Cloud services with big data provide a solution for monitoring and tracking sustainable development goals

To achieve the Sustainable Development Goals(SDGs),high-quality data are needed to inform the formulation of policies and investment decisions,to monitor progress towards the SDGs and to evaluate the impacts of policies.However,the data landscape is changing.With emerging big data and cloud-based services,there are new opportunities for data collection,influencing both official data collection processes and the operation of the programmes they monitor.This paper uses cases and examples to explore the potential of crowdsourcing and public earth observation(EO)data products for monitoring and tracking the SDGs.This paper suggests that cloud-based services that integrate crowdsourcing and public EO data products provide cost-effective solutions for monitoring and tracking the SDGs,particularly for low-income countries.The paper also discusses the challenges of using cloud services and big data for SDG monitoring.Validation and quality control of public EO data is very important;otherwise,the user will be unable to assess the quality of the data or use it with confidence.

Access Control Policy Analysis and Access Denial Method for Cloud Services

Personal cloud computing is an emerging trend in the computer industry. For a sustainable service, cloud computing services must control user access. The essential business characteristics of cloud computing are payment status and service level agreement. This work proposes a novel access control method for personal cloud service business. The proposed method sets metadata, policy analysis rules, and access denying rules. Metadata define the structure of access control policies and user requirements for cloud services. The policy analysis rules are used to compare conflicts and redundancies between access control policies. The access denying rules apply policies for inhibiting inappropriate access. The ontology is a theoretical foundation of this method. In this work, ontologies for payment status, access permission, service level, and the cloud provide semantic information needed to execute rules. A scenario of personal data backup cloud service is also provided in this work. This work potentially provides cloud service providers with a convenient method of controlling user access according to changeable business and marketing strategies.

SDN-Based Broadband Network for Cloud Services

Over-the-top services and cloud services have created great challenges for telecom operators. To better meet the requirements of cloud services, we propose a decoupled network architecture. Software-defined networking/network function virtualization （SDN/ NFV） will be vital in the construction of cloud-oriented broadband infrastructure, especially within data centers and for intercon nection between data centers. We also propose introducing SDN/NFV in the broadband access network in order to realize a virtu- alized residential gateway （VRG）. We discuss the deployment modes of VRG.

Cloud Services Quality Enhancement through Control &Monitoring of Service Level Agreements at Server and Consumer Side

Several researches and case studies have been revealing a repetitive issue and that is monopolization of controlling, measuring, and metering of the consumer’s billing for the consumed Cloud Services. The Cloud Service Providers (CSPs) have been hiding, or monopolizing the controlling, metering tools and ignoring the calculation and consideration of the service defects like downtime, service outage, poor performance and client service migration delays during overloads of the servers. The main issues behind these discrepancies are the Service Level Agreement (SLA), its violation, and the monopolized Cloud Governance. Till now there is a lack of parallel monitoring and metering system of the consumed cloud services at the customer level under the provisions of SLAs. The Cloud Governance Tier has not given any flexibility or utility to monitor such consumed cloud services at the client tier in parallel to the CSP tier. This research is an effort to develop a SLA controlling/monitoring framework to solve the identified problems other than the CSP level. Further the E_Draw max was used for designing the framework. The framework consists of the components like;SLA_CSP, SLA_CSC, SLA_M&C and Cloud Services and Delivery Models. After designing the framework, a prototype was developed using CloudSim on java net beans, and MySQL database. This prototype was implemented using four scenarios to evaluate its performance and the functionalities. 1) Checking the SLA under CSP whether the resources to the consumer in the same manner with promised. 2) To check if the request from cloud consumer is less than what is expected in SLA. 3) To check by increasing the request of cloud consumer more than what is expected in SLA and 4) Using the SLA_M&C mechanism. After execution it was observed that, in the first and the second cases there is no violation, but there is violation in the third and fourth cases. This implied that there are chances of the discrepancies in resources provided to make the selves beneficiary beyond SLA under CSP and CSC was discriminated while receiving services from CSP.

