The energy costs constitute a significant portion of the total cost of cloud providers. The major cloud data centers are often geographically distributed, and this brings an opportunity to minimize their energy cost. In this work, we model a geographically distributed data center network that is specialized to run batch jobs. Taking into account the spatio-temporal variation in the electricity ...

Grid computing, emerging as a new paradigm for next-generation computing, enables the sharing, selection, and aggregation of geographically distributed heterogeneous resources for solving large-scale problems in science, engineering, and commerce. The resources in the Grid are heterogeneous and geographically distributed. The paper demonstrates the capability of economicbased systems for wide-a...

The selection of appropriate requirements for product releases can make a big difference in a product success. The selection of requirements is done by different requirements prioritization techniques. These techniques are based on pre-defined and systematic steps to calculate the requirements relative weight. Prioritization is complicated by new development settings, shifting from traditional ...

Historically, builders of CSCW tools have not focused on the creation of trust among users as a critical design goal. Yet, high levels of trust produce a number of benefits, including reduced coordination and communication costs. These benefits are particularly salient and desirable for geographically distributed workers. Therefore, to the extent that support for geographically distributed work...

Today a large number of scientific and commercial applications often require to analyse large data sets maintained over geographically distributed sites by using the computational power of distributed high-performance environments. Advances in networking technology and computational infrastructure made it possible to construct large-scale distributed computing platforms, called computational gr...

The development of many complex simulation applications requires collaborative effort from researchers with different domain knowledge and expertise, possibly at different locations. These simulation systems often require huge computing resources and data sets, which may be geographically distributed. In order to support collaborative model development and to cater for the increasing complexity...