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This paper describes the development and implementation of a lightweight software solution, called OSSperf, which can be used to investigate the performance of object-based public cloud storage services like Amazon S3, Google Storage and Microsoft Azure Blob Storage, as well as private cloud re-implementations. Furthermore, this paper presents an e...
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... Performance evaluation environment with open stack deployment, the test cases investigate the internal behavior of open stack in terms of computing. The results in terms of performance usage in uploading and downloading developments is improved with open stack methodologies [56]. ...
Storage in cloud computing is the fundamental service which is widely used by consumers of cloud. Cloud offer many advantages such as flexibility, elasticity, scalability and sharing of data among users. However, cloud storage throws many privacy and security challenges. Especially, the most significant problem is access control mechanism which ensures sharing of dataonly to authorized users. Most of the cloud service providers offer Role Based Access Control (RBAC) where users are grouped into roles and access is given to resources based on roles. The problem with this scheme is that once a role gets access to a resource, further restrictions are not possible, where there are security limitations for which data owner needs to restrict access to a part of an object but not entire object. This work proposes to useSwift, an object storage service in open source cloud named OpenStack. Swift restricts access to objects using Access Control Lists (ACLs). As per ACL, users can gain access to an object. However, once access is given, users can access the complete object without further restrictions. The proposed work is evaluated in real cloud environment Amazon cloud, Microsoft Azure, and Open stack cloud. A framework termed Predicate Based Access Control (PBAC) is proposed to render fine grained access control to Swift storage. Access is provided to predicates that are part of an object. Instead of following an “all or nothing” approach, an access control mechanism that makes the Swift storage and retrieval more secure is preferred.
... Komputasi awan menawarkan akses sesuai permintaan sumber daya komputasi, infrastruktur dan data dioperasikan dari sumber jarak jauh. Teknologi baru ini telah membuka cara baru sumber daya yang fleksibel ketentuan untuk bisnis untuk mengelola aplikasi IT dan data menanggapi tuntutan baru dari pelanggan [4]. Konsep Cloud adalah mengubah hardware-dedicated menjadi software-dedicated sehingga Cloud menjadi salah satu solusi yang lebih praktis dan dengan biaya minimal [5], karena jika terjadi penurunan performa tidak perlu menambah komponen secara fisik melainkan menambah secara logic. ...
Era Pandemi menyebabkan peningkatan penggunaan aplikasi konferensi video yang tiba-tiba dan siginifikan. Bagi perusahaan harus segera beradaptasi dalam hal aplikasi komunikasi. Salah satu aplikasi yang bisa digunakan yaitu openmeetings. Openmeetings adalah aplikasi yang digunakan sebagai pengatur konferensi yang terinstal pada server. Umumnya server dibangun menggunakan komponen fisik, namun memiliki keterbatasan sehingga seringkali mengalami penurunan performa dalam segi kecepatan server dalam menjalankan layanan. Salah satu upaya meningkatkan performa server harus menambah atau mengganti perangkat keras sehingga kurang menguntungkan pada biaya operasional. Konsep Cloud selain dapat mengefisienkan biaya operasional server juga handal dalam hal ketersedian layanan. Cloud merupakan sebuah model Client-server, dapat diakses oleh pengguna dimana saja dan kapan saja. Membangun Cloud salah satunya dapat menggunakan openstack, merupakan software open source untuk membangun cloud. Penelitian dilakukan perbandingan harga cloud dengan komponen fisik serta pengujian Video Conference yang di jalankan dalam Cloud untuk mengetahui kinerja Cloud dari sisi Quality of Service (QoS) meliputi delay, packetloss, jitter dan throughput. Hasilnya disimpulkan menggunakan cloud lebih efisien dibandingkan dengan menggunakan server fisik. nilai rata-rata terbesar pada sisi upload adakah throughput sebesar 639.85kbps, delay sebesar 30.22ms, jitter sebesar 10.35ms dan packetloss sebesar 0.94%, untuk nilai rata-rata terbesar pada sisi download adalah throughput sebesar 1,856.55kbps, delay sebesar 10.19ms, jitter sebesar 6.18ms dan packetloss sebesar 0.87%.