An Adaptive Video-on-Demand Framework for Multimedia Cross-Platform Cloud Services

Although Video-On-Demand (VOD) has been in existence for years, its cross-platform applicability in cloud service environments is still in increasing need. In this paper, an Adaptive Video-On-Demand (AVOD) framework that is suitable for private cloud environments is proposed. Private cloud has the key advantage of satisfying the real need of both consumers and providers. Hence, demands such as reasonable benefits for provider and high quality for consumers are essential design considerations in this framework. The difficulty is that these two factors are always high in one end and low in the other, and hard to find a delicate balance. Cloud service could be an opportunity for the multimedia providers to obtain higher benefits and cost less for the consumers but with an even better quality in service. An adaptive framework for such a cloud service environment is proposed to resolve this problem. Some interesting phenomena are observed from the experimental results including CPU utilization, data reading and writing speed, memory usage, port configuration execution time, and bandwidth.

Transparent Computing: Spatio-Temporal Extension on von Neumann Architecture for Cloud Services

The rapid advancements in hardware, software, and computer networks have facilitated the shift of the computing paradigm from mainframe to cloud computing, in which users can get their desired services anytime, anywhere, and by any means. However, cloud computing also presents many challenges, one of which is the difficulty in allowing users to freely obtain desired services, such as heterogeneous OSes and applications, via different light-weight devices. We have proposed a new paradigm by spatio-temporally extending the von Neumann architecture, called transparent computing, to centrally store and manage the commodity programs including OS codes, while streaming them to be run in non-state clients. This leads to a service-centric computing environment, in which users can select the desired services on demand, without concern for these services＇ administration, such as their installation, maintenance, management, and upgrade. In this paper, we introduce a novel concept, namely Meta OS, to support such program streaming through a distributed 4VP~ platform. Based on this platform, a pilot system has been implemented, which supports Windows and Linux environments. We verify the effectiveness of the platform through both real deployments and testbed experiments. The evaluation results suggest that the 4VP~ platform is a feasible and promising solution for the future computing infrastructure for cloud services.

RESTlogic: Detecting Logic Vulnerabilities in Cloud REST APIs

logical testing model and resource lifecycle information,generate test cases and complete parameters,and alleviate inconsistency issues through parameter inference.Once again,we propose a method of analyzing test results using joint state codes and call stack information,which compensates for the shortcomings of traditional analysis methods.We will apply our method to testing REST services,including OpenStack,an open source cloud operating platform for experimental evaluation.We have found a series of inconsistencies,known vulnerabilities,and new unknown logical defects.

Quantum-Edge Cloud Computing for IoT: Bridging the Gap between Cloud, Edge, and Quantum Technologies

The rapid expansion of the Internet of Things (IoT) has driven the need for advanced computational frameworks capable of handling the complex data processing and security challenges that modern IoT applications demand. However, traditional cloud computing frameworks face significant latency, scalability, and security issues. Quantum-Edge Cloud Computing (QECC) offers an innovative solution by integrating the computational power of quantum computing with the low-latency advantages of edge computing and the scalability of cloud computing resources. This study is grounded in an extensive literature review, performance improvements, and metrics data from Bangladesh, focusing on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. The discussion covers vital elements, including integrating quantum cryptography to enhance data security, the critical role of edge computing in reducing response times, and cloud computing’s ability to support large-scale IoT networks with its extensive resources. Through case studies such as the application of quantum sensors in autonomous vehicles, the practical impact of QECC is demonstrated. Additionally, the paper outlines future research opportunities, including developing quantum-resistant encryption techniques and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC has the potential to overcome the current limitations of IoT frameworks, setting a new standard for future IoT applications.

Prioritization technique for learning cloud services

Purpose–The purpose of this paper is to propose a combined technique of cumulative voting and numerical assignment to prioritize the services of the learning cloud service.Design/methodology/approach–The approach starts with requirement elicitation,then analyses of the requirements in terms of prioritization and finally classifies the priority of services into groups.Findings–As a result of the case study the requirements of the College of Art Media and Technology students has been classified into three service groups.Originality/value–This combined prioritized techniques can involve learners in the decision making process about learning cloud services utilization in the organizations.

