Abstract: The design of analog electronics learning media applications needs quality analysis. ISO 25010 is one of the standard references in measuring the quality of an Android-based application product. Analysis that can be done is by testing the compatibility and performance efficiency aspect of the media being developed. This study uses a Research and Development (R&D) method with the ADDIE development model which will produced a quality analog electronics learning media application. Data collection was conducted used a cloud testing and direct testing. Before data collection was conducted validity of media by expert judgement. The results showed that media is "valid" and the quality of the compatibility aspect this media learning was supported on more than 208 smartphones android device and performance efficiency predicate “Satisfied” so that the application could be used for the learning process during the COVID-19 pandemic or tested on other quality aspects.

Abstract: Cloud computing is a technological commitment that allows it to achieve a set goal, improving business performance. Cloud computing offers many applications like scalability, extensive infrastructure, storage, resource pooling, virtualization, and a wide range of online services. Cloud service providers provide a variety of technologies to cloud computing users all the time. Load balancing algorithms are used to improve the performance and speed of nodes in cloud environments and protect each device from affecting their threshold by reducing their performance. Classification of load balancing algorithms was based on two factors, i.e., the state of the system and the person who initiated the process. The dynamic load balancing algorithms are based on challenges like high availability, scalability, fault tolerance, virtual machine migration, low response time. Dynamic load balancing algorithms apply some policies because they use the current state of a system. This paper describes the study of the different dynamic load balancing algorithms in the cloud environment, as well as their comparison, which is based on different load balancing systems.

Abstract: Cloud computing is an on-demand service where customers may access any time common IT resources, information, software and other equipment. It is a web-based development that offers virtual resources over the Internet as a service. The higher the cloud use, the higher the charge. The allocation of loads to components processing is a challenging phenomenon. In a multi-node system, there is a very good possibility that some nodes will be idle while others will be overloaded. The load balancing algorithms' objective is to keep the load on each processing element constant. Cloud computing [1] gives omnipresent access to shared pools of customized system resources and superior services which may be delivered quickly, often through the Internet, with minimizing management efforts. Like a public service, cloud computing relies on the pooling of resources to create coherence and economies of scale.Figure 1 depicts a generic cloud computing paradigm. Third-party clouds allow firms to focus on their core competencies rather than on computer infrastructure and upkeep. Cloud computing, according to proponents, allows businesses to avoid or reduce upfront IT infrastructure expenditures. Cloud computing [2] supporters also say that it enables companies to get their applications up and running faster, with greater management and less maintenance, and that it enables IT staff to more quickly change resources to meet changing and unexpected demand. Figure 1: Cloud Computing ModelCloud providers usually employ a "pay-as-you-go" approach, which might result in unanticipated operational costs if administrators are unfamiliar with cloud-pricing methods.Cloud load balancing [3] [4] [5] is the technique used to dissimulate demands among different computing resources. Each job should be planned correctly in order to balance the load so that each user gets service within the quickest time. Round robin, ant-colony optimization, particle swarm optimization, max min, min-min, and others are all load balancing methods.A technique for Random Load Balancing in Cloud Computing is devised, in which the amount of user requests is instantly assigned to the resources. This method employs a random strategy to decrease the request's waiting time. This proposed load balancing technique is simulated in Cloud Analyst tool. The performance comparison study between proposed random method and other available load balancing methods is conducted. It is found that the performance of proposed random method is better in terms of response time.

Abstract: Σε αυτήν την εργασία αναλύεται το Cloud Computing, οι υπηρεσίες που προσφέρει, και οι πάροχοι τέτοιων υπηρεσιών που υπάρχουν σήμερα, καθώς και τα συστήματα διαχείρισης περιεχομένου (Content Management Systems), και τα συστήματα Web CMS ή WCMS. Έπειτα παρουσιάζεται η έρευνα που υπάρχει αυτή τη στιγμή για τις υπηρεσίες του Cloud Computing, για τα CMS, αλλά και για τη χρήση των υπηρεσιών του Cloud Computing στα CMS. Στη συνέχεια, αφού αξιολογείται η υπάρχουσα κατάσταση, παρουσιάζεται η πρόταση της χρήσης των υπηρεσιών Cloud για τον εμπλουτισμό των υπαρχόντων συστημάτων CMS, και όχι η εξ ολοκλήρου μετάβαση σε υπηρεσίες Cloud. Για την απόδειξη της προτεινόμενης πρότασης, αναπτύχθηκε το πρωτότυπο πρόσθετο (plugin) Kumori για το σύστημα WCMS WordPress, με τη χρήση της γλώσσας PHP, το οποίο χρησιμοποιεί τις υπηρεσίες Cloud της Amazon Web Services για τη μετατροπή αρχείων βίντεο, επιδεικνύοντας έτσι τη δυνατότητα χρήσης των υπηρεσιών Cloud στα συστήματα CMS.

