Comparative Analysis of Distributed and Parallel File Systems' Internal Techniques

A file system optimization is the most common task in the file system field. Usually, it is seen as the key file system problem. Moreover, it is possible to state that optimization is dominant in commercial development. A problem of a new file system architecture development arises more frequently in academia. End-user can treat file system performance as the key problem of file system evolving as technology. Such understanding arises from common treatment of persistent memory as slow subsystem. As a result, problem of improving performance of data processing treats as a problem of file system performance optimization. However, evolution of physical technologies of persistent data storage requires significant changing of concepts and approaches of file systems' internal techniques. Generally speaking, only trying to improve the file system efficiency cannot resolve all issue of file systems as technological direction. Moreover, it can impede evolution of file system technology at whole. It is impossible to satisfy end-user's expectations by means of file systems optimization only. New persistent storage technologies can question about file systems necessity at whole without suggestion of revolutionary new file system's approaches. However, file system contains paradigm of information structuring that is very important for end-user as a human being. It needs to distinguish the two classes of tasks: (1) optimization task; (2) task of elaboration a new architecture vision or paradigm. But, frequently, project goal degenerates into optimization task which is meant really elaboration of a new paradigm. End-user expectations are complex and contradictory set of requirements. Only optimization tasks cannot resolve the all current needs of end-user in the file system field. End-user's expectations require resolving tasks of a new architecture vision or paradigm elaboration

Open-Source Simulators for Cloud Computing: Comparative Study and Challenging Issues

Resource scheduling in infrastructure as a service (IaaS) is one of the keys for large-scale Cloud applications. Extensive research on all issues in real environment is extremely difficult because it requires developers to consider network infrastructure and the environment, which may be beyond the control. In addition, the network conditions cannot be controlled or predicted. Performance evaluations of workload models and Cloud provisioning algorithms in a repeatable manner under different configurations are difficult. Therefore, simulators are developed. To understand and apply better the state-of-the-art of cloud computing simulators, and to improve them, we study four known open-source simulators. They are compared in terms of architecture, modeling elements, simulation process, performance metrics and scalability in performance. Finally, a few challenging issues as future research trends are outlined.Comment: 15 pages, 11 figures, accepted for publication in Journal: Simulation Modelling Practice and Theor

Synchronized Multi-Load Balancer with Fault Tolerance in Cloud

In this method, service of one load balancer can be borrowed or shared among other load balancers when any correction is needed in the estimation of the load.Comment: 8 Pages, 10 figure

Recent Developments in Cloud Based Systems: State of Art

Cloud computing is the new buzzword in the head of the techies round the clock these days. The importance and the different applications of cloud computing are overwhelming and thus, it is a topic of huge significance. It provides several astounding features like Multitenancy, on demand service, pay per use etc. This manuscript presents an exhaustive survey on cloud computing technology and potential research issues in cloud computing that needs to be addressed

All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey

With the Internet of Things (IoT) becoming part of our daily life and our environment, we expect rapid growth in the number of connected devices. IoT is expected to connect billions of devices and humans to bring promising advantages for us. With this growth, fog computing, along with its related edge computing paradigms, such as multi-access edge computing (MEC) and cloudlet, are seen as promising solutions for handling the large volume of security-critical and time-sensitive data that is being produced by the IoT. In this paper, we first provide a tutorial on fog computing and its related computing paradigms, including their similarities and differences. Next, we provide a taxonomy of research topics in fog computing, and through a comprehensive survey, we summarize and categorize the efforts on fog computing and its related computing paradigms. Finally, we provide challenges and future directions for research in fog computing.Comment: 48 pages, 7 tables, 11 figures, 450 references. The data (categories and features/objectives of the papers) of this survey are now available publicly. Accepted by Elsevier Journal of Systems Architectur

Software-Defined Networking: State of the Art and Research Challenges

Plug-and-play information technology (IT) infrastructure has been expanding very rapidly in recent years. With the advent of cloud computing, many ecosystem and business paradigms are encountering potential changes and may be able to eliminate their IT infrastructure maintenance processes. Real-time performance and high availability requirements have induced telecom networks to adopt the new concepts of the cloud model: software-defined networking (SDN) and network function virtualization (NFV). NFV introduces and deploys new network functions in an open and standardized IT environment, while SDN aims to transform the way networks function. SDN and NFV are complementary technologies; they do not depend on each other. However, both concepts can be merged and have the potential to mitigate the challenges of legacy networks. In this paper, our aim is to describe the benefits of using SDN in a multitude of environments such as in data centers, data center networks, and Network as Service offerings. We also present the various challenges facing SDN, from scalability to reliability and security concerns, and discuss existing solutions to these challenges

DDoS Attacks: Tools, Mitigation Approaches, and Probable Impact on Private Cloud Environment

The future of the Internet is predicted to be on the cloud, resulting in more complex and more intensive computing, but possibly also a more insecure digital world. The presence of a large amount of resources organized densely is a key factor in attracting DDoS attacks. Such attacks are arguably more dangerous in private individual clouds with limited resources. This paper discusses several prominent approaches introduced to counter DDoS attacks in private clouds. We also discuss issues and challenges to mitigate DDoS attacks in private clouds

Distributed Hierarchical Control versus an Economic Model for Cloud Resource Management

We investigate a hierarchically organized cloud infrastructure and compare distributed hierarchical control based on resource monitoring with market mechanisms for resource management. The latter do not require a model of the system, incur a low overhead, are robust, and satisfy several other desiderates of autonomic computing. We introduce several performance measures and report on simulation studies which show that a straightforward bidding scheme supports an effective admission control mechanism, while reducing the communication complexity by several orders of magnitude and also increasing the acceptance rate compared to hierarchical control and monitoring mechanisms. Resource management based on market-based mechanisms can be seen as an intermediate step towards cloud self-organization, an ideal alternative to current mechanisms for cloud resource management.Comment: 13 pages, 4 figure

Towards Transactional Load over XtreemFS

We propose using trace-based assessment of the performance of distributed file systems (DFS) under transactional IO load. The assessment includes simulations and experiments using the IO traces. Our experiments suggest that DFS, and specifically XtreemFS have a good potential to support transactional IO load in distributed environments: they demonstrate good performance, high availability and scalability, while at the same time opening the way to TCO reduction.Comment: The paper is withdrawn by the author due to affiliation incorrectnes

Application Management in Fog Computing Environments: A Taxonomy, Review and Future Directions

The Internet of Things (IoT) paradigm is being rapidly adopted for the creation of smart environments in various domains. The IoT-enabled Cyber-Physical Systems (CPSs) associated with smart city, healthcare, Industry 4.0 and Agtech handle a huge volume of data and require data processing services from different types of applications in real-time. The Cloud-centric execution of IoT applications barely meets such requirements as the Cloud datacentres reside at a multi-hop distance from the IoT devices. \textit{Fog computing}, an extension of Cloud at the edge network, can execute these applications closer to data sources. Thus, Fog computing can improve application service delivery time and resist network congestion. However, the Fog nodes are highly distributed, heterogeneous and most of them are constrained in resources and spatial sharing. Therefore, efficient management of applications is necessary to fully exploit the capabilities of Fog nodes. In this work, we investigate the existing application management strategies in Fog computing and review them in terms of architecture, placement and maintenance. Additionally, we propose a comprehensive taxonomy and highlight the research gaps in Fog-based application management. We also discuss a perspective model and provide future research directions for further improvement of application management in Fog computing