SEFeb 11, 2018

An Investigation of the Monitoring Activity in Self Adaptive Systems

arXiv:1802.03667v11 citations
Originality Synthesis-oriented
AI Analysis

This work addresses monitoring challenges in self-adaptive systems, but it is incremental as it builds on existing MAPE-K concepts without introducing major new methods.

The paper investigates the monitoring activity in self-adaptive systems using the MAPE-K control loop, exploring its architecture, interfaces, adaptive aspects, and modes, and presents a Java framework for the monitoring process.

Runtime monitoring is essential for the violation detection during the underlying software system execution. In this paper, an investigation of the monitoring activity of MAPE-K control loop is performed which aims at exploring:(1) the architecture of the monitoring activity in terms of the involved components and control and data flow between them; (2) the standard interface of the monitoring component with other MAPE-K components; (3) the adaptive monitoring and its importance to the monitoring overhead issue; and (4) the monitoring mode and its relevance to some specific situations and systems. This paper also presented a Java framework for the monitoring process for self adaptive systems.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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