Investigations into elasticity in cloud computing

Modern software engineering tools, technologies and approaches can radically speed up the development and engineering of multi-tier cloud applications and may be applied to the cloud/edge/fog computing paradigm. The engineering of such cloud applications must take into account Non-Functional Requirements (NFRs), such as end-user, software and cloud infrastructure requirements for low-power computing, performance, availability, elasticity, operational cost and similar. Such requirements should be identified and considered early in the software engineering process and decisions must be taken on their trade-offs, e.g. greater service availability while balancing operational costs. This paper introduces a new multi-criteria decision making approach via the use of the Pareto method to aid the software engineers with NFR trade-off adjustment possibilities. Adjustment possibilities may include geographic distribution of application tiers, horizontal and vertical scaling of virtual resources (such as Virtual Machines and containers) and similar. This work builds on top of technologies and tools developed under the SWITCH and ENTICE projects. The impact of this approach is the ability to fully tailor the adjustments of non-functional properties of the multi-tier cloud application according to the decisions of its engineer. An early warning system cloud application is used to present the approach.

With the advent of cloud computing, different cloud providers with heterogeneous cloud services (compute, storage, network, applications, etc.) and their related Application Programming Interfaces (APIs) have emerged. This heterogeneity complicates the implementation of an interoperable cloud system. Several standards have been proposed to address this challenge and provide a unified interface to cloud resources. The Open Cloud Computing Interface (OCCI) thereby focuses on the standardization of a common API for Infrastructure-as-a-Service (IaaS) providers, while the Topology and Orchestration Specification for Cloud Applications (TOSCA) focuses on the standardization of a template language to enable the proper definition of the topology of cloud applications and their orchestrations on top of a cloud system. TOSCA thereby does not define how the application topologies are created on the cloud. Therefore, we analyze the conceptual similarities between the two approaches and we study how we can integrate them to obtain a complete standard-based approach to manage both Cloud Infrastructure and Cloud application layers. We propose an automated extensive mapping between the concepts of the two standards, and we provide TOSCA Studio, a model-driven tool chain for TOSCA that conforms to OCCI. TOSCA Studio allows to graphically design cloud applications as well as to deploy and manage them at runtime using a fully model-driven cloud orchestrator based on the two standards. Our contribution is validated by successfully transforming and deploying three cloud applications: WordPress, Node Cellar and Multi-Tier.

A cloud environment is a complex environment composed of many different entities and layers. Each of these cloud entities may be furnished with mechanisms offering various management actions. For any given situation, different management actions may be applicable and often simultaneously. Enforcing isolated management actions or combining contradictory management actions may negatively affect cloud application quality and cloud infrastructure performance. This means that correctly selecting and effectively combining these management actions for a given situation becomes an important challenge in cloud computing. In this paper, we address the problem of identifying situations where more than one management action can be performed. The key contributions of our paper are: (1) a three dimensional (3-D) monitoring model for analyzing cloud monitoring information; (2) the concept and formalization of Context of Interest (CoI) that specifies how to retrieve meaningful information from the 3-D model to support the coordination of management actions between cloud infrastructure and application. We conducted experiments in a real testbed using Openstack and the WordPress Web site application. Our results show that analyzing cloud monitoring information using the 3-D model and the CoI can support a more effective identification of management actions to be taken.

Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud-infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

Cloud computing and big data: Technologies and applications

In Healthcare big data, data is originated from various heterogeneous sources. Numerous novel base particular healthcare applications offered to handling source of data from electronic health record (EHR) to medical images. Imaging, Electronic Health Report, technology in light of sensor and numerous different procedures created an immense measure of Healthcare data. Cloud computing development was an excellent paradigm to substantiate big data which incited find of imperceptible examples. Cloud computing is a developing new registering design intended to answer different contending administrations on the Web. Fog Computing is a design style in which arrange segments amongst devices and the cloud execute application-particular rationale. We in this paper investigate, characterize, and talk about various application of cloud and fog computing. We talk about the impact of cloud computing and fog computing on healthcare big data. Cloud base framework for Homediagnosis Service, Fog computing architecture and the justification of moving from cloud to Fog presented comprehensively in this paper.

