Infrastructure As A Service Research Articles

Cloud Infrastructure and Enterprise IT Environment

Cloud infrastructure has emerged as a game-changer for the enterprise IT environment in Nigeria. As the country's businesses continue to grow and adapt to the digital era, cloud computing offers a scalable, flexible, and cost-effective solution for managing data, applications, and services. The adoption of cloud technology has the potential to revolutionize the way Nigerian enterprises operate, streamlining processes, enhancing collaboration, and improving overall efficiency. The study, however, investigated the effect of cloud infrastructure on the enterprise IT environment in Nigeria. The study used cloud infrastructure as an independent variable, proxied using software as a service (SAAS), platform as a service (PAAS), and infrastructure as a service (IAAS). The dependent variable is enterprise IT environment. The study adopted a survey research design using a simple random sampling technique to distribute about 121 copies of questionnaires among various IT departments in Nigeria. A validity and reliability test were carried out on 10% copies of the questionnaire and the result was reliable at 0.7 and valid. The study's main objective was analyzed using descriptive and inferential methods of statistics. The result found that cloud infrastructure has a significant impact on enterprise IT environment. The study, therefore, suggested that adopting cloud infrastructure offers numerous advantages, enabling companies to optimize their IT resources, access cutting edge, and swiftly adapt to changing market demands

Cloud Computing – Data Center – Access from Anywhere

Now days we are attached with our electronic gadgets either offline or online in such a way as we breathe, as without breathing we can’t alive, same like these electronics have become a vital part of our daily life. As of now by growing demand of these gadgets either in office work, or in research work or in various technical fields. As the use of computers increases as in day in and day out, the relevant resources that we need also go up. For companies like Oracle, IBM and Microsoft, utilizing the resources and establishing a huge infrastructure or network is not a big issue for these big giants. But for the new startup and small enterprises But when it comes to smaller enterprises, expensiveness becomes a huge factor. At the user or developer end we are facing a lot of issues like hardware disruption, various bugs in software, network errors. So this was such a big hassle for the large community of computer science in all over the world. Cloud Computing offers a quick fix to this situation. This technology has been completely transformed the way in which computing is moved up from PCs and as well as for the single user to enterprise via various servers to a ‘cloud’ of computers e.g: web servers, application servers, database servers and so on. A cloud is a virtualized server grid which can provide the different computing resources through IAAS (Infrastructure as a service),PAAS(platform as a service),SAAS(Software as a service) of their clients. The underlying details of how it is implemented which is not direct to end user. The data and the services provided reside in extensively scalable data centers so anyone can use or access it from any part of the globe. Various big giants like Google, Microsoft, Yahoo, IBM and Amazon have started providing cloud computing services from the individual user either paid or free upto some extent or to other small enterprises, big businesses through various models like B2B,B2C,C2C etc. Amazon, salesforce is the trailblazer in the field of cloud computing. Every big and small enterprise, companies which are doing their businesses online using cloud services for the storing information so that later on they will extract some meaning full insights for the growth of businesses. Cloud Computing is finding use in various areas like web hosting, parallel batch processing, graphics rendering, financial modeling, web crawling, genomics analysis, etc.

A Secure Two-Factor Authentication Framework in Cloud Computing

Cloud computing technology has brought tremendous evaluation in the arena of IT (information technology). This technology paves the path of starting business with lowest investment by availing infrastructure as a service (IAAS), platform as a service (PAAS) and software as a service (SAAS) pay per uses model. Cloud computing services can be quickly and easily provisioned and discharged with minimum efforts and service provider (SP) relationship. Cloud computing characteristics such as on demand self-service, broad network access, resource pooling, and rapid elasticity lead the demand of computing. Despite these features, this platform is free to security issues and attacks specifically in terms of communication because of unsecure authentication and privacy. However, strong user authentication procedure impedes illegal access to the SP which is the principal requirement for securing cloud computing ecosystem. In this regard, we attempt to propose possible counter measures for the cloud ecosystem. Hence, this paper presented a novel one way hash and nonce-based two-factor secure authentication scheme with traditional user IDs, password, and OTP verification procedure that resist brute force attack, session and account hijacking attack, MITM attacks, and replay attacks.

