8 research outputs found
A REVIEW ON ENERGY EFFICIENT JOB SCHEDULING ALGORITHMS IN GREEN CLOUD COMPUTING
Cloud computing is the hottest topic in today's world and is being used by most of the information technology companies due to its benefits incost saving and ease of use. It is a dynamic, scalable, and pay-per-use distributed computing model. The cloud computing is aims to give accessto remote and geographically distributed resources. Scheduling the job from one data center to other data center or from one region of cloud toother region is truly a testing in cloud environment. However, when data are shifted from one data center to other data center, huge amount ofcarbon dioxide (CO2) gases emits and also consumes more power. Since energy is an important issue, that is, why green cloud computing comesinto the picture. Green cloud computing can be obtained by applying various techniques and algorithms, which use less power and emits lessCO2 gas, that is, damaging the environment. Cloud provides many facilities to its tenants such as sharing of resources for different purposes. Incloud domain, job scheduling is one of the biggest and hypothetical problems. Numerous investigations for scheduling a job and efforts carriedout in this regard because it is one of the main jobs to get the most profit. Scheduling can decrease the power consumption. So many algorithmshad been proposed for this purpose, and a lot more had to be done. In the paper, intends to present a variety of energy-efficient job schedulingalgorithms along with performance comparison analysis of various preexisting algorithms for scheduling jobs to provide energy efficiency ingreen cloud computing
Energy-efficient Nature-Inspired techniques in Cloud computing datacenters
Cloud computing is a systematic delivery of computing resources as services to the consumers via the Internet. Infrastructure
as a Service (IaaS) is the capability provided to the consumer by enabling smarter access to the processing, storage,
networks, and other fundamental computing resources, where the consumer can deploy and run arbitrary software including
operating systems and applications. The resources are sometimes available in the form of Virtual Machines (VMs). Cloud
services are provided to the consumers based on the demand, and are billed accordingly. Usually, the VMs run on various
datacenters, which comprise of several computing resources consuming lots of energy resulting in hazardous level of carbon
emissions into the atmosphere. Several researchers have proposed various energy-efficient methods for reducing the energy
consumption in datacenters. One such solutions are the Nature-Inspired algorithms. Towards this end, this paper presents a
comprehensive review of the state-of-the-art Nature-Inspired algorithms suggested for solving the energy issues in the Cloud
datacenters. A taxonomy is followed focusing on three key dimension in the literature including virtualization, consolidation,
and energy-awareness. A qualitative review of each techniques is carried out considering key goal, method, advantages, and
limitations. The Nature-Inspired algorithms are compared based on their features to indicate their utilization of resources
and their level of energy-efficiency. Finally, potential research directions are identified in energy optimization in data centers.
This review enable the researchers and professionals in Cloud computing datacenters in understanding literature evolution
towards to exploring better energy-efficient methods for Cloud computing datacenters
Real-time and dynamic fault-tolerant scheduling for scientific workflows in clouds
Cloud computing has become a popular technology for executing scientific workflows. However, with a large number of hosts and virtual machines (VMs) being deployed, the cloud resource failures, such as the permanent failure of hosts (HPF), the transient failure of hosts (HTF), and the transient failure of VMs (VMTF), bring the service reliability problem. Therefore, fault tolerance for time-consuming scientific workflows is highly essential in the cloud. However, existing fault-tolerant (FT) approaches consider only one or two above failure types and easily neglect the others, especially for the HTF. This paper proposes a Real-time and dynamic Fault-tolerant Scheduling (ReadyFS) algorithm for scientific workflow execution in a cloud, which guarantees deadline constraints and improves resource utilization even in the presence of any resource failure. Specifically, we first introduce two FT mechanisms, i.e., the replication with delay execution (RDE) and the checkpointing with delay execution (CDE), to cope with HPF and VMTF, simultaneously. Additionally, the rescheduling (ReSC) is devised to tackle the HTF that affects the resource availability of the entire cloud datacenter. Then, the resource adjustment (RA) strategy, including the resource scaling-up (RS-Up) and the resource scaling-down (RS-Down), is used to adjust resource demands and improve resource utilization dynamically. Finally, the ReadyFS algorithm is presented to schedule real-time scientific workflows by combining all the above FT mechanisms with RA strategy. We conduct the performance evaluation with real-world scientific workflows and compare ReadyFS with five vertical comparison algorithms and three horizontal comparison algorithms. Simulation results confirm that ReadyFS is indeed able to guarantee the fault tolerance of scientific workflow execution and improve cloud resource utilization
SusTrainable: Promoting Sustainability as a Fundamental Driver in Software Development Training and Education. 2nd Teacher Training, January 23-27, 2023, Pula, Croatia. Revised lecture notes
This volume exhibits the revised lecture notes of the 2nd teacher training
organized as part of the project Promoting Sustainability as a Fundamental
Driver in Software Development Training and Education, held at the Juraj
Dobrila University of Pula, Croatia, in the week January 23-27, 2023. It is the
Erasmus+ project No. 2020-1-PT01-KA203-078646 - Sustrainable. More details can
be found at the project web site https://sustrainable.github.io/
One of the most important contributions of the project are two summer
schools. The 2nd SusTrainable Summer School (SusTrainable - 23) will be
organized at the University of Coimbra, Portugal, in the week July 10-14, 2023.
The summer school will consist of lectures and practical work for master and
PhD students in computing science and closely related fields. There will be
contributions from Babe\c{s}-Bolyai University, E\"{o}tv\"{o}s Lor\'{a}nd
University, Juraj Dobrila University of Pula, Radboud University Nijmegen,
Roskilde University, Technical University of Ko\v{s}ice, University of
Amsterdam, University of Coimbra, University of Minho, University of Plovdiv,
University of Porto, University of Rijeka.
To prepare and streamline the summer school, the consortium organized a
teacher training in Pula, Croatia. This was an event of five full days,
organized by Tihana Galinac Grbac and Neven Grbac. The Juraj Dobrila University
of Pula is very concerned with the sustainability issues. The education,
research and management are conducted with sustainability goals in mind.
The contributions in the proceedings were reviewed and provide a good
overview of the range of topics that will be covered at the summer school. The
papers in the proceedings, as well as the very constructive and cooperative
teacher training, guarantee the highest quality and beneficial summer school
for all participants.Comment: 85 pages, 8 figures, 3 code listings and 1 table; editors: Tihana
Galinac Grbac, Csaba Szab\'{o}, Jo\~{a}o Paulo Fernande