligent Application Servers by enabling control system as a first class feature in component software, at design time and runtime. In this direction, it is important to build efficient data access mechanisms that capture the control system models, performance data, analyze the data efficiently, identify patterns and build a knowledge base. In this paper we propose a data organization and architecture as a building block of developing Intelligent Application Servers.


Computers ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 22
Author(s):  
Christian Krupitzer ◽  
Benedikt Eberhardinger ◽  
Ilias Gerostathopoulos ◽  
Claudia Raibulet

The joint 1st Workshop on Evaluations and Measurements in Self-Aware Computing Systems (EMSAC 2019) and Workshop on Self-Aware Computing (SeAC) was held as part of the FAS* conference alliance in conjunction with the 16th IEEE International Conference on Autonomic Computing (ICAC) and the 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO) in Umeå, Sweden on 20 June 2019. The goal of this one-day workshop was to bring together researchers and practitioners from academic environments and from the industry to share their solutions, ideas, visions, and doubts in self-aware computing systems in general and in the evaluation and measurements of such systems in particular. The workshop aimed to enable discussions, partnerships, and collaborations among the participants. This special issue follows the theme of the workshop. It contains extended versions of workshop presentations as well as additional contributions.


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