Adaptive Mechanisms for Large Scale Software Systems

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This project investigates adaptive mechanisms for large-scale software systems. It focuses on models, algorithms and architectures that allow large scale software systems to respond autonomously to changes in environment and user requirements. As cloud computing services mature and proliferate, an open research question is how to manage large scale software systems deployed to distributed clouds, where multiple clouds are distributed on the basis of geography, data privacy, latency, or other dimensions. Adaptive software systems are emerging as a new research and practice area in software systems engineering with the goal of making software more versatile, robust, continuously available and self-managing.First, using various combinations of distributed cloud systems requires an adaptive system that is both integrated and distributed. We will explore arranging feedback loops, the basic building blocks of adaptive systems, in hierarchical patterns to optimize both local clouds at the low level and globally at a higher level. We will examine how the loops interact and converge to a global solution, and determine how best to specify the desired global solution. Second, adaptive systems can function in multiple modes depending on the system conditions, the workload, and the operating environment. This objective addresses the question of how to model these multiple modes, and in particular what models, loops, and control algorithms are required. Third, to improve the quality of decisions and the speed of implementation, we will experiment with superimposing two feedback loops, one to respond to long term trends in the application and another to address short term needs. Accurate trend prediction and division of labor to avoid repeated thrashing and conflict between short and long term goals will be required. This important work in adaptive systems enables the next generation of cloud computing, in particular the automation of complex systems to decrease costs, increase energy efficiency, and improve the quality of service. These contributions will advance the state of the art in an area of practical application that is of great interest to Canadian industry, researchers, and citizens.