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Energy consumption has attracted a lot of attention in the past few years, because energy reduction causes a significant mitigation of the negative impact on the environment along with an operational cost reduction. Energy-efficient task scheduling is an effective technique to decrease the energy consumption in the Cloud Computing Systems (CCSs). In this paper, the problem of scheduling a set of precedence-constrained...
Energy efficiency is becoming an increasingly important factor to consider in day-to-day operations, and the Information, Communication and Technology (ICT) arena is no exception. The energy consumption in the ICT sector is increasing at a rate that deems energy consumption a possible limitation to the continuous fast growth of the future Internet. We address this limitation in two ways. (1) We propose...
Increasing energy consumption in server consolidation environments leads to high maintenance costs for data centers. Main memory, no less than processor, is a major energy consumer in this environment. This paper proposes a technique for reducing memory energy consumption using virtual machine scheduling in multicore systems. We devise several heuristic scheduling algorithms by using a memory power...
In order to develop a data center power efficiency index, we built a test bed of a data center and measured power components and environmental variables in some detail, including the power consumption and temperature of each node, rack and air conditioning unit, as well as load on the CPU, Disk I/O and the network. In these measurements we found that there was a significant imbalance of CPU temperatures...
Currently, a large number of cloud computing servers waste a tremendous amount of energy and emit a considerable amount of carbon dioxide. Thus, it is necessary to significantly reduce pollution and substantially lower energy usage. This paper seeks to implement six innovative green task scheduling algorithms that have two main steps: assigning as many tasks as possible to a cloud server with lowest...
The recent emergence of clouds with large, virtualized pools of compute and storage resources raises the possibility of a new compute paradigm for scientific research. With virtualization technologies, consolidation of scientific workflows presents a promising opportunity for energy and resource cost optimization, while achieving high performance. We have developed pSciMapper, a power-aware consolidation...
The reduction of energy consumption in large-scale datacenters is being accomplished through an extensive use of virtualization, which enables the consolidation of multiple workloads in a smaller number of machines. Nevertheless, virtualization also incurs some additional overheads (e.g. virtual machine creation and migration) that can influence what is the best consolidated configuration, and thus,...
Virtualization has become a very important technology which has been adopted in many enterprise computing systems and data centers. Virtualization makes resource management and maintenance easier, and can decrease energy consumption through resource consolidation. To develop and employ sophisticated resource management, accurate power and performance models of the hardware resources in a virtualized...
Apache Hadoop is a framework for managing large scale storage based datacenters whose primary job is to deliver data to clients. In such systems, the primary job is to associate each data request to a specific data replica among many available replicas. This assignment impacts the workload and power distribution across the storage servers. In this paper, we explore thermal and power aware task scheduling...
Dynamic cluster configuration is dynamically adjusting the servers scale based on the network load in order to achieve optimal service performance under the minimum system power consumption. In previous methods, they adopted adjustment methods based on the specific physical experimental model without the description of mathematical models. This paper presents a prediction-based dynamic clusters configuration...
With the increasing prevalence of large scale cloud computing environments, how to place requested applications into available computing servers regarding to energy consumption has become an essential research problem, but existing application placement approaches are still not effective for live applications with dynamic characters. In this paper, we proposed a novel approach named EnaCloud, which...
In this paper, we are interested by the integration of precedence and resources sharing constraints in the real time scheduling of periodic and aperiodic tasks. We also treat the problem of dynamic voltage scaling of the processor in the same context. Many dynamic voltage scaling algorithms have been proposed in the literature. However, these algorithms do not consider the constraints of precedence...
Energy consumption and timely requirements are two key factors affecting the performance of mission-critical cyber-physical systems. Little work deals with scheduling a set of time-sensitive services in a finite time interval. We consider a server serving N users in time interval [0, T]. Each user demands its service to be completed in a strict deadline. Based on convex power-speed relationship, a...
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