Generic event-based monitoring and adaptation methodology for heterogeneous distributed systems

The Cloud computing paradigm provides the basis for a class of platforms and applications that face novel challenges related to multi-tenancy, adaptivity, and elasticity. To account for service delivery guarantees in the face of ever increasing levels of heterogeneity, scale and dynamism, service provisioning in the Cloud has raised the demand for systematic and flexible approaches to monitoring and adaptation of applications. In this paper, we tackle this issue and present a framework for efficient runtime management of Cloud environments, and distributed heterogeneous systems in general. A novel domain-specific language (DSL) termed MONINA is introduced that allows to define integrated monitoring and adaptation functionality for controlling such systems. We propose a mechanism for optimal deployment of the defined control operators onto available computing resources. Deployment is based on solving a quadratic programming problem, which aims at achieving minimized reaction times, low overhead, as well as scalable monitoring and adaptation. The monitoring infrastructure is based on a distributed messaging middleware, providing high level of decoupling and allowing new monitoring nodes to join the system dynamically. We provide a detailed formalization of the problem domain, discuss architectural details, highlight the implementation of the developed prototype, and put our work into perspective with existing work in the field