Limitations Of Cloud Computing Research Articles

Cloud Computing Security: Threats and Countermeasures

Cloud computing has revolutionized the way IT organizations and IT teams manage their internal digital assets and workloads. One of the major drawbacks or limitations of cloud computing is security. Cloud computing comes with various threats and vulnerabilities, and new threats and vulnerabilities are discovered all the time. Every year, small to large security incidents are reported around the world. To our knowledge, there are no recent research articles covering recent advances in cloud computing security. To address this issue, this paper provides an analysis of recent cloud computing security literature. Expanding on the threats proposed by the Cloud Security Alliance, a taxonomy related to cloud computing threats and vulnerabilities is provided to educate cloud users and guide the cloud. providers to strengthen or review their security policies and practices. can do. In conclusion, we also provide a taxonomy of state-of-the-art countermeasures and solutions to protect the cloud from various threats.

Review on QoS and security challenges associated with the internet of vehicles in cloud computing

Internet of Vehicles (IoV) is an area of research and development that has rapidly developed in the VANETs (Vehicular Ad-hoc Networks) that provides a mode of smart communication between vehicle to vehicle and cloud using IoT (Internet of Things). Two-way communication between Internet-enabled automobiles and network equipment is fully supported by IoV providing faster and more reliable solutions. Moving computation to the network's periphery can speed up service delivery and drop the latency. Computing designs that are centralized (cloud computing) and decentralized (Edge computing) face the challenges of high latency, infrastructure cost, and performance deterioration. While using Cloud Computing (CC) the impact is on other areas including the transportation sector resulting in the development of the Internet of Vehicles with Cloud Computing (IoV-CC). VANET is considered to be the fastest wireless communication, In terms of quick handoffs, network availability, security, safety with the deployment of advanced applications, etc., VANET will have more advanced features and will undergo a radical change as it progresses in its development path. VANET and Cloud Computing will play a major role in providing highly efficient technology for autonomous driving, vehicle control, and intelligent systems in near future. CC is a centralized computing paradigm but is not able to address many QoS (Quality of Service) parameters like latency, throughput, and bandwidth optimization. To resolve the limitations of CC, Fog Computing (FC) is introduced in VANETs. The IoV-CC must address concerns regarding security and privacy. As a result, the security protocols used in traditional VANET and CC have had to be updated for IoV-CC and a new secure algorithm needs to be developed to have secure communication between FOG and cloud nodes. To innovate QoS in VANET for IoV-CC there is a significant absence of data dissemination and security difficulties. The purpose of this research is to explore IoV's data distribution and security acceptability with respect to centralized and decentralized computing. Further, it addresses the associated efforts and their consequences, as well as future possibilities for dealing with these difficulties, in the subsequent section.

A scheduling-based dynamic fog computing framework for augmenting resource utilization

Fog computing is one of the most important emerging paradigms in recent technological development. It alleviates several limitations of cloud computing by bringing computation, communication, storage, and real-time services near to the end-users. However, with the rapid development of automation in smart cities, the number of task executions by fog nodes are increasing, requiring additional fog nodes. In this paper, we present a Scheduling-based Dynamic Fog Computing (SDFC) Framework to augment the utilization of existing resources rather than adding further fog resources. It includes an additional layer, Master Fog (MF), between the cloud and general-purpose fogs, which are addressed here as Citizen Fog (CF). The MF is responsible for deciding task execution in CFs and the cloud. We use the Comparative Attributes Algorithm (CAA) to schedule tasks based on their priority and a Linear Attribute Summarized Algorithm (LASA) to select the most available CF with the highest computational ability. Our empirical results validate our SDFC framework and show the dependency on the cloud reduces by 15%–20% and overall execution time decreases by 45%–50%.

Structure proposed to deal with sensor-based data

The possibility of greater control over processes, with the increasing use of sensors, leads to the generation of a large amount of data and, consequently, inherent difficulties, also need care. Storage, processing, filtering, become more difficult and the use of cloud computing can be a solution, however, the cloud computing technology also has limitations regarding latency and availability that can be mitigated with the use of an intermediate layer, called fog computing. As the structuring of the fog computing layer is not yet standardized, one of the possibilities is the application of an enterprise service bus (ESB), a structure based on the availability and interconnection of targeted services, for processing, filtering or storage. From an ESB structure such as fog computing, proofs of concept were developed to validate the technology, the first proof of concept being an environment, whose temperature must be controlled, with distributed sensors and their values received, processed and stored by services in the ESB and the second proof of concept, based on soil contaminant data, obtained by sensors and made available in the literature, for which filtering and processing services, on the same bus, were used. The study presents, in its results, the applicability of the fog computing layer, minimizing the limitations of cloud computing.