The focal point of this research maneuvers over the challenges and threats that are continuously being faced in cloud computing. Cloud computing is considered as one of the most versatile technology in the recent years. It is an innovative approach towards Information Systems and it has become an integral part of the IT industry. The paper aims to highlight the seriousness of the threats and challenges encountered in cloud computing. In this paper, we give an overview on what makes this technology the future of computing. Immense literature study was conducted to gather adequate data on the recent techniques and terminologies related to the research field. An in-depth research analysis presents a competent mechanism that identifies the challenges and threats in cloud computing. The paper also refers to different security breaches that occurred over the years and what measures were taken to overcome the catastrophic loss. Along with that, it also caters the alternative strategies and approaches available to overcome the possible security threats and challenges. Different alternative methods such as Cryptography and Access Control Mechanisms are identified which are feasible and can be utilized for enhancing the security in cloud computing. Cloud computing is no doubt growing in popularity but even the immensity of this technology cannot disguise the security issues that linger with it. After thoroughly investigating and inspecting all the literary resources, gathered data and information, it is discovered that although cloud computing is tremendously gaining its popularity in the IT field, concerns about its security impact have also been raised considerably. The conclusion of this paper provides different strategies to be adopted to condense the effect of security challenges in the chosen area of the research. Keywords: Access Control, Cloud Application, Cloud Computing, Challenges, Cryptography, Data Portability, Information System, Interoperability, PaaS, SaaS, Security, Threats, Virtualization;

Cloud computing is a fast-growing paradigm that has forcefully emerged and established itself in the next generation of IT industry and business, performing massive-scale and complex computing. As cloud technology adoption continues to progress, massive growth in the scale of data generated through cloud computing has been observed. A large part of that data has been machine-generated log data; it is generated at every layer and component within the cloud information technology ecosystem that spans a range of IT functions from storage and computation to networking and application services. Log files are essential for enterprise-level monitoring, troubleshooting, security, debugging, compliance, etc. We argue that cloud computing is in need of a new methodology for recording, managing, storing and analyzing the log data that is generated by the cloud infrastructure, based on big data technologies, allowing for the access to a wealth of knowledge that can contribute to its own advancement. Our paper discusses and expands existing standard log management solutions to design new methods of exploiting the unstructured log data in order to gain unprecedented insights.

The issue of acquiring large amounts of data and creating large sets of digital data, and then processing and analyzing them (Big Data) for the needs of generating artificial intelligence (AI) solutions is one of the key challenges to the development of economy and national security. Data have become a resource that will determine the power and geopolitical and geoeconomic position of countries and regions in the 21st century.The layout of data storage and processing in distributed databases has changed in recent years. Since the appearance of hosting services in the range of ICT services, we are talking about a new type of ASP (Applications Service Providers) – provision of the ICT networks as part of an application). Cloud Computing is therefore one of the versions of the ASP services. The ASP guarantees the customer access to a dedicated application running on a server. Cloud Computing, on the other hand, gives the opportunity to use theresources of a shared infrastructure for many users simultaneously (Murphy n.d.). The use of the CC model is more effective in many aspects. Cloud Computing offers the opportunity to use three basic services: data storage in the cloud (cloud storage), applications in the cloud (cloud applications) and computing in the cloud (compute cloud). Website hosting and electronic mail are still the most frequently chosen services in Cloud Computing. The article attempts to explain the responsibility for content stored in the Cloud Computing.

The deployment of component-based applications in cloud systems environment is becoming more and more complex. It is expected to provide elasticity in order to allow a deployed application to scale dynamically and meet variation in demand while ensuring a certain level of quality of service (QoS). However, there are still some open issues associated with the elasticity management. A conceptual model of elasticity management enabling the description of deployment and application constraints, properties and elasticity strategies at different levels (depending on the internal application architecture or on the cloud infrastructure and platform) in an automatic way is needed. In this paper, we propose a domain specific language (DSL) based on a metamodel, which precisely specifies three main views: the cloud service models, the automatic elasticity management strategies and the internal cloud application architecture. We illustrate through a case study, the MAPE-K-based approach using different scenarios of automatic elasticity management.

