Related papers: WattsApp: Power-Aware Container Scheduling
The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important…
Although cloud computing has been transformational to the IT industry, it is built on large data centres that often consume massive amounts of electrical power. Efforts have been made to reduce the energy clouds consume, with certain data…
Power packets are proposed as a transmission unit that can deliver power and information simultaneously. They are transferred using the store-and-forward method of power routers. A system that achieves power supply/demand in this manner is…
The energy consumption of computer and communication systems does not scale linearly with the workload. A system uses a significant amount of energy even when idle or lightly loaded. A widely reported solution to resource management in…
The planning and operation of renewable energy, especially wind power, depend crucially on accurate, timely, and high-resolution weather information. Coarse-grid global numerical weather forecasts are typically downscaled to meet these…
Distributed multi-controller deployment is a promising method to achieve a scalable and reliable control plane of Software-Defined Networking (SDN). However, it brings a new challenge for balancing loads on the distributed controllers as…
The energy consumption issue in distributed computing systems has become quite critical due to environmental concerns. In response to this, many energy-aware scheduling algorithms have been developed primarily by using the dynamic…
Classical list scheduling is a very popular and efficient technique for scheduling jobs in parallel and distributed platforms. It is inherently centralized. However, with the increasing number of processors, the cost for managing a single…
High-performance computing (HPC) systems and cloud data centers are converging, and containers are becoming the default method of portable software deployment. Yet, while containers simplify software management, they face significant…
The convergence of IoT, Edge, Cloud, and HPC technologies creates a compute continuum that merges cloud scalability and flexibility with HPC's computational power and specialized optimizations. However, integrating cloud and HPC resources…
Short-term load forecasting is of paramount importance in the efficient operation and planning of power systems, given its inherent non-linear and dynamic nature. Recent strides in deep learning have shown promise in addressing this…
Advances in cloud computing have simplified the way that both software development and testing are performed. This is not true for battery testing for which state of the art test-beds simply consist of one phone attached to a power meter.…
This paper presents a closed-loop controller for wind farms to provide active power control services using a high-fidelity computational fluid dynamics based wind plant simulator. The proposed design enhances power tracking stability and…
Residential and commercial buildings, equipped with systems such as heat pumps (HPs), hot water tanks, or stationary energy storage, have a large potential to offer their consumption flexibility as grid services. In this work, we leverage…
Energy consumption represents a significant cost in data center operation. A large fraction of the energy, however, is used to power idle servers when the workload is low. Dynamic provisioning techniques aim at saving this portion of the…
Kubernetes has been for a number of years the default cloud orchestrator solution across multiple application and research domains. As such, optimizing the energy efficiency of Kubernetes-deployed workloads is of primary interest towards…
Energy consumption is a growing issue in data centers, impacting their economic viability and their public image. In this work we empirically characterize the power and energy consumed by different types of servers. In particular, in order…
In business process landscapes, a common challenge is to provide the necessary computational resources to enact the single process steps. One well-known approach to solve this issue in a cost-efficient way is to use the notion of…
In the context of GreenPAD project it is important to predict the energy consumption of individual (and mixture of) VMs / workload for optimal scheduling (running those VMs which require higher energy when there is more green energy…
Cloud service providers are distributing data centers geographically to minimize energy costs through intelligent workload distribution. With increasing data volumes in emerging cloud workloads, it is critical to factor in the network costs…