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Electricity consumption for cooling purpose is known to be the most expensive operational cost factor in data centers. Inefficient cooling leads to high temperature and this in turn leads to hardware failure. This paper proposes a Thermal Aware Modified Least Slack Time Round Robin Based (MLST-RR) scheduling algorithm that can avoid high thermal stress circumstances such as large hotspots, thermal...
Over the decades people have seen a change from large mainframe computing to commodity, off-the-shelf clusters of high performance computers. Currently data centers have thousands or tens of thousands of high performance computers that provides services as well as computation for tens or hundreds of thousands of users. Traditional IT challenges such as scheduling, resource allocation and now data...
Electricity consumption typically forms the biggest portion of a Data Centre's operational cost, with the biggest consumers, in roughly equal proportion, being the servers and the cooling units. In an effort to reduce electricity consumption, in this paper, we propose a grid scheduling algorithm that takes advantage of a prior Gas-District Cooling Data Centre model to reduce the cooling energy consumption...
In recent years, increasing demand for computing has led to the development of computational grid. Typically scheduling challenges tend to be NP-hard problems where there is no optimal solution. The research reported here therefore is focused on the development of hybrids scheduling algorithms based on deadline and slack time parameters and its variations, using the concept of optimization techniques...
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