Muhammad Abdullah Adnan

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With the increasing popularity of Cloud computing and Mobile computing, individuals, enterprises and research centers have started outsourcing their IT and computational needs to on-demand cloud services. Recently geographical load balancing techniques have been suggested for data centers hosting cloud computation in order to reduce energy cost by(More)
This paper explores the opportunity for energy saving in data centers using the flexibility from the Service Level Agreements (SLAs) and proposes a novel approach for scheduling workload that incorporates use of renewable energy sources. We investigate how much renewable power to store and how much workload to delay for increasing renewable usage while(More)
Data center topologies typically consist of multirooted trees with many equal-cost paths between a given pair of hosts. Existing power optimization techniques do not utilize this property of data center networks for power proportionality. In this paper, we exploit this opportunity and show that significant energy savings can be achieved via path(More)
This paper explores the opportunity for energy cost saving in data centers that utilizes the flexibility from the Service Level Agreements (SLAs) and proposes a novel approach for capacity provisioning under bounded latency requirements of the workload. We investigate how many servers to keep active and how much workload to delay for energy saving while(More)
Recent increase in energy prices has led researchers to find better ways for capacity provisioning in data centers to reduce energy wastage due to the variation in workload. This paper explores the opportunity for cost saving and proposes a novel approach for capacity provisioning under bounded latency requirements for the workload. We investigate how many(More)
Distributed computing resources in a cloud computing environment provides an opportunity to reduce energy and its cost by shifting loads in response to dynamically varying availability of energy. This variation in electrical power availability is represented in its dynamically changing price that can be used to drive workload deferral against performance(More)
In this paper we give an algorithm to generate all distributions of distinguishable objects to bins without repetition. Our algorithm generates each distribution in constant time. To the best of our knowledge, our algorithm is the first algorithm which generates each solution in O(1) time in ordinary sense. As a byproduct of our algorithm, we get a new(More)
Utilities face complex problems of peak demand and intermittent supply, made more pressing by the need to integrate large EV loads and distributed generation. The added flexibility of EV loads, which can charge at varying rates, together with forecasts of renewable availability can be used to reduce integration costs. We show that, in addition, the(More)