Cloud datacenter’s energy consumption has increased tremendously due to increase in the computation requirements of the user workload. Cloud BI is Thus, saving energy has become an important concern to address. These two objectives can present a potential conflict within cloud resource management decision making that must balance between service consolidation and replication to minimize energy consumption whilst maximizing server availability and reliability, respectively. However, the amount of energy consumed by cloud data centres is a major concern. energy optimization in cloud data centre. consumption. energy-efficient cloud resources." So, this was all about, future, trends, and prediction about Cloud computing. components. Holistic Management Aspects: A Comparison, Dzmitry Kliazovich, Pascal Bouvry, Yury, Singh, Sukhpal, and Inderveer Chana. A Roadmap To The Next GenEration DistRibuted COmputing (NERO) Systems, ROUTER: Fog Enabled Cloud based Intelligent Resource Management Approach for Smart Home IoT Devices, Holistic Resource Management for Sustainable and Reliable Cloud Computing: An Innovative Solution to Global Challenge, Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: Evolution, vision, trends and open challenges, HEART: Unrelated Parallel Machines Problem with Precedence Constraints for Task Scheduling in Cloud Computing using Heuristic and Meta-Heuristic Algorithms in Software, Transformative Effects of IoT, Blockchain and Artificial Intelligence on Cloud Computing: Evolution, Vision, Trends and Open Challenges, CLOUD COMPUTING IN AMAZON WEB SERVICES, MICROSOFT WINDOWS AZURE, GOOGLE APP ENGINE AND IBM CLOUD PLATFORMS: A COMPARATIVE STUDY A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF APPLIED SCIENCES OF NEAR EAST UNIVERSITY In Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Information Systems NICOSIA, 2019, Performance improvement of cloud security with parallel anarchies society optimization algorithm for virtual machine selection in cloud computing, An IoT Enabled Framework for Smart Buildings Empowered with Cloud & Fog Infrastructures, Adaptive cloud resource management through workload prediction, Resource-utilization-aware task scheduling in cloud platform using three-way clustering, An Integer Linear Programming model and Adaptive Genetic Algorithm approach to minimize energy consumption of Cloud computing data centers, Energy Efficient Task Scheduling in Cloud Environment, A Taxonomy and Future Directions for Sustainable Cloud Computing: 360 Degree View, BULLET: Particle Swarm Optimization Based Scheduling Technique for Provisioned Cloud Resources, Using Thermal-Aware VM Migration Mechanism for High-Availability Cloud Computing, SOCCER: Self-Optimization of Energy-efficient Cloud Resources, DVFS-Aware Consolidation for Energy-Efficient Clouds, A statistical survey on vm scheduling in cloud workstation for reducing energy consumption by balancing load in cloud, Minimizing SLA violation and power consumption in Cloud data centers using adaptive energy-aware algorithms, Dynamic virtual machine consolidation for improving energy efficiency in cloud data centers, QoS-aware Autonomic Resource Provisioning and Scheduling for Cloud Computing, Role of IoT, Cloud Computing and Big data, PRISM: An Experiment Framework for Straggler Analytics in Containerized Clusters, Hosting Virtual Machines on Distributed Datacenters, Virtual Machine Sizing in Virtualized Public Cloud Data Centres, Resource Management of IaaS Providers in Cloud Federation, Energy-Aware Virtual Machine Clustering for Consolidation in Multi-tenant IaaS Public Clouds, Conference: 2018 2nd International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). Think of the cloud as the ability to rent Energy consumption is reduced through efficient consolidation that is informed by VM resource consumption. possible future research directions for cloud computing. SkyDrive of Microsoft, iCloud of Apple, Google Drive, Google Doc & other services of Google, Cloud Service of Amazon, Online Photo-shop of Adobe, SCloud of Samsung and Nokia Air of Nokia are telling the future of computing. This paper focuses on task scheduling using Clonal Selection Algorithm (TSCSA) to optimize energy and processing time. Cloud computing is the newest computing paradigm that makes computing resources available over the Internet on a utility costing basis. number of servers and thus, the choice ab, dissemination and power-utilization. Such system must cope with varying load and evolving usage reflecting societies interaction and dependency on automated computing systems whilst satisfying Quality of Service (QoS) guarantees. Cloud computing plays a critical role in modern society and enables a range of applications from infrastructure to social media. The taxonomy is used to investigate the existing techniques for sustainability that need careful attention and investigation as proposed by several academic and industry groups. energy losses caused by I/O virtualization. 