Power and energy efficiency are now critical concerns in extreme-scale high-performance
scientific computing. Many extreme-scale computing systems today (for example: Top500) …

Software-intensive systems in most domains, from autonomous vehicles to health, are
becoming predominantly parallel to efficiently manage large amount of data in short (even …

The modern day advancement is increasingly digitizing our lives which has led to a rapid
growth of data. Such multidimensional datasets are precious due to the potential of …

Big data entails massive cloud resources for data processing and analysis, which consumes
more energy to run. The resources and tasks are increasing exponentially in the cloud …

The problem of energy consumption in the cloud related environments has attracted a great
deal of attention in research and industry communities. In the past ten years, a large number …

The massive amount of data generated in projects focused on smart cities creates a degree
of complexity in how to manage all this information. In attention to solve this problem, several …

Energy proportionality is the key design goal followed by architects of multicore processors.
One of its implications is that optimization of an application for performance will also …

Several Job scheduling algorithms have been developed for Hadoop-MapReduce model,
which vary widely in design and behavior for handling different issues such as locality of …

The spread of projects focused on smart cities have grown in recent years. With this, the
massive amount of data generated in these initiatives, creates a degree of complexity in how …

During the past ten years, the energy consumption problem in cloud-related environments
has attracted substantial attention in research and industrial communities. Researchers …