Many-Objective Optimization-Based Task Scheduling in Hybrid Cloud Environments

Due to the security and scalability features of hybrid cloud architecture,it can bettermeet the diverse requirements of users for cloud services.And a reasonable resource allocation solution is the key to adequately utilize the hybrid cloud.However,most previous studies have not comprehensively optimized the performance of hybrid cloud task scheduling,even ignoring the conflicts between its security privacy features and other requirements.Based on the above problems,a many-objective hybrid cloud task scheduling optimization model(HCTSO)is constructed combining risk rate,resource utilization,total cost,and task completion time.Meanwhile,an opposition-based learning knee point-driven many-objective evolutionary algorithm(OBL-KnEA)is proposed to improve the performance of model solving.The algorithm uses opposition-based learning to generate initial populations for faster convergence.Furthermore,a perturbation-based multipoint crossover operator and a dynamic range mutation operator are designed to extend the search range.By comparing the experiments with other excellent algorithms on HCTSO,OBL-KnEA achieves excellent results in terms of evaluation metrics,initial populations,and model optimization effects.

Hybrid Mobile Cloud Computing Architecture with Load Balancing for Healthcare Systems

Healthcare is a fundamental part of every individual’s life.The healthcare industry is developing very rapidly with the help of advanced technologies.Many researchers are trying to build cloud-based healthcare applications that can be accessed by healthcare professionals from their premises,as well as by patients from their mobile devices through communication interfaces.These systems promote reliable and remote interactions between patients and healthcare professionals.However,there are several limitations to these innovative cloud computing-based systems,namely network availability,latency,battery life and resource availability.We propose a hybrid mobile cloud computing(HMCC)architecture to address these challenges.Furthermore,we also evaluate the performance of heuristic and dynamic machine learning based task scheduling and load balancing algorithms on our proposed architecture.We compare them,to identify the strengths and weaknesses of each algorithm;and provide their comparative results,to show latency and energy consumption performance.Challenging issues for cloudbased healthcare systems are discussed in detail.

Cost Effective Optimal Task Scheduling Model in Hybrid Cloud Environment

In today’s world, Cloud Computing (CC) enables the users to accesscomputing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located inremote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and taskscheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud isemployed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the currentresearch work develops a Cost-Effective Optimal Task Scheduling Model(CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) modelis used in the proposed work for hybrid clouds. Moreover, the algorithm workson the basis of multi-intentional task completion process with optimal resourceallocation. The model was successfully simulated to validate its effectivenessbased on factors such as processing time, make span and efficient utilization ofvirtual machines. The results infer that the proposed model outperformed theexisting works and can be relied in future for real-time applications.

Hybrid Cloud Architecture for Higher Education System

As technology improves,several modernization efforts are taken in the process of teaching and learning.An effective education system should maintain global connectivity,federate security and deliver self-access to its services.The cloud computing services transform the current education system to an advanced one.There exist several tools and services to make teaching and learning more interesting.In the higher education system,the data flow and basic operations are almost the same.These systems need to access cloud-based applications and services for their operational advancement and flexibility.Architecting a suitable cloud-based education system will leverage all the benefits of the cloud to its stakeholders.At the same time,educational institutions want to keep their sensitive information more secure.For that,they need to maintain their on-premises data center along with the cloud infrastructure.This paper proposes an advanced,flexible and secure hybrid cloud architecture to satisfy the growing demands of an education system.By sharing the proposed cloud infrastructure among several higher educational institutions,there is a possibility to implement a common education system among organizations.Moreover,this research demonstrates how a cloud-based education architecture can utilize the advantages of the cloud resources offered by several providers in a hybrid cloud environment.In addition,a reference architecture using Amazon Web Service(AWS)is proposed to implement a common university education system.

The Future of Cloud Computing: Benefits and Challenges

The purpose of this paper is to provide a better knowledge of the cloud computing as well as to suggest relevant research paths in this growing field. Also, we will go through the future benefits of cloud computing and the upcoming possible challenges we will have. Intext Cloud, performance, cloud computing, architecture, scale-up, and big data are all terms used in this context. Cloud computing offers a wide range of architectural configurations, including the number of processors, memory, and nodes. Cloud computing has already changed the way we store, process, and access data, and it is expected to continue to have a significant impact on the future of information technology. Cloud computing enables organizations to scale their IT resources up or down quickly and easily, without the need for costly hardware upgrades. This can help organizations to respond more quickly to changing business needs and market conditions. By moving IT resources to the cloud, organizations can reduce their IT infrastructure costs and improve their operational efficiency. Cloud computing also allows organizations to pay only for the resources they use, rather than investing in expensive hardware and software licenses. Cloud providers invest heavily in security and compliance measures, which can help to protect organizations from cyber threats and ensure regulatory compliance. Cloud computing provides a scalable platform for AI and machine learning applications, enabling organizations to build and deploy these technologies more easily and cost-effectively. A task, an application, and its input can take up to 20 times longer or cost 10 times more than optimal. Cloud products’ ready adaptability has resulted in a paradigm change. Previously, an application was optimized for a specific cluster;however, in the cloud, the architectural configuration is tuned for the workload. The evolution of cloud computing from the era of mainframes and dumb terminals has been significant, but there are still many advancements to come. As we look towards the future, IT leaders and the companies they serve will face increasingly complex challenges in order to stay competitive in a constantly evolving cloud computing landscape. Additionally, it will be crucial to remain compliant with existing regulations as well as new regulations that may emerge in the future. It is safe to say that the next decade of cloud computing will be just as dramatic as the last where many internet services are becoming cloud-based, and huge enterprises will struggle to fund physical infrastructure. Cloud computing is significantly used in business innovation and because of its agility and adaptability, cloud technology enables new ways of working, operating, and running a business. The service enables users to access files and applications stored in the cloud from anywhere, removing the requirement for users to be always physically close to actual hardware. Cloud computing makes the connection available from anywhere because they are kept on a network of hosted computers that carry data over the internet. Cloud computing has shown to be advantageous to both consumers and corporations. To be more specific, the cloud has altered our way of life. Overall, cloud computing is likely to continue to play a significant role in the future of IT, enabling organizations to become more agile, efficient, and innovative in the face of rapid technological change. This is likely to drive further innovation in AI and machine learning in the coming years.

