Analysis of Control-theoretic Predictive Strategies for the Adaptation of Distributed Parallel Computations

In adaptive distributed parallel applications the adaptation process is based on the ability to change some characteristics of parallel components, such as the parallelism form and the parallelism degree, in response to unexpected execution conditions. Although existing research work has studied this problem, it is of increasing importance to investigate adaptation strategies able to reach important properties like the stability of control decisions, i.e. to guarantee that recon- gurations are eective and durable, and control optimality, expressed by means of cooperative and non-cooperative agreements between decisions of dierent controllers. These properties are crucial in distributed environments like Grids and Clouds, where recongurations imply a cost both in terms of a performance degradation as well as a monetary charge. In this paper we brie y introduce the basic ideas of our methodology and we introduce dierent adaptation strategies based on alternative formulations of the Modelbased Predictive Control technique. First hints about the eectiveness of our approach are discussed through experiments developed in a simulation environment.