250 research outputs found

    Mirroring Mobile Phone in the Clouds

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    This paper presents a framework of Mirroring Mobile Phone in the Clouds (MMPC) to speed up data/computing intensive applications on a mobile phone by taking full advantage of the super computing power of the clouds. An application on the mobile phone is dynamically partitioned in such a way that the heavy-weighted part is always running on a mirrored server in the clouds while the light-weighted part remains on the mobile phone. A performance improvement (an energy consumption reduction of 70% and a speed-up of 15x) is achieved at the cost of the communication overhead between the mobile phone and the clouds (to transfer the application codes and intermediate results) of a desired application. Our original contributions include a dynamic profiler and a dynamic partitioning algorithm compared with traditional approaches of either statically partitioning a mobile application or modifying a mobile application to support the required partitioning

    CloudJet4BigData: Streamlining Big Data via an Accelerated Socket Interface

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    Big data needs to feed users with fresh processing results and cloud platforms can be used to speed up big data applications. This paper describes a new data communication protocol (CloudJet) for long distance and large volume big data accessing operations to alleviate the large latencies encountered in sharing big data resources in the clouds. It encapsulates a dynamic multi-stream/multi-path engine at the socket level, which conforms to Portable Operating System Interface (POSIX) and thereby can accelerate any POSIX-compatible applications across IP based networks. It was demonstrated that CloudJet accelerates typical big data applications such as very large database (VLDB), data mining, media streaming and office applications by up to tenfold in real-world tests

    Secure Cloud Storage: A Framework for Data Protection as a Service in the Multi-cloud Environment

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    This paper introduces Secure Cloud Storage (SCS), a framework for Data Protection as a Service (DPaaS) to cloud computing users. Compared to the existing Data Encryption as a Service (DEaaS) such as those provided by Amazon and Google, DPaaS provides more flexibility to protect data in the cloud. In addition to supporting the basic data encryption capability as DEaaS does, DPaaS allows users to define fine-grained access control policies to protect their data. Once data is put under an access control policy, it is automatically encrypted and only if the policy is satisfied, the data could be decrypted and accessed by either the data owner or anyone else specified in the policy. The key idea of the SCS framework is to separate data management from security management in addition to defining a full cycle of data security automation from encryption to decryption. As a proof-of-concept for the design, we implemented a prototype of the SCS framework that works with both BT Cloud Compute platform and Amazon EC2. Experiments on the prototype have proved the efficiency of the SCS framework
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