Cloud-Based NAS (Network Attached Storage) Analysis as an Infrastructure as A Service (IAAS) Using Open Source NAS4FREE and Owncloud

At this time, computer systems and networks are an essential part of human life. The number can see this of computer users in the office or on campus, and at school. This need has reached a relatively large number. To access data, many computer users in the network continue to increase, impacting the selection of servers, and large data storage media is necessary. Currently, the storage media that is often used to store data still uses physical media such as hard disks, flash disks that are virus-prone and easy to lose. Another problem also arises when physical storage has a relatively high price compared to cloud storage that can be accessed anywhere when needed.

Analysis of Host Resources Utilization by OpenStack in Ubuntu Environment

Cloud computing is one of the frontier technologies, which over the last decade has gained a widespread commercial and educational user base. OpenStack is one of the popular open source cloud management platforms for establishing a private or public Infrastructure-as-a-Service (IAAS) cloud. Although OpenStack started with very few core modules, it now houses nearly 38 modules and is quite complex. Such a complex software bundle is bound to have an impact on the underlying hardware utilization of the host system. The objective is to monitor the usage of system resources by OpenStack on commodity hardware. This paper analyzes the effect of OpenStack on the host machine's hardware. An extensive empirical evaluation has been done on different types of hardware, at different virtualization levels and with different flavours of operating systems comparing the CPU utilization, memory consumption, disk I/O, network, and I/O requests. OpenStack was deployed using Devstack on a single node. The novel aspect of this work is monitoring the resource usage by OpenStack without creating virtual machines on commodity hardware. From the analysis of data, it is observed that standalone machine with Ubuntu server operating system is the least effected by OpenStack and thereby has more available resources for computation of user workloads. Doi: 10.28991/esj-2020-01246 Full Text: PDF

Improving Cost for Data Migration in Cloud Computing Using Genetic Algorithm

Cloud computing is gradually increasing its popularity in enterprise-wide organizations. Information technology organizations e.g., IBM, Microsoft, and Amazon have already shifted towards Cloud computing. Cloud-based offerings such as Software as a Service, Platform as a Service and Infrastructure as a Service (IAAS) are the most famous offerings. Most of the existing enterprise applications are deployed using an on-premise model. Organizations are looking for Cloud based offerings to deploy or upgrade their existing applications. SAP, Microsoft Dynamics, and Oracle are the most famous ERP or CRM application OEMs. These enterprise applications generate lots of data are hosted in an organization or on client data centers. Moving data from one data center to the Cloud is always a challenging tasks which cost a lot and takes much effort. This study proposes an efficient approach to optimize cost for data migration in cloud computing. This study also proposes the approach to optimize cost for data collection from multiple locations which can be processed centrally and then migrate to Cloud Computing.

Artificial Intelligence (AI) Backed Cloud Resource Management Approach for Infrastructure as a Service (IAAS)

Artificial Intelligence (AI) Backed Cloud Resource Management Approach for Infrastructure as a Service (IAAS)

A work load prediction strategy for power optimization on cloud based data centre using deep machine learning

The application development industry has moved into cloud computing for stratifying the need of the customer for higher availability and higher scalability. The cloud computing environment provides the infrastructure off the premises for the application owner, which reduces the need for cost and security aspects. The primary intension of the cloud-based data centres is to virtualize the infrastructure for the applications and present it as Infrastructure As A Service (IAAS). The deployment of the applications from the application owner is done on the data centres and must be allocated to any of the pre-configured instances. The instances are again configured with virtual machines for virtualizing the computing capabilities, memory capabilities, network bandwidth capabilities and finally the storage capabilities. The deployed applications on the virtual machines must be accessible by the application consumers or the clients of the application owners. Load balancing typically includes committed programming or equipment, for example, a multilayer switch or a Domain Name System server process. Once the load is balanced, then the application performances can be justified. Great number of research endeavors have endeavored to build the presentation of the applications during load balancing by sending different calculations for distinguishing proof of the loaded virtual machines and less loaded cases for determination of the goal servers. Nevertheless, the performances of these strategies for load balancing is always criticized by various research attempts for being highly time complex and directly effecting the overall performances. Extraordinary number of research tries have attempted to construct the introduction of the applications during load balancing by sending various estimations for recognizing verification of the loaded virtual machines and less loaded cases for assurance of the objective servers. The outcome from this research is highly satisfactory and demonstrates nearly 98% accuracy on the load prediction and nearly 85% reduction on the time complexity with 88% reduction on the SLA violation.