1 within the context of providing WRF as a To serve the maximum number of user requests, performance metrics of the proposed approach are evaluated. Furthermore, an Adaptive Genetic Algorithm (GA) is proposed to reflect the dynamic nature of the Cloud environment and to provide a near optimal scheduling solution that minimizes the energy consumption. (2018). Existing IoT and Fog computing resource managers focus on a singular or specific sub-set of metrics including application response time, latency, energy, and network bandwidth ( Lee et al., 2016;Yu et al., 2017;Stojkoska and Trivodaliev, 2017;Zhang et al., 2017 ), Capturing all these parameters within a Fog computing resource management is particularly important within the context of smart homes, which are positioned to process increasingly larger quantities of data from smart devices and appliances connected to IoT systems, whilst simultaneously ensuring high QoS and reduced energy consumption to reduce electricity bills for home dwellers ( Garraghan et al., 2018 ). further discuss Cloud Federation as a key concept allowing the development of new types of applications. In this paper, we propose a cuckoo optimization-based energy-reliability aware resource scheduling technique (CRUZE) for holistic management of cloud computing resources including servers, networks, storage, and cooling systems. An independent blockchain will be set up in order to invoice the transactions on the nuco.cloud, and the cryptographic token 'NUCO (s)' shall be created for this purpose. Performance of the proposed technique has been evaluated in cloud environment. Cloud computing is becoming a profitable technology because of it offers cost-effective IT solutions globally. g societies’ interaction and dependency on automated computing systems whilst satisfying Quality of Service (QoS) guarantees. Further, the current research on sustainable cloud computing is organized into several categories: application design, sustainability metrics, capacity planning, energy management, virtualization, thermal-aware scheduling, cooling management, renewable energy and waste heat utilization. Tremendous amount of energy consumption leads to high operational costs and reduces return on investment and contributes towards carbon footprints to the environment. As IaaS and PaaS continue to be used worldwide to achieve diverse goals, we will see these solutions as the most deployed cloud services around the world. The major problem in the usage of the technology is the security concerns which increase the demand for a robust security mechanism to protect the data on the cloud. €170 million public-private partnership to help build the Internet of the future, with cloud computing as a key component. Electrical Engineering 47 (2015): 241-254. We developed the model Auto-Regressive Integrated Moving Average-workload Prediction for Efficient Resource Provisioning (ARIMA-PERP) and evaluated the results that can satisfy the on-demand need of end-users for efficient resource utilization. Such system must cope with varying load and evolving usage reflecting societies’ interaction and dependency on automated computing systems whilst satisfying Quality of Service (QoS) guarantees. Specifically, these schedulers are not designed to operate within an environment including highly mobile edge devices ( Son and Buyya, 2019 ), latency-sensitive applications, nor wide geographical areas intrinsic to Fog computing environments. In this paper, we propose a technique for determining fixed VM sizes, which satisfy application workload resource demands. Cluster Computing. The experimental results show that the proposed technique efficiently reduces execution cost, time and energy consumption along with other QoS parameters. To achieve this objective of efficient resource provisioning, algorithms are developed for workload prediction which helps in deciding optimum resource provisioning. cilities through the power of cloud computing. International Journal of Grid and Distributed Computing. According to a survey by RightScale,1 81 percent of companies with 1,000 employees or more have a multi-platform strategy. On one level, it means that organizations will leverage both public hyperscale … Title: Microsoft Word - PIP_Future_of_Internet_ 2010_cloud_.doc Author: Janna Q. Anderson Created Date: 6/10/2010 5:02:27 AM Here you can download the free Cloud Computing Pdf Notes – CC notes pdf of Latest & Old materials with multiple file links to download. We formulate the problem of hosting virtual machines on distributed datacenters as an optimization problem, and propose a distributed framework DHC that can dynamically direct workload between datacenters to maximize total utility of entire datacenters. In cloudbusting, the application runs in a private cloud … We have presented an approach in this paper to reduce power consumption for IaaS Providers, by choosing the most appropriate host and allocating the best virtual machine which leads to satisfy users requests, save energy and reduce the cost of resources. A. A conceptual model for sustainable cloud computing has been proposed along with discussion on future research directions. As the growth of data is increasing tremendously, efficient resource management is the need in cloud computing. which utilizes heterogeneous stages to spare power. It provides