... OpenStack is a distributed collection of open source cloud computing software projects that enterprises or cloud providers can adopt for creating, managing, and deploying infrastructure cloud services [32]. 4.04.5-server ...
Given the development of the Cloud Computing recently, clients and customers using the Cloud for both individual and business needs have expanded to an uncommon scale. This has normally prompted the expanded deployments of Cloud data centers over the globe. As a result, Cloud data centers are seen to be monstrous energy consumers and natural polluters. They require an extraordinary measure of regular energy which has made an effect on the energy supply and natural conditions of the environment. This is the reason why the vulnerability of persistent energy supply, later on, is being referred to. In this way, there is a need of an energy-aware cloud-based system which automatically and efficiently manages and optimize cloud computing data center resources by considering energy consumption as an essential Quality of Service (QoS) parameter. This paper, focus on the energy utilization of the data centers and how this can be limited so as to make the cloud computing greener. Thus, a new autonomic resource optimization manager has been proposed to avail the most optimum level of resources with reduced server energy consumption. The proposed framework has been verified theoretically and tested experimentally. The experimental analysis has demonstrated that the effectiveness of the proposed solution is greater than the state-of-the-art methods in terms of the achieved results related to reducing energy consumption and response time in cloud computing data centers.
... Performance evaluation environment with open stack deployment, the test cases investigate the internal behavior of open stack in terms of computing. The results in terms of performance usage in uploading and downloading developments is improved with open stack methodologies [56]. ...
Emphasis on security for providing Access Control in Cloud computing environment plays a significant role. Cloud computing provides number of benefits such as resource sharing, low speculation and large storage space. Huge amount of information stored in cloud can be accessed from anywhere, anytime on pay-per use basis. Resources in cloud should be accessed only by the authorized clients. Access Control in cloud computing has become a critical issue due to increasing number of users experiencing dynamic changes. Authentication, authorization and approval of the access ensuring liability of entities from login credentials including passwords and biometric scan is essential. Also, the federated authentication management is secured. Current approaches require large-scale distributed access control in cloud environment. Data security and access control are the drawbacks in existing access control schemes. Due to the drawbacks in exist-ing access control schemes such as privacy of information when susceptible information is stored in intermediary service provider a fed-erated identity access management is essential. Access control applications majorly concentrate on Healthcare, Government Organiza-tions, Commercial, Critical Infrastructure and Financial Institutions. This review illustrates a detailed study of access control models in cloud computing and various cloud identity management schemes.
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
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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. This paper analyzes the effect of OpenStack on the host machine’s hardware. For this purpose, an extensive empirical evaluation has been done on different types of hardware, different virtualization levels and with different flavors of operating systems comparing the CPU utilization, and memory consumption. OpenStack was deployed using Devstack on a single node. From the results it is evident that standalone machine with Ubuntu server operating system is the least affected by OpenStack and thereby has more available resources for computation of user workloads.
Private IaaS clouds offer an attractive environment to be used in enterprise and scientific fields providing advantages such as scalability, security and avoids dependence on third parties. However, one of the challenges is to port applications to the cloud environment without compromising performance. In response to this, the goal of this text is to characterize the application''s performance in private IaaS clouds using scientific and enterprise applications. Therefore, the CloudStack was used to manage clouds and KVM and LXC-based were deployed as virtualization technologies. To represent real-world applications from the scientific and enterprise fields, it was used the NPB-OMP and PARSEC suite. These applications were benchmarked to characterize the high-performance and multi-tenancy environment. The statistical method was used to verify if there were significant differences among the clouds in each proposed environment. The results reveal that scientific and enterprise workloads are statistically different in the majority of the experiments performed in KVM and LXC-based clouds, however, there are results with non-significant differences.