Abstract: Cloud computing rapidly surpassed the phase of initial adoption and quickly gains momentum on the market of information technologies. Companies, startups and regular users leverage the cloud to avoid infrastructure or middleware costs, to gain flexibility in computing usage and to obtain unlimited computational or storage resources available on demand. However, along with cloud computing's benefits, new challenges arrived. In order to achieve the advantages of the cloud, developers have to redesign their existing applications and build new ones with scalability and elasticity in mind. Additionally, as the market of cloud providers developed, two competing application development paradigms emerged. When bringing an application to the cloud, developers have to decide if they follow the Infrastructure as a Service model, which provides flexibility and software architecture freedom, or the Platform as a Service model that offers a higher level of abstraction and a simpler application development process. This thesis addresses emerging cloud computing challenges presenting a transparent application distribution approach based on the JCloudScale middleware. The described cloud application development approach hides boilerplate cloud interaction code from developers and allows focusing on the business logic of the application instead. Providing benefits common to Platform as a Service solutions, the discussed approach allows keeping flexibility and freedom that is missing in alternatives. However, this approach brings in a set of distinctive challenges, that are targeted in this work. To solve the issue of transparent application code integrity and synchronization, a solution for seamless code distribution was built. To simplify the complexity of elastic application management, a scaling definition language based on complex event processing application architecture was designed. Finally, targeting effective cloud resource usage, a profiling-based task scheduling solution was proposed. Each solution and framework, presented in this thesis, denote the steps on the ongoing road to achieve the declared goal of transparent cloud application distribution. Developed approaches and solutions were thoroughly validated using accomplished user studies and performance evaluations. The obtained results show that the presented transparent cloud application development approach is appealing to developers, increases productivity and simplifies cloud migration or cloud application construction without significant performance costs.

Abstract: <p><span>Because cloud computing offers cost-effectiveness, scalability, and on-demand access to computer resources, it has completely changed how businesses handle these resources. The data storage services provided by the main cloud platforms, containerization technologies for application deployment, continuous integration and deployment (CI/CD) procedures, and testing and maintenance techniques in cloud environments are just a few of the aspects of cloud computing strategies that are examined in this research paper. The first section of the article evaluates and discusses the capabilities, use cases, and selection criteria of the database and storage services offered by Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP). After that, it explores containerization technologies like Docker and Kubernetes, which make it easier to package, launch, and manage cloud applications. In addition, the study looks at best practices, technologies, and ideas related to continuous integration and delivery (CI/CD), highlighting the value of automating software delivery pipelines for accelerated time-to-market, enhanced teamwork, and dependable deployments. It also looks at different approaches, techniques, tools, logging, monitoring, scalability issues, and maintenance procedures specific to cloud-based apps.</span></p>

Abstract: Cloud computing has become increasingly popular amongst organizations as a cost-effective solution to serve large-scale applications. Cloud deployments, however, are undermined by a fundamental disconnect between the software development process and the cloud environment: testing of applications on the cloud is expensive, and poorly optimized software often results in poor performances and functional issues when scaled up in the cloud. In this scenario, cloud simulators are promising tools that let engineers and researchers test applications and novel algorithms using limited resources. Current state of the art simulators, such as CloudSim, leverage outdated software frameworks that force developers to go through a steep learning-curve and did not keep up with the scale of today’s real-world deployments which involve thousands of servers distributed across multiple regions. This work addresses the shortcomings of current cloud simulation tools and introduces a novel, distributed, scalable, and extensible cloud simulation framework: CAST. CAST brings cloud simulations to the cloud by leveraging the actor model to distribute computation efficiently. Moreover we designed CASTDSL, a declarative language that allows engineers to write simulations by providing their high-level description.

Abstract: Cloud computing has become increasingly popular amongst organizations as a cost-effective solution to serve large-scale applications. Cloud deployments, however, are undermined by a fundamental disconnect between the software development process and the cloud environment: testing of applications on the cloud is expensive, and poorly optimized software often results in poor performances and functional issues when scaled up in the cloud. In this scenario, cloud simulators are promising tools that let engineers and researchers test applications and novel algorithms using limited resources. Current state of the art simulators, such as CloudSim, leverage outdated software frameworks that force developers to go through a steep learning-curve and did not keep up with the scale of today’s real-world deployments which involve thousands of servers distributed across multiple regions. This work addresses the shortcomings of current cloud simulation tools and introduces a novel, distributed, scalable, and extensible cloud simulation framework: CAST. CAST brings cloud simulations to the cloud by leveraging the actor model to distribute computation efficiently. Moreover we designed CASTDSL, a declarative language that allows engineers to write simulations by providing their high-level description.