greater flexibility to work between both the cloud solutions. In this paper, we focus on different aspects of cloud computing for holistic management of cloud resources in an energy-efficient, reliable and sustainable manner. Environment." Future is demanding business operators to go forward towards interoperable federation of cross cloud platform. By employing the method of pseudorandom number generators (PRNGs), random keys are generated and the finest keys are produced by using the WMCNN method. It also describes operations between two distinct formally disconnected telecommunication networks with distinct internal structures. In the WMCNN approach, randomly generated keys are taken as input and the approximation concerning the secret key of the input is produced by the hidden layers. All content in this area was uploaded by Sukhpal Singh Gill on Mar 05, 2019, Opportunities, Challenges and Research Trends. Data centers hosting Cloud applications consume massive amount of power, contributing to high carbon footprints to the environment. The energy consumption and makespan associated with the resources allocated should be taken into account. More often, the users overprovision the resources, which go to waste. management of cloud resources in an energy-efficient. Recently there are many emerging cloud platforms to choose from to run, deploy and maintain applications over the cloud, offering a variety of services and tools at the disposal of a user. The Future Of Cloud Computing 1 Thursday, September 1, 11::Setting Some Context ... Toward A Secure Cloud Future... 16 Thursday, September 1, 11. This study is beneficial for potential users such as small mid-size enterprises, start-up developers and large companies for selecting a cloud platform that meets their requirements. Further, we identify several technologies driving these paradigms and invite international experts to discuss the current status and future directions of cloud computing. Second. Cloud computing infrastructures are designed to support the accessibility and availability of various services to consumers over the Internet. However, these techniques lack collection and analysis of active real cloud traces from the IaaS cloud. temperature and utilization of the servers. When comparing the experimental results of the proposed system with the existing system, it is observed that the proposed system accomplished an enhanced performance with respect to resource utilization, cost, throughput, service latency as well as execution time. Additionally, the CSPs do not have control over the types of applications that are executed and thus VM consolidation is performed blindly. The idea of ‘Cloud Computing’ and ‘Cloud Storage’ has created an initial hype and excitement around the world. Amazon … Computers & Electrical Engineering 40.5, Massoud Pedram. In this study, we aim to explore how three emerging paradigms (Blockchain, IoT and Artificial Intelligence) will influence future cloud computing systems. Cloud datacenter. According to the world-famous writer and public figure Nicolas Carr, today IT systems are becoming a thing of the past: the competitive importance of IT inevitably decreases, the software, like once electricity, becomes… a communal service! Cloud computing, such as Infrastructure as a Service (IaaS), enables vendors to use virtualization technology to rent computing resources on a physical machine to execute the desired applications of users. Finally, the results were compared to existing scheduling algorithms and found that the proposed algorithm (TSCSA) provide an optimal balance results for multiple objectives. The paper is structured as follows: Section II provides an overview of the state of the art Cloud Stack and describes economic problems related to Cloud Computing. Most private clouds are Keywords: Cloud Computing, Federation, Cloud Architecture. @$�5��)��`�>��`v������h�HfC��8s+X�D Storage of the files concerning the encrypted data is done in the cloud storage system. Finally, we proposed a conceptual model for cloud futurology to explore the influence of emerging paradigms and technologies on evolution of cloud computing. DVFS system and workload planning, timetable created by a different scheduler [10. consolidation and reduces the number of active hosts. Organizations take the benefit of cloudbusting when there is an increase in application demand. Resource management strategy in adaptive cloud provisions the needed resources dynamically to the end-users. To achieve cost effective IT solution for the society in sustainable manner. Cloud Computing and Business Intelligence (BI) are becoming increasingly important in gaining and maintaining a competitive edge [1]. It is observed that our evaluated results achieved an accurate prediction by 91.11%, which meets the efficient resource utilization for the demanded workload. The Future of Cloud Computing for Academic Research Computing 5 • Although in their infancy, hybrid clouds hold the promise of enabling modest size private clouds used for steady-state workloads to burst to public, community, or national CI during peak workloads. 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