ARCN: Authenticated Routing on Cloud Network to Mitigate Insider Attacks on Infrastructure as a Service

Cloud security is one of the major issues which are affecting the acceptance of Cloud computing (CC). In spite of the number of benefits offered by CC, it also suffers from a myriad of security vulnerabilities. Security is the prime concern while we are accessing the resources from the Cloud through the Internet. This research work is primarily on IAAS (Infrastructure as a service). Here a protocol called Authenticated Routing on Cloud Network (ARCN) has been proposed, to secure the communication route between the client and service provider. The proposed protocol ARCN uses the public key cryptography to mitigate the various security attacks like malicious insider attacks, Spoofing, Falsified routes, DoS, etc.

Design of Security Technique through Secure Logging for Cloud Forensics

Cloud computing has a new edge computing paradigm these days. Sometimes cloud computing architectures don’t support for computer forensics investigations. Analyzing various types of logs and logging mechanism plays an important role in computer forensics. Distributed nature and the multi-tenant cloud models, where many users share the same processing and network resources, collecting, storing and analyzing logs from a cloud is very hard. User activity logs can be a valuable source of information in cloud forensic investigations. Generally, Cloud service providers have access to activity logs of cloud user and CSP can tamper the logs so that investigator cannot reach to the real culprit. In such an environment, log security is one of challenge in the cloud. Logging technique is used to monitor employee’s behavior, to keep track of malicious activities and prevent cloud networks from intrusion by well-known organizations. Ensuring the reliability and integrity of logs is crucial. Most existing solutions for secure logging are designed for traditional systems rather than the complexity of a cloud environment. In the proposed framework secure logging environment is provided by storing and processing activity logs and encrypting using advanced encryption method. It detects DDoS (distributed denial of service) attack on cloud infrastructure by using the published logs on cloud and thus helpful in cloud forensics. It is detected by the investigator using available application activity logs in the cloud server. Searchable encryption algorithm will be used to increase the security of the logging mechanism and to maintain confidentiality and privacy of user data. Proof of past (PPL) logs is created by storing logs at more than one place. This PPL helps in the verification process of changed logs by CSP the actual implementation of this application on AWS Infrastructure as a service ( IAAS ) cloud shows real-time use of this structure.

A powerful software‐defined cyber‐physical system to expand CPS adoption

SummaryThe cyber‐physical system (CPS) has become a promising direction that can enrich the interaction between people and people, people and objects, objects and objects in the physical world and the virtual world. Because of the development of CPS, the number and types of smart device connected to the Internet has rapidly increased, bringing with it the current issues of flexibility, efficiency, availability, security, and scalability of the Internet‐of‐Things (IoT) network. These problems are caused by the key mechanism of large‐scale distribution to the IoT network. In this article, we propose CPSS inspired by software‐defined networking (SDN) and service‐oriented architecture, which is a powerful software‐defined cyber‐physical system to solve the challenges of broader CPS adoption. CPSS has three complementary modules: application‐as‐a‐service (AAAS), network‐as‐a‐service (NAAS), and infrastructure‐as‐a‐service (IAAS). IAAS collects network information from a different set of controllers and devices and generates a domain‐wide network view. NAAS collects information from different domains and generates a global view, which helps data transmission between different domains and enables seamless switching between applications and infrastructure devices. AAAS provides personalized service for each user. To test CPSS, we develop a prototype system. Our experimental results show that CPSS can effectively control cyber‐physical system, and CPSS has greatly improved network latency, network throughput, and network reliability compared to traditional controller‐controlled CPS.

