Power Consumption and Carbon Emission Equivalent for Virtualized Resources – An Analysis: Virtual Machine and Container Analysis for Greener Data Center

The International Energy Agency (IEA) revealed that the worldwide energy-related carbon dioxide (CO2) situation has hit a historic high of 33.1 Giga tonnes (Gt) of CO2. 85% of the rise in emissions was due to China, India, and the United States. The increase in emissions in India was 4.8%, or 105 Mega tonnes (Mt) of CO2, with the increase in emissions being evenly distributed across the transportation and industrial sectors, according to Beloglazov et al (2011). Environmental contamination brought on by carbon emissions is harmful to the environment. As a result, there is an urgent need for the IT sectors to develop effective and efficient technology to eliminate such carbon emissions. The primary focus is on lowering carbon emissions due to widespread awareness of the issue

Classification and Performance Study of Task Scheduling Algorithms in Cloud Computing Environment

Cloud computing is becoming very common in recent years and is growing rapidly due to its attractive benefits and features such as resource pooling, accessibility, availability, scalability, reliability, cost saving, security, flexibility, on-demand services, pay-per-use services, use from anywhere, quality of service, resilience, etc. With this rapid growth of cloud computing, there may exist too many users that require services or need to execute their tasks simultaneously by resources provided by service providers. To get these services with the best performance, and minimum cost, response time, makespan, effective use of resources, etc. an intelligent and efficient task scheduling technique is required and considered as one of the main and essential issues in the cloud computing environment. It is necessary for allocating tasks to the proper cloud resources and optimizing the overall system performance. To this end, researchers put huge efforts to develop several classes of scheduling algorithms to be suitable for the various computing environments and to satisfy the needs of the various types of individuals and organizations. This research article provides a classification of proposed scheduling strategies and developed algorithms in cloud computing environment along with the evaluation of their performance. A comparison of the performance of these algorithms with existing ones is also given. Additionally, the future research work in the reviewed articles (if available) is also pointed out. This research work includes a review of 88 task scheduling algorithms in cloud computing environment distributed over the seven scheduling classes suggested in this study. Each article deals with a novel scheduling technique and the performance improvement it introduces compared with previously existing task scheduling algorithms. Keywords: Cloud computing, Task scheduling, Load balancing, Makespan, Energy-aware, Turnaround time, Response time, Cost of task, QoS, Multi-objective. DOI: 10.7176/IKM/12-5-03 Publication date:September 30th 2022

Nu@ge: Towards a solidary and responsible cloud computing service

Best Paper AwardInternational audienceThe adoption of cloud computing is still limited by several legal concerns from companies. One of those reasons is the data sovereignty, as data can be physically host in sensible locations, resulting in a lack of control for companies. In this paper, we present the Nu@ge project aimed at building a federation of container-sized datacenter on the French territory. Nu@ge provides a software stack that enables companies to put independent datacenters in cooperation in a national mesh. Additionally, a prototype of a container-sized datacenter has been validated and patented

Energy-Efficient, Thermal-Aware Modeling and Simulation of Datacenters: The CoolEmAll Approach and Evaluation Results

International audienceThis paper describes the CoolEmAll project and its approach for modeling and simulating energy-efficient and thermal-aware data centers. The aim of the project was to address energy-thermal efficiency of data centers by combining the optimization of IT, cooling and workload management. This paper provides a complete data center model considering the workload profiles, the applications profiling, the power model and a cooling model. Different energy efficiency metrics are proposed and various resource management and scheduling policies are presented. The proposed strategies are validated through simulation at different levels of a data cente

Energy Aware SLA with Classification of Jobs for Cloud Environment

AbstractThe accelerated growth of the cloud eco-system is leading to the progress of new services, innovative ideas for the service replen- ishing and the newest interaction models both among the cloud providers and the customers which take advantage of the cloud resources. SLAs are one of the factors which allow for different interactions by keeping the objectives over privacy,QoS attributes and security constraints driving towards QoP attributes, the description of actions is needed in order to deliver the services ac- cording to the QoS attributes as expected by the customers. Energy aware SLAs extends the existing SLA agreements in order to include energy and carbon aware parameters. In this paper we propose an approach in order to relax certain jobs in a standardized way to obtain high energy consumption without disturbing the efficiency and availability of the system especially during the peak load times. The results for the above proposal are being discussed in this paper and were able to find that it is energy efficient