An Evolution, Present, and Future Changes of Cloud Computing Services

This study presents a clear evolution of computing and its key applications. Cloud computing services evolved from distributed, grid, and utility computing. Critical companies such as Salesforce,Amazon, Google, and Microsoft play important roles in cloud computing. Dramatic changes in the technology environment have created new challenges for current information technologies. This study discusses four significant challenges for cloud computing services,including the next-generation Internet, data synchronization, cloud security, and competitive advantages.And then it also discusses how managers can learn about the future of cloud computing services.

Cloud Datacenter Selection Using Service Broker Policies:A Survey

Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin in CC’s performance,the Cloud Service Broker(CSB),orchestrates DC selection.Failure to adroitly route user requests with suitable DCs transforms the CSB into a bottleneck,endangering service quality.To tackle this,deploying an efficient CSB policy becomes imperative,optimizing DC selection to meet stringent Qualityof-Service(QoS)demands.Amidst numerous CSB policies,their implementation grapples with challenges like costs and availability.This article undertakes a holistic review of diverse CSB policies,concurrently surveying the predicaments confronted by current policies.The foremost objective is to pinpoint research gaps and remedies to invigorate future policy development.Additionally,it extensively clarifies various DC selection methodologies employed in CC,enriching practitioners and researchers alike.Employing synthetic analysis,the article systematically assesses and compares myriad DC selection techniques.These analytical insights equip decision-makers with a pragmatic framework to discern the apt technique for their needs.In summation,this discourse resoundingly underscores the paramount importance of adept CSB policies in DC selection,highlighting the imperative role of efficient CSB policies in optimizing CC performance.By emphasizing the significance of these policies and their modeling implications,the article contributes to both the general modeling discourse and its practical applications in the CC domain.

Information Security in the Cloud: Emerging Trends and Challenges

This article explores the evolution of cloud computing, its advantages over traditional on-premises infrastructure, and its impact on information security. The study presents a comprehensive literature review covering various cloud infrastructure offerings and security models. Additionally, it deeply analyzes real-life case studies illustrating successful cloud migrations and highlights common information security threats in current cloud computing. The article concludes by offering recommendations to businesses to protect themselves from cloud data breaches and providing insights into selecting a suitable cloud services provider from an information security perspective.

Cloud service performance evaluation： status, challenges, and opportunities - a survey from the system modeling perspective

With rapid advancement of Cloud computing and networking technologies, a wide spectrum of Cloud services have been developed by various providers and utilized by numerous organizations as indispensable ingredients of their information systems. Cloud service performance has a significant impact on performance of the future information infrastructure. Thorough evaluation on Cloud service performance is crucial and beneficial to both service providers and consumers; thus forming an active research area. Some key technologies for Cloud computing, such as virtualization and the Service-Oriented Architecture （SOA）, bring in special challenges to service performance evaluation. A tremendous amount of effort has been put by the research community to address these challenges and exciting progress has been made. Among the work on Cloud performance analysis, evaluation approaches developed with a system modeling perspective play an important role. However, related works have been reported in different sections of the literature; thus lacking a big picture that shows the latest status of this area. The objectives of this article is to present a survey that reflects the state of the art of Cloud service performance evaluation from the system modeling perspective. This articles also examines open issues and challenges to the surveyed evaluation approaches and identifies possible opportunities for future research in this important field.

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.

Analysis on Key Technology of ＂Cloud Computing＂

This paper introduces the background of cloud computing, takes analysis of key technology, analysis of cloud computing and traditional competitive intelligence information model for comparative study, for the security of cloud computing, function and service of the following aspects to elaborate, to explore the influence of cloud computing on the information.

Network Access Mechanisms and Security Issues under the Cloud Service Architecture

Currently, under the cloud service architecture, the increasing importance of network security and security issues are still emerging. With the rapid development of the network platform, it is connected to the number and size of the trusted computing environment for all kinds of applications that are rapidly expanding, ever-changing network health, network time being emergencies, assault, failure, threat of disaster, its safety, survivability and availability of face serious challenges. Although TNC Working Group made safe and reliable framework from the network access layer, it is not at the level of user access, system access levels and further given the level of situational awareness and effective solutions.