READ: Robustness-Oriented Edge Application Deployment in Edge Computing Environment

In recent years, edge computing has emerged as a prospective distributed computing paradigm that overcomes several limitations of cloud computing. In the edge computing environment, a service provider can deploy its application instances on edge servers at the edge of the network to serve its own users with low latency. Given a limited budget <inline-formula><tex-math notation="LaTeX">$\mathcal {K}$</tex-math></inline-formula> for deploying applications on the edge servers in a particular geographical area, a number of approaches have been proposed very recently to determine the optimal deployment strategy that achieves various optimization objectives, e.g., to maximize the servers’ coverage, to minimize the average network latency, etc. However, the robustness of the services collectively delivered by the service provider’s applications deployed on the edge servers has not been considered at all. This is a critical issue, especially in the highly distributed, dynamic and volatile edge computing environment. In this article, we make the first attempt to tackle this challenge. Specifically, we formulate this <i>Robustness-oriented Edge Application Deployment</i> (READ) problem as a constrained optimization problem and prove its <inline-formula><tex-math notation="LaTeX">$\mathcal {NP}$</tex-math></inline-formula> -hardness. Then, we provide an integer programming based approach named READ- <inline-formula><tex-math notation="LaTeX">$\mathcal {O}$</tex-math></inline-formula> for solving this problem precisely. We also provide an approximation algorithm, namely READ- <inline-formula><tex-math notation="LaTeX">$\mathcal {A}$</tex-math></inline-formula> , for finding near-optimal solutions to large-scale READ problems efficiently. We prove its approximation ratio is not worse than <inline-formula><tex-math notation="LaTeX">$\mathcal {K}/2$</tex-math></inline-formula> , which is a constant regardless of the total number of edge servers. We evaluate our approaches experimentally on a widely-used real-world dataset against five representative approaches. The experiment results demonstrate that our approaches can solve the READ problem effectively and efficiently.

Cloud Computing: A Revolution in Libraries and Information Services

Cloud computing technology has changed the scenario of the world. During last decades this technology has been adopted by all over the world and it has changed the scenario of the way you working. Cloud computing technology has made many things possible which may not possible in the traditional computing methods. There are many advantages of cloud computing for libraries also, many libraries are now moving into the cloud, it has reduced the heavy burden of library staff to protect and preserve their digital data and assets. Through consortia libraries can create a network of libraries and sharing their resources with member libraries. In this article, we have discussed concept, types, service models, advantages and limitations of cloud computing.

Cost benefit analysis of cloud computing in education

Application of cloud computing in education not only relieves the educational institutions from the burden of handling the complex IT infrastructure management as well as maintenance activities, but also leads to huge cost savings. Along with many industry sectors, education sector would be largely benefited by adopting cloud services. Cloud promises to deliver affordable, reliable and flexible computing solutions to the education sector and enable it to compete more effectively with bigger organisations. The motive of this paper is to analyse the approach that has been followed to identify the benefits and limitations of cloud computing. Specific case of a lab setup has been taken to illustrate the financial aspects. A comparative analysis of cloud-based hosting versus conventional (on-premise) application deployment has also been presented.

Cost benefit analysis of cloud computing in education

Application of cloud computing in education not only relieves the educational institutions from the burden of handling the complex IT infrastructure management as well as maintenance activities, but also leads to huge cost savings. Along with many industry sectors, education sector would be largely benefited by adopting cloud services. Cloud promises to deliver affordable, reliable and flexible computing solutions to the education sector and enable it to compete more effectively with bigger organisations. The motive of this paper is to analyse the approach that has been followed to identify the benefits and limitations of cloud computing. Specific case of a lab setup has been taken to illustrate the financial aspects. A comparative analysis of cloud-based hosting versus conventional (on-premise) application deployment has also been presented.

Cloud computing: challenges, limitations and R&amp;D solutions

This book reviews the challenging issues that present barriers to greater implementation of the cloud computing paradigm, together with the latest research into developing potential solutions. Topics and features: presents a focus on the most important issues and limitations of cloud computing, covering cloud security and architecture, QoS and SLAs; discusses a methodology for cloud security management, and proposes a framework for secure data storage and identity management in the cloud; introduces a simulation tool for energy-aware cloud environments, and an efficient congestion control system for data center networks; examines the issues of energy-aware VM consolidation in the IaaS provision, and software-defined networking for cloud related applications; reviews current trends and suggests future developments in virtualization, cloud security, QoS data warehouses, cloud federation approaches, and DBaaS provision; predicts how the next generation of utility computing infrastructures will be designed.

A Panorama of Cloud Services

Cloud computing paradigm has attracted a lot of attention in the last five years as coming during an economic crisis with an appealing offer in reducing the infrastructure and maintenance costs. After first wave of enthusiasm in adopting the concept, a clearer image has been formed about the benefits and limitations of Cloud computing and a lot of different supporting technologies were developed. As consequence a new threat is raised by the high number of the proprietary technologies that makes difficult the decision of the proper technological selection according to the real business needs. In this context the aim of this paper is to offer a snapshot on the current concepts and the available technologies, especially of the ones that can allow the development of a solid market of Cloud services and applications. A particular attention is given to the trend of federating and brokering Cloud services in the process of forming new markets. Moreover, we propose a classification of groups of services from multiple Clouds based on models similar to the ones used in computer graphics to express colors. Furthermore, a technological solution aligned to the market requirements is presented as case study, pointing also to the role of open-source codes for promoting the Cloud service usage on large scale.