Designing Software as a Service in Cloud Computing Using Quality Function Deployment

Cloud computing is an approach to access the virtualized resources based on an integrated system. Flexibility, scalability, high accessibility, and cost-effectiveness are some features of this system. These advantages have caused a favorable reception of different cloud computing services, such as software as a service (SAAS), platform as a service (PAAS), and infrastructure as a service (IAAS) on the part of businesses. In this article, a model for SAAS services has been proposed as one of the cloud computing layers with the maximum adjustment between the dimensions and components of QFD-based customer requirements. QFD is a method that seeks to translate the customer's voice into the technical design requirement. For this purpose, the dimensions and components of customer requirements and the dimensions and components of designing were determined through the review of literature and consulting with the experts. Finally, the dimensions and components of final desirable outcome were determined for SAAS by stages to achieve a modified QFD. After the examination of dimensions and components, a comparison was made between the companies and finally the most effective customer needs and the target values were determined. Thus, an SAAS service was designed. The telecommunications and cloud computing service provider companies can satisfy the customers and achieve a competitive advantage in designing SAAS services using the results of this research.

Optimum Utilization of Resources Through Restricted Virtual Machine Migration and Efficient VM Placement in Cloud Data Center

In infrastructure-as-a-service (IAAS) cloud platforms, it is a real challenge to provide high performance gain by the optimum utilization of resources while maintaining minimum consumption of energy. The existing research works show that reduction in energy consumption causes violation of service level agreement (SLA). In this article, the concept of probability has been used to take the migration decision of virtual machines (VM) from over-utilized as well as under-utilized nodes. A novel method has also been proposed for selecting the destination server where a migrated VM will be placed. This method is based on the current utilization of CPU, memory and network bandwidth. The proposed scheme maintains a balance between energy consumption and performance gain. Results obtained through trace driven simulation demonstrate that the probability-based migration scheme achieves energy-performance trade-off whereas the VM placement method shows a very high gain in performance.

DIRAC universal pilots

In the last few years, new types of computing models, such as IAAS (Infrastructure as a Service) and IAAC (Infrastructure as a Client), gained popularity. New resources may come as part of pledged resources, while others are in the form of opportunistic ones. Most but not all of these new infrastructures are based on virtualization techniques. In addition, some of them, present opportunities for multi-processor computing slots to the users. Virtual Organizations are therefore facing heterogeneity of the available resources and the use of an Interware software like DIRAC to provide the transparent, uniform interface has become essential. The transparent access to the underlying resources is realized by implementing the pilot model. DIRAC’s newest generation of generic pilots (the so-called Pilots 2.0) are the “pilots for all the skies”, and have been successfully released in production more than a year ago. They use a plugin mechanism that makes them easily adaptable. Pilots 2.0 have been used for fetching and running jobs on every type of resource, being it a Worker Node (WN) behind a CREAM/ARC/HTCondor/DIRAC Computing element, a Virtual Machine running on IaaC infrastructures like Vac or BOINC, on IaaS cloud resources managed by Vcycle, the LHCb High Level Trigger farm nodes, and any type of opportunistic computing resource. Make a machine a “Pilot Machine”, and all diversities between them will disappear. This contribution describes how pilots are made suitable for different resources, and the recent steps taken towards a fully unified framework, including monitoring. Also, the cases of multi-processor computing slots either on real or virtual machines, with the whole node or a partition of it, is discussed.

Middleware for Multicloud

There are many different options available to implement information technology (IT) today: enterprise data center legacy approaches or private cloud, public cloud, hybrid cloud, fog, device, mobile edge, and multicloud. Although definitions vary, for a variety of reasons, many companies are using multicloud approaches in a variety of patterns, at various layers such as infrastructure as a service (IaSS) and software as a service (SaaS).1 In some cases, multiple SaaS or infrastructure public or private clouds are used to support an end-to-end process, sometimes called workflow enactment.2 For example, a purchase order might be sent via a (cloud-based SaaS) email service such as Gmail, processed in a private cloud application, and then billed via a (cloud-based SaaS) billing service such as Zuora. Other use cases involve multiple public infrastructure clouds. For example, Netflix famously uses Amazon Web Services (AWS) for digital movie transcoding and its entertainment recommendation engine, but it also backs up data to Google’s cloud in the event of an AWS outage.