Enhancing Reliability via Checkpointing in Cloud Computing Systems

Cloud computing is becoming an important solution for providing scalable computing resources via Internet. Because there are tens of thousands of nodes in data center, the probability of server failures is nontrivial. Therefore, it is a critical challenge to guarantee the service reliability. Fault-tolerance strategies, such as checkpoint, are commonly employed. Because of the failure of the edge switches, the checkpoint image may become inaccessible. Therefore, current checkpoint-based fault tolerance method cannot achieve the best effect. In this paper, we propose an optimal checkpoint method with edge switch failure-aware. The edge switch failure-aware checkpoint method includes two algorithms. The first algorithm employs the data center topology and communication characteristic for checkpoint image storage server selection. The second algorithm employs the checkpoint image storage characteristic as well as the data center topology to select the recovery server. Simulation experiments are performed to demonstrate the effectiveness of the proposed method.

Prediction of Cloud Ranking in a Hyperconverged Cloud Ecosystem Using Machine Learning

Cloud computing is becoming popular technology due to its functional properties and variety of customer-oriented services over the Internet.The design of reliable and high-quality cloud applications requires a strong Quality of Service QoS parameter metric.In a hyperconverged cloud ecosystem environment,building high-reliability cloud applications is a challenging job.The selection of cloud services is based on the QoS parameters that play essential roles in optimizing and improving cloud rankings.The emergence of cloud computing is significantly reshaping the digital ecosystem,and the numerous services offered by cloud service providers are playing a vital role in this transformation.Hyperconverged software-based unified utilities combine storage virtualization,compute virtualization,and network virtualization.The availability of the latter has also raised the demand for QoS.Due to the diversity of services,the respective quality parameters are also in abundance and need a carefully designed mechanism to compare and identify the critical,common,and impactful parameters.It is also necessary to reconsider the market needs in terms of service requirements and the QoS provided by various CSPs.This research provides a machine learning-based mechanism to monitor the QoS in a hyperconverged environment with three core service parameters:service quality,downtime of servers,and outage of cloud services.

A rapid, low-cost deep learning system to classify strawberry disease based on cloud service

Accurate and timely classification of diseases during strawberry planting can help growers deal with them in timely manner, thereby reducing losses. However, the classification of strawberry diseases in real planting environments is facing severe challenges, including complex planting environments, multiple disease categories with small differences, and so on. Although recent mobile vision technology based deep learning has achieved some success in overcoming the above problems, a key problem is how to construct a non-destructive, fast and convenient method to improve the efficiency of strawberry disease identification for the multi-region, multi-space and multi-time classification requirements. We develop and evaluate a rapid, low-cost system for classifying diseases in strawberry cultivation. This involves designing an easy-to-use cloudbased strawberry disease identification system, combined with our novel self-supervised multi-network fusion classification model, which consists of a Location network, a Feedback network and a Classification network to identify the categories of common strawberry diseases. With the help of a novel self-supervision mechanism, the model can effectively identify diseased regions of strawberry disease images without the need for annotations such as bounding boxes. Using accuracy, precision, recall and F1 to evaluate the classification effect, the results of the test set are 92.48, 90.68, 86.32 and 88.45%, respectively. Compared with popular Convolutional Neural Networks(CNN) and five other methods, our network achieves better disease classification effect. Currently, the client(mini program) has been released on the We Chat platform. The mini program has perfect classification effect in the actual test, which verifies the feasibility and effectiveness of the system, and can provide a reference for the intelligent research and application of strawberry disease identification.

Research on Trust Model in Container-Based Cloud Service

Container virtual technology aims to provide program independence and resource sharing.The container enables flexible cloud service.Compared with traditional virtualization,traditional virtual machines have difficulty in resource and expense requirements.The container technology has the advantages of smaller size,faster migration,lower resource overhead,and higher utilization.Within container-based cloud environment,services can adopt multi-target nodes.This paper reports research results to improve the traditional trust model with consideration of cooperation effects.Cooperation trust means that in a container-based cloud environment,services can be divided into multiple containers for different container nodes.When multiple target nodes work for one service at the same time,these nodes are in a cooperation state.When multi-target nodes cooperate to complete the service,the target nodes evaluate each other.The calculation of cooperation trust evaluation is used to update the degree of comprehensive trust.Experimental simulation results show that the cooperation trust evaluation can help solving the trust problem in the container-based cloud environment and can improve the success rate of following cooperation.