Design Architecture-Based on Web Server and Application Cluster in Cloud Environment

Cloud has been a computational and storage solution for many data centric organizations. The problem today those organizations are facing from the cloud is in data searching in an efficient manner. A framework is required to distribute the work of searching and fetching from thousands of computers. The data in HDFS is scattered and needs lots of time to retrieve. The major idea is to design a web server in the map phase using the jetty web server which will give a fast and efficient way of searching data in MapReduce paradigm. For real time processing on Hadoop, a searchable mechanism is implemented in HDFS by creating a multilevel index in web server with multi-level index keys. The web server uses to handle traffic throughput. By web clustering technology we can improve the application performance. To keep the work down, the load balancer should automatically be able to distribute load to the newly added nodes in the server

Experimental setup for investigating the efficient load balancing algorithms on virtual cloud

Cloud computing has emerged as the primary choice for developers in developing applications that require high-performance computing. Virtualization technology has helped in the distribution of resources to multiple users. Increased use of cloud infrastructure has led to the challenge of developing a load balancing mechanism to provide optimized use of resources and better performance. Round robin and least connections load balancing algorithms have been developed to allocate user requests across a cluster of servers in the cloud in a time-bound manner. In this paper, we have applied the round robin and least connections approach of load balancing to HAProxy, virtual machine clusters and web servers. The experimental results are visualized and summarized using Apache Jmeter and a further comparative study of round robin and least connections is also depicted. Experimental setup and results show that the round robin algorithm performs better as compared to the least connections algorithm in all measuring parameters of load balancer in this paper

Implementing a dynamic scaling of web applications in a virtualized cloud computing environment

Cloud computing is becoming more essential day by day. The allure of the cloud is the significant value and benefits that people gain from it, such as reduced costs, increased storage, flexibility, and more mobility. Flexibility is one of the major benefits that cloud computing can provide in terms of scaling up and down the infrastructure of a network. Once traffic has increased on one server within the network, a load balancer instance will route incoming requests to a healthy instance, which is less busy and less burdened. When the full complement of instances cannot handle any more requests, past research has been done by Chieu et. al. that presented a scaling algorithm to address a dynamic scalability of web applications on a virtualized cloud computing environment based on relevant indicators that can increase or decrease servers, as needed. In this project, I implemented the proposed algorithm, but based on CPU Utilization threshold. In addition, two tests were run exploring the capabilities of different metrics when faced with ideal or challenging conditions. The results did find a superior metric that was able to perform successfully under both tests

Designing a VM-level vertical scalability service in current cloud platforms: A new hope for wearable computers

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Public clouds are becoming ripe for enterprise adoption. Many companies, including large enterprises, are increasingly relying on public clouds as a substitute for, or a supplement to, their own computing infrastructures. On the other hand, cloud storage service has attracted over 625 million users. However, apart from the storage service, other cloud services, such as the computing service, have not yet attracted the end users’ interest for economic and technical reasons. Cloud service providers offers horizontal scalability to make their services scalable and economical for enterprises while it is still not economical for the individual users to use their computing services due to the lack of vertical scalability. Moreover, current virtualization technologies and operating systems, specifically the guest operating systems installed on virtual machines, do not support the concept of vertical scalability. In addition, network remote access protocols are meant to administer remote machines but they are unable to run the non-administrative tasks such as playing heavy games and watching high quality videos remotely in a way that makes the users feel as if they are sitting locally on their personal machines. On the other hand, the industry is yet unable to make efficient wearable computers a reality due to the limited size of the wearable devices, where it is infeasible to place efficient processors and big enough hard disks. This paper aims to highlight the need for the vertical scalability service and design the appropriate cloud, virtualization layer, and operating system services to incorporate vertical scalability in current cloud platforms in a way that will make it economically and technically efficient for the end users to use cloud virtual machines as if they are using their personal laptops. Through these services, the cloud takes wearable computing to the next stage and makes wearable computers a reality

Database for LnL

This project originally sought to replace LnL’s Perl web based database system with a more modern Java MVC Servlet solution. Complications in the original project resulted in this project morphing into an analysis of the differences in web based technologies between 1995, 2008, and 2017. This project analyzes the differences in technologies over a twenty-two year period, with a special emphasis on the programming languages used, processing models, and decisions about hosting locations