With ever increasing usage of IT infrastructure around the globe, the increase in energy consumption and carbon emission is a worrisome situation for everyone because of its direct effect on environment. The environment is being dangerously impacted by Information Technology infrastructure extensive use and its waste. Cloud computing has emerged as one step further solution to deploy all virtualized IT resources as per need on self-service basis as a rental method for the users. Different cloud deployment methods have emerged according to the need of users, institutions and communities. In last decade virtualization has been a milestone in enabling optimal usage of information technology resources. Cloud computing has provided a platform for deploying everything as a Service in IT, which has changed the economics of IT based business and organizations from Capital Expenditure to Operational Expenditure. For enabling Cloud services we first need to understand our existing infrastructure. In second step we should be able to virtualize it for optimal usage. Then with the help of existing cloud applications we can deliver and deploy information technology as a resource at various levels such as infrastructure, platform, and software. Keywords; cloud computing, carbon emission, energy consumption, IT waste, virtualization. The Advancement in the field of information technology has enabled us to optimize the use of physical infrastructure with the help of virtualization, most of which is only used in specific applications like vitalizing a local area network on switch or vitalizing a compute resource to run more than one operating system on a desktop. The benefits of same has not been completely implemented and utilized in industrial environments where we require a large amount of IT resources. The advantage of using cloud is to enable complete utilization of Information technology resources, where most of the resources are underutilized. The cost involved in maintenance and management of those resources is huge which can be saved due to centralized management of private cloud infrastructure. We create private cloud keeping in mind. • Availability and performance requirements for the cloud • Infrastructure sizing, performance and continual availability requirements • The need for data security or isolation • The appropriate user interface With advent of IT as a service in cloud computing technology energy consumption and related carbon emissions and waste are considerably lesser than in-house implementation. Technology in Cloud Computing creates an able structure for sharing resources with the help of virtualization among many; it greatly decreases or abolishes the need for most products, equipment, utilities and facilities. The results are more sustainable IT infrastructures and processes which help in keeping environment safe. • Highest resource consumption and effectiveness • Reduced energy consumption by up to 95 % with the help of virtualization which optimizes the use of physical infrastructure and thereby helps IT to be delivered as a service. • Displaced utility costs Workstation utility costs are cut by 90% due to change of capital expenditure into operational expenditure in industries or organizations across the world. • Reduced electronic waste as No more batteries and minimal software/hardware waste. • Reduced waste overall due to consumption of computational power as service, no more as infrastructure. • Reduced ecological impact of workstations as compared to thin clients as anything related to computation can be provided as a service on a client connected with internet to the cloud provider.

Recent advances in virtualization technology and wide acceptance of the cloud computing model are having significant impact on the software service industry. Though cloud computing and virtualization technology has been widely applied in supporting the information processing needs of conventional enterprise and business applications, there has been little success to-date in enabling realtime 3D virtual appliances in the cloud. This paper aims to address this deficiency by presenting SHARC, a solution for enabling scalable support of realtime 3D applications in a cloud computing environment. The solution uses a scalable pipelined processing infrastructure which consists of three processing networks according to the principle of division-of-labor, a virtualization server network for running 3D virtual appliances, a graphics rendering network for processing graphics rendering workload with load balancing, and a media streaming network for transcoding rendered frames into H.264/MPEG-4 media streams and streaming the media streams to a cloud user. The paper describes a prototype implementation of SHARC and reports test results that demonstrate the viability of this approach.

Cloud computing can describe on-demand administration and prerequisite of resources, and information as services on the cloud. The dynamic environment of the cloud causes various unexpected obstacles. The ability of a system to respond normally to unexpected equipment and programming fault is called fault tolerance. In order to realize robustness and reliability in cloud computing, it is necessary to evaluate and process obstacles effectively. Various fault detection methods and architecture models have been proposed to increase the fault tolerance capability of the cloud. Consider the fact, this paper has been paying attention on solving the problem of faults in the cloud computing. This research has conducted to outline the work that has been done in this field which represents the basic concept of fault tolerance developed by different researchers and various algorithms used to resolve the fault tolerance problem in cloud computing.

Cloud Computing is a model based on computing system which provides convenient and customizable services to the users for accessing to different cloud applications. It provides a way for storing and accessing cloud data from anywhere via connecting the cloud application utilizing internet. The cloud computing and its related safety problems is one of widely discussed concerns in today generation's research field. While numerous cloud security investigations are previously widespread, there residues a definite distance in properly identifying these issues and find the appropriate solutions. Some studies discuss the problems of virtualization and approach the target, while others talk about access control mechanisms, but what's missing is a standard framework which simultaneously extends the concept of cloud security and describes its specific requirements. In addition, countermeasures given in a survey must clearly illustrate the problem it deals with. This analysis paper took all of these elements into consideration so that the necessary areas were properly connected and a number of open issues were discussed in this area. This paper also reviews the most significant security techniques to data protection and cloud security in the cloud computing. Moreover, security techniques for data protection will be recommended in order to have enhanced security in cloud computing. It will concentrate primarily on issues related to data security and provides solutions.

As a direct consequence of the increasing popularity of Cloud Computing solutions, data centers are amazingly growing and hence have to urgently face with the energy consumption issue. Available solutions rely on Cloud Computing models and virtualization techniques to scale up/down application based on their performance metrics. Although those proposals can reduce the energy footprint of applications and by transitivity of cloud infrastructures, they do not consider the internal characteristics of applications to finely define a trade-off between applications Quality of Service and energy footprint. In this paper, we propose a self-adaptation approach that considers both application internals and system to reduce the energy footprint in cloud infrastructure. Each application and the infrastructure are equipped with their own control loop, which allows them to autonomously optimize their executions. Simulations show that the approach may lead to appreciable energy savings without interfering on application provider revenues.