bhargav teja | Texas A&M University - Kingsville (original) (raw)
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Papers by bhargav teja
Energy efficiency is increasingly important for future information and communication technologies... more Energy efficiency is increasingly important for future information and communication technologies, because the increased usage of ICT, together with increasing energy costs and the need to reduce greenhouse gas emissions call for energy-efficient technologies that decrease the overall energy consumption of computation, storage and communications. Cloud computing has recently received considerable attention, as a promising approach for delivering ICT services by improving the utilization of data centre resources. The implementation of cloud computing has attracted computing as a utility and enables penetrative applications from scientific, consumer and business domains. However, this implementation faces energy, power and associated cost concerns. We investigate energy consumption patterns. Specifically, we make use of measurable metrics based on runtime tasks to compare rationally the relation existing between energy consumption and cloud workload and computational tasks, as well as system performance.
Energy efficiency is increasingly important for future information and communication technologies... more Energy efficiency is increasingly important for future information and communication technologies, because the increased usage of ICT, together with increasing energy costs and the need to reduce greenhouse gas emissions call for energy-efficient technologies that decrease the overall energy consumption of computation, storage and communications. Cloud computing has recently received considerable attention, as a promising approach for delivering ICT services by improving the utilization of data centre resources. The implementation of cloud computing has attracted computing as a utility and enables penetrative applications from scientific, consumer and business domains. However, this implementation faces energy, power and associated cost concerns. We investigate energy consumption patterns. Specifically, we make use of measurable metrics based on runtime tasks to compare rationally the relation existing between energy consumption and cloud workload and computational tasks, as well as system performance.