This is challenging especially in Infrastructure as a Service (IaaS) public clouds where customers select VM sizes set beforehand by the Cloud Service Providers (CSPs) without the knowledge of the amount of resources their applications need. In this study, we aim to explore how three emerging paradigms (Blockchain, IoT and Artificial Intelligence) will influence future cloud computing systems. Thus a metric is required for. Section 5 is devoted to how to implement the model of Fig. Distributed Computing Cloud (hereinafter referred to as 'nuco.cloud'). Extensive numerical experiments have been performed to evaluate the performance of proposed algorithms. 1332 D. Villegas et al. To achieve this objective of efficient resource provisioning, algorithms are developed for workload prediction which helps in deciding optimum resource provisioning. In cloudbusting, the application runs in a private cloud ⦠By employing the method of pseudorandom number generators (PRNGs), random keys are generated and the finest keys are produced by using the WMCNN method. Cloud computing (CC) is a future promising computing technology and has proven tremendous exceptional attainable in managing the hardware and software program sources placed at third-party provider vendors. The results demonstrate that the proposed solution offers performance gains with regards to response time and in reducing energy consumption. The aim of this study is to compare four widely adopted cloud platforms, AWS, Microsoft windows azure, Google app engine and IBM cloud based on some commonly shared features such as cloud service type, storage, database, security, service level agreements, programming languages used, pricing, virtualization, mobile services offered, internet of things, data backup and recovery and user interface to guide customers in selecting a suitable cloud platform. Cloud computing infrastructures are designed to support the accessibility and availability of various services to consumers over the Internet. 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. ��ş�ţ��6�l%���`&e@$�50��f#�-"�܁$��g ���b&���ā�$��ԩv�&�� ��� complex. 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). 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. This story, "Federation: The future of cloud" was originally published by ITworld The future will be very bright for the use of BI in the cloud, both because of the advantages that underpin this new computing paradigm as well as the explosion of digital data that grows each day [2]. In this paper, energy efficient autonomic cloud system [Self-Optimization of Cloud Computing Energy-efficient Resources (SOCCER)] is proposed for energy efficient scheduling of cloud resources in data centers. It provides greater flexibility to work between both the cloud solutions. A Mixed Integer Linear Programming (MILP) formulation has been provided for the two variants of the problem. further discuss Cloud Federation as a key concept allowing the development of new types of applications. 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. We evaluate the effectiveness of CRUZE against existing state-of-the-art solutions using the CloudSim toolkit. In traditional systems, resources are managed based on demand, availability and the strategy of scheduling which results in delayed response time at large. By leveraging VM migration, the risk to the physical machine can be removed by transferring its load to a normal one and reducing the CPU temperature. Thus, saving energy has become an important concern to address. International Journal of Scientific Research in Computer Science Engineering and Information Technology. This is because the maintenance, server cost, and back -up are often provided for by the cloud servicer provider, who distributes the cost among many customers. Tremendous amount of energy consumption leads to high operational costs and reduces return on investment and contributes towards carbon footprints to the environment. The first one is the balancing of a large amount of data on existing resources and the second is resource provisioning which can adjust the number of resources optimally to adapt the time-varying workload. 136 0 obj <>/Filter/FlateDecode/ID[<3D7FAA0FC9C3B7A46DE04FD549FF21A5><9221FC7D045696419EE80B5C8FBEC318>]/Index[106 109]/Info 105 0 R/Length 140/Prev 292181/Root 107 0 R/Size 215/Type/XRef/W[1 3 1]>>stream education, weather forecasting, hedge funding, e-commerce and big data solution, DST Inspire Project, Government of India, (Registration/IVR Number: 201400000761 [DST/INSPIRE/03/2014/000359]). Resource management strategy in adaptive cloud provisions the needed resources dynamically to the end-users. Heuristic and meta-heuristic (HEART) based algorithms are proposed to solve the task scheduling problems. server consolidation and dynamic voltage frequency. Future of cloud computing | 10. This requires the streaming of significant amounts of data over the network, which in turn represents various management challenges, involving energy efficiency, time-critical operations, and similar, ... • Internet of Things: IoT devices are network devices such as actuators, software, home appliances and sensors and Internet connectivity is used to exchange data among these network devices [8]. 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. Because of the dynamic nature of cloud workloads, we show that any resource demands that exceed fixed VM resources can be addressed via statistical multiplexing. China is also focusing on the cloud; its 12th Five-Year Plan, issued in 2010, addresses cloud computing as part of an initiative to develop strategic new industries. degrades the server’s performance, reliability. âThe future of cloud computing is undeniably hybrid. The result obtained by TSCSA was simulated by an open source cloud platform (CloudSim). Storage of the files concerning the encrypted data is done in the cloud storage system. The usage of large number of cloud datacenters increases cost as well as carbon footprints, which further effects the sustainability of cloud services. energy optimization in cloud data centre. The proposed adaptive GA is validated by simulating the Cloud infrastructure and conducting a set of performance and quality evaluation study in this environment. According to a survey by RightScale,1 81 percent of companies with 1,000 employees or more have a multi-platform strategy. Enabling these systems are a cohort of conceptual technologies, synthesized to meet demand of evolving computing applications. Cloud federation is an approach to share resources, enhance the scalability and availability. Computers & Electrical Engineering (2018). 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. Cloud BI is Algorithms and Architectures for Parallel. Technology and Science, pp.115-121, 2011. Cloud computing plays a critical role in modern society and enables a range of applications from infrastructure to social media. Additionally, the CSPs do not have control over the types of applications that are executed and thus VM consolidation is performed blindly. 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