Cloud computing is a new computing model which uses virtualization technology, distributed computing, parallel computing and other existing technologies to achieve cloud service virtualization and economies of scale, whilst increasingly overwhelming cloud security issues has brought great challenges and concerns to the cloud services providers and cloud users, especially trust and privacy issues with regard to cloud computing and cloud shared storage associated security issues. In the paper, we expound the basic concepts of cloud computing, deployment models, service models and key features, analyze and outline the currently highlighted cloud security issues, report the status quo of cloud computing security, investigate the prevalent and typical cloud computing security problem key solving techniques, and thus render a comprehensive cloud computing security technical reference model, which is composed of associated cloud security solving techniques that result from inevitably multi-faceted cloud security issues. The model is expected to alleviate prominent cloud security issues. This paper generalizes cloud security technology research directions and further development space of cloud security technology and standardization.
Cloud computing is moving from being a testing ground for isolated projects to being a strategic approach of the entire business organization. So the choice among the possible cloud offers, with a strong focus on the choice of services that enable better processes and projects of the business lines, is gaining importance. Nevertheless the heterogeneity of the Cloud services, resources, technology and service levels offered by the several providers make difficult to decide. Besides the inconveniences caused by the "lock-in", give rise to the need for developers to be able to develop an application regardless of where it is released, structuring and building it in a vendor agnostic way so that it is possible to deploy on the provider that best fits them at the moment. The mOSAIC project aims at designing and developing an innovative open-source API and platform that enables applications to be Cloud providers' neutral and to negotiate Cloud services as requested by their users, allowing automatic discovery, matchmaking, and thus supporting selection, brokering, interoperability end even composition of Cloud Services among multiple Clouds. In this paper, we illustrate the interoperation of the two components, the Semantic Engine and the Cloud Agency for the agnostic retrieval, discovery and brokering of cloud services. The focus will be put on the way to support the Cloud Application Developer to express the requirements and services/resources in vendor agnostic way and to translate automatically these requirements into a neutral format in order to compare it with the different offers of providers and to broker the best one according to defined policies.
A notion of increasing the energy efficiency of HPC machines or applications has reached the global HPC community forum in recent years. This has opened up several interesting possibilities that reduces the energy consumption of applications, including an energy consumption analysis mechanism which delves into the reason behind the energy consumption bottlenecks of applications. In order to easily analyze the energy consumption of applications (from machine to machine), a need for a dedicated energy consumption analysis tool has undoubtedly enthused application developers or users. In general, when applications were analyzed for performance bottlenecks in modern HPC architectures, such as, exascale machines which have more than tens of thousands of cores, a performance analysis tool might deliver a huge performance dataset. Querying such data in a short span of time can efficiently be done using document based NoSQL database systems. This paper proposes an online-based energy consumption analysis mechanism of HPC applications using EnergyAnalyzer Performance Database (EAPerfDB), a NoSQL-based performance database feature, of EnergyAnalyzer tool. The EnergyAnalyzer tool uses semantic agents in a distributed fashion to undergo the energy consumption analysis of HPC applications. In addition, the paper explores the findings of the energy consumption analysis of High Performance Computing Challenge (HPCC) benchmarks when NoSQL-based EnergyAnalyzer tool was used at the HPCCLoud Research Laboratory of our premise.
Security measures, such as proving data integrity, became more important with the increase in popularity of cloud data storage services. Dynamic Provable Data Possession (DPDP) was proposed in the literature to enable the cloud server to prove to the client that her data is kept intact, even in a dynamic setting where the client may update her files. Realizing that variable-sized updates are very inefficient in DPDP (in the worst case leading to uploading the whole file again), Flexible DPDP (FlexDPDP) was proposed.In this paper, we analyze FlexDPDP scheme and propose optimized algorithms. We show that the initial pre-processing phase at the client and server sides during the file upload (generally the most time-consuming operation) can be efficiently performed by parallelization techniques that result in a speed up of 6 with 8 cores. We propose a way of handling multiple updates at once both at the server and the client side, achieving an efficiency gain of 60% at the server side and 90% in terms of the client's update verification time.We deployed the optimized FlexDPDP on the large-scale network testbed PlanetLab and demonstrate the efficiency of our proposed optimizations on multi-client scenarios according to real workloads based on version control system traces.
The increased use of virtualized environments has led to numerous research efforts about the possibilities and restrictions of the use of these virtualized environments in cloud computing or for resource consolidation. However, most of these studies are limited to a level of performance analysis, that does not address the effects of concurrency among the various virtual environments, and how to mitigate these effects. The study presented below proposes the concept of affinity, based on the correct combination of certain applications classes, that are able to share the same environment, at the same time, causing less loss of performance. The results show that there are combinations of applications that could share the same environment with minimum loss, but there are combinations that must be avoided. This study also shows the influence of the type of parallel library used for the implementation of these applications.