Cloud-Enabled E-Governance Framework for Citizen Centric Services

In the modern arena, the Information and Communication Technologies (ICTs) have been playing a vital role in every walks of our day to day life. In order to enhance the ICT capacity and align with the global technology transformations, the developing countries have started introducing the computerization and automation processes at different levels of the governments. The several research studies revealed that the existing legacy of governance system and their services in current state have several issues and challenges in terms of timeliness, cost of services, delay in service delivery, time-bound availability of services (24/7/365), inefficiency services, ease of service and discomforts, poor service collaboration, absence of responsiveness, and limited security of sensitive information/documents. A significant question is still unanswered that how to bring the Citizens and Government bodies closer for alleviating the aforementioned issues and challenges of existing government system services. This research paper aims to investigate the issues and challenges in the current status of Governance and partial E-Governance systems which encompass the computerization or automation process. The research designs a cloud framework for effective delivery of citizen centric services in general and Ethiopia as a specific case study. After rigorous analysis of prior research efforts, along with primary survey and interview, it was clearly observed that cloud computing can be an alternative instrumental for significant transformation of governmental service delivery. The research paper used a mix of exploratory and constructive research design and methodology with qualitative & quantitative data analysis approach. Finally, a Cloud Based E-Governance (CBEG) Framework is designed for the delivery of Ethiopian Citizen Centric Services. The validation, evaluation and acceptance test of the framework proves that the revealed knowledge can provide a significant transformation towards the betterment of the E Governance Services Delivery Systems.

Flexible CP-ABE Based Access Control on Encrypted Data for Mobile Users in Hybrid Cloud System

In hybrid cloud computing, encrypted data access control can provide a fine-grained access method for organizations to enact policies closer to organizational policies. This paper presents an improved CP-ABE (ciphertext-policy attribute-based encryption) scheme to construct an encrypted data access control solution that is suitable for mobile users in hybrid cloud system. In our improvement, we split the original decryption keys into a control key, a secret key and a set of transformation keys. The private cloud managed by the organization administrator takes charge of updating the transformation keys using the control key. It helps to handle the situation of flexible access management and attribute alteration. Meanwhile, the mobile user's single secret key remains unchanged as well as the ciphertext even if the data user's attribute has been revoked. In addition, we modify the access control list through adding the attributes with corresponding control key and transformation keys so as to manage user privileges depending upon the system version. Finally, the analysis shows that our scheme is secure, flexible and efficient to be applied in mobile hybrid cloud computing.

Optimized bandwidth allocation for maximizing user's QoE in hybrid cloud P2P content distribution

Hybrid cloud peer to peer （P2P） system is widely used for content distribution by utilizing user＇s capabilities to relieve the cloud bandwidth pressure. However, as demands for large-size files grow rapidly, it is a challenge to support high speed downloading experience simultaneously in different swarms with limited cloud bandwidth resource in such system. Therefore, it requires an optimized cloud bandwidth allocation to improve overall downloading experience of users. In this paper, we propose a system performance model which characterizes the relationship between cloud uploading bandwidth and user download speed. Based on the model, we study the cloud uploading bandwidth allocation, with the goal of optimizing user＇s quality of experience （QoE） that mainly depends on downloading rate of desired contents. Furthermore, to decrease the computation complexity, we put forward a heuristic algorithm to approximate the optimized solution. Simulation results show that our heuristic algorithm can obtain higher user＇s QoE as compared with two typical bandwidth allocation algorithms.

Research on robot grabbing system based on hybrid cloud

Robot grabbing has been successfully applied to a range of challenging environments but met the resource bottleneck. To answer this question, a hybrid cloud-based robot grabbing system is proposed, which supports centralized bin-picking management and deployment, large-scale storage, and communication technologies. The hybrid cloud combines the powerful computational capabilities through massive parallel computation and higher data storage facilities in the public cloud with data privacy in the private data center. The benchmark tasks against a public cloud based on robot grabbing method are evaluated, whose results indicate that the whole system reduces the data collection time and increases elastic resource scheduling and is adapted in the real industry.

IN2CLOUD: A novel concept for collaborative management of big railway data

In the EU Horizon 2020 Shift2Rail MultiAnnual Action Plan, the challenge of railway maintenance is generating knowledge from data and/or information. Therefore, we promote a novel concept called"IN2CLOUD," which comprises three sub-concepts, to address this challenge: 1) A hybrid cloud, 2) an intelligent cloud with hybrid cloud learning, and 3) collaborative management using asset-related data acquired from the intelligent hybrid cloud. The concept is developed under the assumption that organizations want/need to learn from each other(including domain knowledge and experience)but do not want to share their raw data or information.IN2CLOUD will help the movement of railway industry systems from "local" to "global" optimization in a collaborative way. The development of cutting-edge intelligent hybrid cloud-based solutions, including information technology(IT) solutions and related methodologies, will enhance business security, economic sustainability, and decision support in the field of intelligent asset management of railway assets.