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The development of cloud computing has brought a lot of advantages, such as reducing the hardware cost and a more convenient storage solution. Because of the convenient and cheap storage solution, a large number of users put their valuable data onto the cloud. There have been more and more outsourcing data security and privacy issues. Several schemes using attribute-based encryption (ABE) have been...
In this work, we propose a bidding policy for cloud users to reduce the instance rental bill by using the spot instance. Our approach is based on the recently developed two-timescale Lyapunov Optimization framework. It is shown that our approach is effective to save the instance rental cost.
information which are used in their respective environments independently to produce new science or better explain existing approaches. The interaction of data between these two domains is very limited and, hence, the information is disseminated. These disparate datasets need to be integrated to consolidate scattered pieces of information into a unified knowledge base to support new research challenges...
Web-based systems test techniques developed rapidly over the past years. Continuous integration approach demanded rejection of manual testing methods, and transition to fully automated methods, covering all application from the source code of core services to the user interface and API correctness. Every year there are dozens of new approaches to cloud applications testing, many of which, despite...
WBAN (Wireless Body Area Network) plays a fundamental role in telemedicine. However, due to the small size of sensor devices and weak capabilities in data processing/storage, WBAN is limited in application. In order to improve the ability of WBAN system and provide a richer service, the cloud-assisted WBAN has been proposed. Recently, He et al. proposed a method to check the data integrity in cloud-assisted...
In this paper, a real-time monocular video-based facial expression recognition system is proposed. An adaptively weighted online statistical appearance model is first constructed to retrieve the continuous facial motion information from each frame of input video. The static and dynamic knowledge of facial expression are obtained by facial expression anatomy and manifold learning respectively, and...
This paper introduces an automatic categorical-marking model for text categorization. Traditional classification algorithms are generally applying labeled training set and call for a lot of manual work to tag classifications beforehand. Also due to the ambiguity and fuzziness of texts, the results of traditional text categorization algorithms may not be clear enough and abundant in content. This paper...
The construction of wavelet synopses with maximum error bound have been studied by many years, which has many real world applications, such as health data stream analysis and image compression. Recently, there are two kinds of wavelet synopses with maximum error bound: one is restricted wavelet synopses whose synopses are restricted to the haar coefficients. Another is unrestricted wavelet synopses...
Cloud computing has been a great enabler for both the In-ternet of Things and Big Data. However, as with all newcomputing developments, development of the technology is usually much faster than consideration for, and development of, solutions for security and privacy. In a previous paper, we proposed that a unikernel solution could be used to improve security and privacy in a cloud scenario. In this...
Whilst there are many attributes that need to be considered for cloud service selection, performance remains one of the most crucial aspects. Thus, we argue for a transparent cloud provider comparison framework in this study. We initiate the development of TCloud: a transparent framework for public cloud service comparison. Our framework helps prospective cloud users to decipher public cloud benchmarking...
Program autotuning is becoming an increasingly valuable tool for improving performance portability across diverse target architectures, exploring trade-offs between several criteria, or meeting quality of service requirements. Recent work on general autotuning frameworks enabled rapid development of domain-specific autotuners reusing common libraries of parameter types and search techniques. In this...
Containers are rapidly replacing Virtual Machines (VMs) as the compute instance in cloud-based deployments. The significantly lower overhead of deploying containers (compared to VMs) has often been cited as one reason for this. However, interference caused by the limited isolation in shared resources can impact into the performance of hosted applications. We develop a Reference Net-based model of...
Cloud computing is nowadays one of the most promising IT technologies, since it provides seemingly unlimited resources on demand at low costs. Hence, different types of applications have been migrated to IaaS environments, e.g. multi-tier (distributed) applications. However, in order to benefit from such characteristics, cloud configurations (i.e. virtual resource configurations) should be designed...
In this paper, we propose a strategy to solve the load imbalance problem at MapReduce stage that caused from using the default partition algorithm of Hadoop platform. Through using multiple partitioning technique, this proposed strategy can refine the tasks and balance the inputs of reduce stage in the map phase. Furthermore, this proposed strategy can fully employ idle nodes to balance the high load...
Cloud computing and services have greatly changed the way how people develop and use software, and also raised a lot of new research issues. In this paper, we investigate two such important issues, service deployment and service request scheduling, for composite cloud services in dynamic cloud environments. We present load-aware service deployment approaches for dynamic workload and a service request...
Over the last few years, the number of smart objects connected to the Internet has grown exponentially in comparison to the number of services and applications. The integration between Cloud Computing and Internet of Things, named as Cloud of Things, plays a key role in managing the connected things, their data and services. One of the main challenges in Cloud of Things is the resource discovery of...
The end-to-end monitoring of inter-dependent applications in the cloud is challenging. Difficulties arise from the complexity of computations and the highly distributed nature of the deployment. Due to the lack of a comprehensive observability solution, it is very difficult to apply autonomous mechanisms to ensure service guarantees in the cloud. To tackle the problem, we propose the method of data-driven...
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