Pilots 2.0: DIRAC pilots for all the skies

In the last few years, new types of computing infrastructures, such as IAAS (Infrastructure as a Service) and IAAC (Infrastructure as a Client), gained popularity. New resources may come as part of pledged resources, while others are opportunistic. Most of these new infrastructures are based on virtualization techniques. Meanwhile, some concepts, such as distributed queues, lost appeal, while still supporting a vast amount of resources. Virtual Organizations are therefore facing heterogeneity of the available resources and the use of an Interware software like DIRAC to hide the diversity of underlying resources has become essential. The DIRAC WMS is based on the concept of pilot jobs that was introduced back in 2004. A pilot is what creates the possibility to run jobs on a worker node. Within DIRAC, we developed a new generation of pilot jobs, that we dubbed Pilots 2.0. Pilots 2.0 are not tied to a specific infrastructure; rather they are generic, fully configurable and extendible pilots. A Pilot 2.0 can be sent, as a script to be run, or it can be fetched from a remote location. A pilot 2.0 can run on every computing resource, e.g.: on CREAM Computing elements, on DIRAC Computing elements, on Virtual Machines as part of the contextualization script, or IAAC resources, provided that these machines are properly configured, hiding all the details of the Worker Nodes (WNs) infrastructure. Pilots 2.0 can be generated server and client side. Pilots 2.0 are the “pilots to fly in all the skies”, aiming at easy use of computing power, in whatever form it is presented. Another aim is the unification and simplification of the monitoring infrastructure for all kinds of computing resources, by using pilots as a network of distributed sensors coordinated by a central resource monitoring system. Pilots 2.0 have been developed using the command pattern. VOs using DIRAC can tune pilots 2.0 as they need, and extend or replace each and every pilot command in an easy way. In this paper we describe how Pilots 2.0 work with distributed and heterogeneous resources providing the necessary abstraction to deal with different kind of computing resources.

Energy Efficient Dynamic Load Balancing Algorithm for Cloud Environment

Cloud computing provides information technology resources and services on demand using the internet. It different types of services like IAAS (infrastructure as a service), PAAS (platform as a service) and SAAS(software as a service). Scenario of cloud computing refers to the two entities mainly cloud service provider and cloud service user. Cloud service provider provides the cloud resources and services to the cloud service user. Cloud service provider must have to use its resources efficiently to gain profit, but challenging task for them is maximum optimization of cloud resources. This paper describes approach which deals with saving of energy by optimally utilizing hosts and by minimizing active host using migration techniques. General Terms Algorithm for energy efficient dynamic load balancing in cloud environment.

Business to Consumer Application Design Based on Cloud Computing for SMEs

The importance of the role of Small and Medium Enterprises for Indonesia's economic growth give rise to the need of a business to consumer applications design that can run on cloud-based information technology infrastructure. The purpose of this research is to create an application design of business to consumer (b2c) of the SMEs to market their products which can be run on the Infrastructure as a Service (IAAS) cloud-based computing. The method used in this study is a system development life cycle (SDLC). Keywords: cloud, business, SME, SDLC

Dynamic Load Rebalancing Algorithm for Private Cloud

Infrastructure-As-A-Service (IAAS) provides an environmental setup under any type of cloud. In Distributed file system (DFS), nodes are simultaneously serve computing and storage functions; that is parallel Data Processing and storage in cloud. Here, file is considered as a data or load. That file is partitioned into a number of File chunks (FC) allocated in distinct nodes so that Map Reduce tasks can be performed in parallel over the nodes. Files and Nodes can be dynamically created, deleted, and added. This results in load imbalance in a distributed file system; that is, the file chunks are not distributed as uniformly as possible among the Chunk Servers (CS). Emerging distributed file systems in production systems strongly depend on a central node for chunk reallocation or Distributed node to maintain global knowledge of all chunks. This dependence is clearly inadequate in a large-scale, failure-prone environment because the central load balancer is put under considerable workload that is linearly scaled with the system size, it may thus become the performance bottleneck and the single point of failure and memory wastage in distributed nodes. So, we have to enhance the Client side module with server side module to create, delete and update the file chunks in Client Module. And manage the overall private cloud and apply dynamic load balancing algorithm to perform auto scaling options in private cloud. In this project, a fully distributed load rebalancing algorithm is presented to cope with the load imbalance problem.

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared over the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by "Big Data" will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.