Cooperative resource management in the cloud

L’évolution des infrastructures informatiques encourage la gestion séparée de l’infrastructure matérielle et de celle des logiciels. Dans cette direction, les infrastructures de cloud virtualisées sont devenues trés populaires. Parmi les différents modèles de cloud, les Infrastructures as a Service (IaaS) ont de nombreux avantages pour le fournisseur comme pour le client. Dans ce modèle de cloud, le fournisseur fournit ses ressources virtualisées et il est responsable de la gestion de son infrastructure. De son coté, le client gère son application qui est déployée dans les machines virtuelles allouées. Ces deux acteurs s’appuient généralement sur des systèmes d’administration autonomes pour automatiser les tâches d’administration. Réduire la quantité de ressources utilisées (et la consommation d’énergie) est un des principaux objectifs de ce modèle de cloud. Cette réduction peut être obtenue à l’exécution au niveau de l’application par le client (en redimensionnant l’application) ou au niveau du système virtualisé par le fournisseur (en regroupant les machines virtuelles dans l’infrastructure matérielle en fonction de leur charge). Dans les infrastructures de cloud traditionnelles, les politiques de gestion de ressources ne sont pas coopératives : le fournisseur ne possède pas d’informations détaillées sur les applications. Ce manque de coordination engendre des surcoûts et des gaspillages de ressources qui peuvent être réduits avec une politique de gestion de ressources coopérative. Dans cette thèse, nous traitons du problème de la gestion de ressources séparée dans un environnement de cloud virtualisé. Nous proposons un modèle de machines virtuelles élastiques avec une politique de gestion coopérative des ressources. Cette politique associe la connaissance des deux acteurs du cloud afin de réduire les coûts et la consommation d’énergie. Nous évaluons les bénéfices de cette approche avec plusieurs expériences dans un IaaS privé. Cette évaluation montre que notre politique est meilleure que la gestion des ressources non coordonnée dans un IaaS traditionnel, car son impact sur les performances est faible et elle permet une meilleure utilisation des ressources matérielles et logicielles. ABSTRACT : Recent advances in computer infrastructures encourage the separation of hardware and software management tasks. Following this direction, virtualized cloud infrastructures are becoming very popular. Among various cloud models, Infrastructure as a Service (IaaS) provides many advantages to both provider and customer. In this service model, the provider offers his virtualized resource, and is responsible for managing his infrastructure, while the customer manages his application deployed in the allocated virtual machines. These two actors typically use autonomic resource management systems to automate these tasks at runtime. Minimizing the amount of resource (and power consumption) in use is one of the main services that such cloud model must ensure. This objective can be done at runtime either by the customer at the application level (by scaling the application) or by the provider at the virtualization level (by migrating virtual machines based on the infrastructure’s utilization rate). In traditional cloud infrastructures, these resource management policies work uncoordinated: knowledge about the application is not shared with the provider. This behavior faces application performance overheads and resource wasting, which can be reduced with a cooperative resource management policy. In this research work, we discuss the problem of separate resource management in the cloud. After having this analysis, we propose a direction to use elastic virtual machines with cooperative resource management. This policy combines the knowledge of the application and the infrastructure in order to reduce application performance overhead and power consumption. We evaluate the benefit of our cooperative resource management policy with a set of experiments in a private IaaS. The evaluation shows that our policy outperforms uncoordinated resource management in traditional IaaS with lower performance overhead, better virtualized and physical resource usage

Adapting Microservices in the Cloud with FaaS

This project involves benchmarking, microservices and Function-as-a-service (FaaS) across the dimensions of performance and cost. In order to do a comparison this paper proposes a benchmark framework

Supply Chain (micro)TMS development

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThe rise of technology across many verticals has necessitated the company’s move to digitalization. Despite “XPTO” company a well know player on the retail and success on e‐commerce internal market, they aimed at the strategy of continuous innovation to drive business growth and strengthen their position as a premium brand. They decided to move forward into digitalism inside cloud based solutions to get all the advantages of microservices architecture: optimize logistics and supply chain management, speed up the workflow and maximize service efficiency. An agile organization is not achieved purely by shifting the focus from traditional functional/ technological oriented organizations. The new way to organize teams must reflect all the principles and right segregations of roles, which will be the most immediate and visible disruption and cutover from the traditional way of managing the IT. In this project we aim to use agile framework with development based in house cloud microservice solution for a (micro)TMS solution/system that address the immediate needs imposed by the market in order to use it has competitive advantage