On estimating actuation delays in elastic computing systems

Abstract

Abstract-Elastic controllers autonomically adjust the allocation of resources in cloud computing systems. Usually such controllers assume that control actions will take immediate effect. In clouds, however, actuation times may be long, and the controllers can hardly guarantee acceptable levels of service if they neglect these actuation delays. Therefore, the ability to correctly estimate the time that control actions take effect on the systems is crucial. However, detecting actuation delays in elastic computing systems is challenging because cloud systems provide only inaccurate and incomplete data about reconfigurations timing.In this paper, we tackle the problem of estimating the delay of control actions in elastic systems. We identify recurring types of changes in the monitored metrics and requirements to properly carry out the estimation. Based on that, we develop a novel framework for the actuation delays estimation that utilizes change point detection techniques. We conduct several experiments with real-world systems to illustrate the feasibility and applicability of our framework.

How do we Evaluate Self-adaptive Software Systems? [replication package]

“…Among these, 11 studies targeted a planning method and ten studies targeted an analysis method. Only one study targeted a new monitoring approach [42] and one other study targeted an execution approach [23]. Independently of the evaluation targets, 79 of all 140 experiments (56%) reported in the primary studies used the full feedback loop, while 61 experiments (44%) considered only a part of the feedback loop in the evaluation.…”

“…Not surprisingly, learning ability is the top evaluation objective for new learning methods (in 31 experiments). Scalability is used as evaluation criterion for four of the six evaluation targets (not for the single new proposed execution [23] and monitoring methods [42]).…”