Cloud Computing
Meituan Bench (MTB) is an enterprise-level benchmarking tool designed for time-series forecasting in real-world business scenarios. Built upon an open-source dataset derived from 10,000 real-world services across various business units, MTB provides a standardized evaluation framework for time-series prediction models. The dataset includes 200 representative services, capturing diverse traffic patterns essential for assessing forecasting performance.
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Shoviv Software started its journey in 2017 and has become a top organization that offers reliable solutions worldwide. It covers almost all kinds of solutions for email clients and cloud-based platforms. The main aim of Shoviv Software is to provide easy ways to backup, migrate, recover, password remover and perform other tasks for various platforms. It is known for its simple tools with advanced features, making tasks easier.
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DataVare Software is the well-known brand in the software industry for a number of software services, like Email conversion, Email Migration, Cloud Backup, Exchange Migration, PDF Management, Outlook files management, Address book Manager and many more. We have highly skilled developers who design the software very well with easy and simple users interface. So all kinds of users can operate it very well whether they have technical knowledge or not. Even free demo versions also offered to all users to use this software before buying it full license versions.
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Performance models identified at run-time can be used by self-adaptive software systems to execute decisions on a cloud environment. These performance models are built by measuring the control inputs, disturbances, and outputs of the controlled system. These models have been shown to accurately interpolate for data already seen by the model identification method. However, automation in cloud operations can push the environment into operational regions the system has not seen, thus the performance model may not accurately extrapolate into unseen regions.
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Due to climate change, the Northwesterner Gilgit Baltistan's, Ghizer district is highly susceptible to glacial lake outburst floods (GLOFs). Nearly 24 GLOFs have occurred in this area in the last ∼200 years, demonstrating the growing recurrent nature of these incidents. Taking this into account, the assessment of risks associated with GLOFs was investigated in this study. All regional glacial lakes were identified in the first phase, and changes between 2000 and 2023 were mapped using moderate-resolution satellite images (Landsat).
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The JU-Impact Radiomap Dataset is a comprehensive dataset designed for research and development in indoor positioning systems. It comprises 5431 instances characterized by readings from 105 static Wi-Fi Access Points (APs) and spans 152 distinct virtual grids. Each virtual grid represents a 1x1 square meter area, derived by dividing a physical floor of a university building into reference coordinate points (x, y). The dataset was collected over a period of 21 days using four mobile devices: Samsung Galaxy Tab, Moto G, Redmi Note 4, and Google Pixel.
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The benchmarking dataset, GenAI on the Edge, contains performance metrics from evaluating Large Language Models (LLMs) on edge devices, utilizing a distributed testbed of Raspberry Pi devices orchestrated by Kubernetes (K3s). It includes performance data collected from multiple runs of prompt-based evaluations with various LLMs, leveraging Prometheus and the Llama.cpp framework. The dataset captures key metrics such as resource utilization, token generation rates/throughput, and detailed inference timing for stages such as Sample, Prefill, and Decode.
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Internet telephony consists of a combination of hardware and software that enables you to
use the Internet as the transmission medium for telephone calls. For users who have free,
or fixed-price Internet access, Internet telephony software essentially provides free
telephone calls anywhere in the world. In its simplest form, PC-to-PC Internet telephony
can be as easy as hooking up a microphone to your computer and sending your voice
through a cable modem to a person who has Internet telephony software that is
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The Multi-Server Multi-User computation offloading (MSCO) dataset is a dataset based on the scenario of multi-server multi-user binary computing offloading. It is characterized by the connection status between users and edge servers, user task information, and server computational resource information. The solution aims to minimize the total cost of power consumption and latency of all tasks. The labels are the offloading decisions of user tasks and the computational resource allocation of edge servers. The features and labels of this dataset are graph-structured.
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This dataset results from a 5-month-long Cloud Telescope Internet Background Radiation collection experiment conducted during the months of October 2023 until February 2024.
A total amount of 130 EC2 instances (sensors) were deployed across all the 26 commercially available AWS regions at the time, 5 sensors per region.
A Cloud Telescope sensor does not serve information. All traffic arriving to the sensor is unsolicited, and potentially malicious. Sensors were configured to allow all unsolicited traffic.
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