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Nowadays enormous amounts of energy are consumed by Cloud infrastructures and this trend is still growing. An existing solution to lower this consumption is to turn off as many servers as possible, but these solutions do not involve the user as a main lever to save energy. We introduce a system that proposes to the user to run her application with degraded performance. A user choosing an energy-efficient...
Energy consumption is very important to cloud data centers, as it takes a large quotient of the operation cost much related to the environment. To decrease the energy consumption in cloud data center, one possible solution is processing different types of applications in clouds with different strategies. However, to reach this goal, the prime question to be solved is how to effectively classify the...
This paper proposes a context-aware energy-saving efforts estimation method that is based on Bluetooth Low Energy beacons (BLE), PC agent, and mobile app. It is important to be properly rewarded for the individual effort to reduce energy consumption, particularly in the office environment. Hence, the intelligent method that makes it possible to perceive and differentiate the energy-saving efforts...
The increasing demand for highly sophisticated cloud services and the consequent worldwide increase in the number of data centers (DC), make the need for energy efficient operation of DCs more actual than ever. Additionally, in the context of smart city and smart grid integration, flexible DCs can play a key role toward acting as grid-stabilization factors. In this paper, a review of the available...
In this paper we consider how energy efficiency aspects can be added to Openstack. With the objective of devising an energy efficient resource manager for Openstack, we first analyze resource and energy utilization on our cloud resources. We observe that there is a large fixed cost associated with server usage patterns and powering down servers is necessary to achieve energy savings. Following this...
An increasing number of modern smartphone applications are dependent on information updates from the cloud. To realize such information updates mainly two communication approaches are common, namely push- and pull. Due to different communication patterns both approaches differ in their energy consumption and notification latency. The energy constrained nature of mobile devices entails a sensible selection...
As a key enabler of Internet of things, cellular network based Machine-to-Machine (M2M) communications have been growing rapidly in recent years, being used in a wide range of services such as security, metering, health, remote control, tracking, and so on. A critical issue in M2M communications is the energy efficiency as typically the machine devices are powered by batteries of low capacity and...
We consider the decision engine of mobile cloud offloading systems, which decides whether to offload a given method to the cloud servers. We design, implement, and evaluate a context-aware decision algorithm, called CADA, to optimize the performance of the mobile devices with various optimization criteria, including short response time and low energy consumption. The CADA algorithm can work with various...
In this paper we approach the high energy consumption problem of large virtualized service centers by proposing a dynamic server consolidation methodology for optimizing the service center IT computing resources usage. The consolidation methodology is based on logically structuring the service center servers hierarchical clusters, consolidation decisions being taken in each cluster using a reinforcement...
Ubiquitous systems are generally embedded into the environment and provide their services all the time and everywhere. In order to increase transparency and personalization, ubiquitous applications are normally context-aware, i.e., they use information about entities of interest to adapt their services. Since they are connected to everyday elements, such systems are frequently shared by two or more...
This paper addresses the problem of run-time management of a service center energy efficiency by using a context aware self-adapting algorithm. The algorithm adapts the service center energy consumption to the incoming workload by considering service center predefined Green Performance Indicators (GPI) and Key Performance Indicators (KPI). The service center energy performance context is obtained...
This paper deals with the reduction of energy consumption in large scale systems, especially by taking into account the impact of energy consumption for server consolidation. Decreasing the number of physical hosts used while ensuring a certain level of quality of services is the goal of our approach. We introduce a metric called energetic yield which represents the quality of a task placement on...
As functionalities required by embedded systems increase, higher levels of abstraction become necessary to fulfill development exigencies. At the same time, traditional physical and economical constraints such as size, memory usage and energy consumption subsist, making embedded systems development even more complex as it must face two contradictory requirements. In this paper, we expose how a component-based...
One of the indispensable functions of network operation is to provide stabile network performance under all conditions, even when failures occur. To make such this function a reality, the network operation system should bring all relevant equipment and traffic under its control. The operation system must be able to provide conscientious support for each customer by monitoring network status as well...
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