Current Issue : July - September Volume : 2018 Issue Number : 3 Articles : 5 Articles
With this paper, we propose a network coding based cloud storage scheme.\nThe storage system is in the form of an m * n data array. The n columns stand\nfor n storage nodes, which are comprised of a part of systematic nodes storing\nsource symbols and a part of nonsystematic nodes storing parity symbols.\nEvery row of the data array is a (n, k) systematic Maximum Distance Separable\n(MDS) code. A source symbol is only involved in the encoding with the\nunique row; it locates at and is not used by other rows. Such a design significantly\ndecreases the complexity of encoding and decoding. Moreover, in case\nof single node failures, we use interference alignment to further reduce repair\nbandwidth. Compared to some existing cloud storage schemes, our scheme\nsignificantly reduces resource consumption on storage, update bandwidth and\nrepair bandwidth....
With the continuous development of cloud computing, cloud security has become one of the most important issues in cloud\ncomputing. For example, data stored in the cloud platformmay be attacked, and its security is difficult to be guaranteed.Therefore,\nwe must attach weight to the issue of how to protect the data stored in the cloud. To protect data, data monitoring is a necessary\nprocess. Based on autonomic computing, we develop a cloud datamonitoring systemon the cloud platform,monitoringwhether the\ndata is abnormal in the cycle and analyzing the security of the data according to the monitored results. In this paper, the feasibility\nof the scheme can be verified through simulation. The results show that the proposed method can adapt to the dynamic change of\ncloud platformload, and it can also accurately evaluate the degree of abnormal data.Meanwhile, by adjustingmonitoring frequency\nautomatically, it improves the accuracy and timeliness of monitoring. Furthermore, it can reduce themonitoring cost of the system\nin normal operation process....
Mobile cloud computing (MCC) has attracted extensive attention in recent years. With the prevalence of MCC, how to select\ntrustworthy and high quality mobile cloud services becomes one of the most urgent problems. Therefore, this paper focuses on\nthe trustworthy service selection and recommendation in mobile cloud computing environments. We propose a novel service\nselection and recommendation model (SSRM), where user similarity is calculated based on user context information and interest.\nIn addition, the relational degree among services is calculated based on PropFlowalgorithmandwe utilize it to improve the accuracy\nof ranking results. SSRM supports a personalized and trusted selection of cloud services through taking into account mobile user�s\ntrust expectation. Simulation experiments are conducted on ns3 simulator to study the prediction performance of SSRM compared\nwith other two traditional approaches. The experimental results show the effectiveness of SSRM....
The process of creating nonphotorealistic rendering images and animations can be enjoyable if a useful method is involved.We use\nan evolutionary algorithmto generate painterly styles of images. Given an input image as the reference target, a cloud model-based\nevolutionary algorithm that will rerender the target image with nonphotorealistic effects is evolved. The resulting animations have\nan interesting characteristic inwhich the target slowly emerges froma set of strokes.Anumber of experiments are performed, aswell\nas visual comparisons, quantitative comparisons, and user studies. The average scores in normalized feature similarity of standard\npixel-wise peak signal-to-noise ratio, mean structural similarity, feature similarity, and gradient similarity based metric are 0.486,\n0.628, 0.579, and 0.640, respectively.The average scores in normalized aesthetic measures of Benford�s law, fractal dimension, global\ncontrast factor, and Shannon�s entropy are 0.630, 0.397, 0.418, and 0.708, respectively. Compared with those of similar method, the\naverage score of the proposed method, except peak signal-to-noise ratio, is higher by approximately 10%. The results suggest that\nthe proposedmethod can generate appealing images and animations with different styles by choosing different strokes, and it would\ninspire graphic designers who may be interested in computer-based evolutionary art....
Cloud computing plays a major role in smart cities development by facilitating the delivery of various services in an efficient and\neffective manner. In a Peer-to-Peer (P2P) federated clouds ecosystem, multiple Cloud Service Providers (CSPs) collaborate and\nshare services among them when experiencing a shortage in certain resources. Hence, incoming service requests to this specific\nresource can be delegated to other members. Nevertheless, the lack of preexisting trust relationship among CSPs in this distributed\nenvironment can affect the quality of service (QoS). Therefore, a trust management system is required to assist trustworthy peers\nin seeking reliable communication partners. We address this challenge by proposing TrustyFeer, a trust management system that\nallows peers to evaluate the trustworthiness of other peers based on subjective logic opinions, formulated using peers� reputations\nand Service Level Agreements (SLAs). To demonstrate the utility of TrustyFeer, we evaluate the performance of our method\nagainst two long-standing trust management systems. The simulation results show that TrustyFeer is more robust in decreasing the\npercentage of services that do not conformto SLAs and increasing the success rate of exchanged services by good CSPs conforming\nto SLAs.This should provide a trustworthy federated clouds ecosystem for a better, more sustainable future....
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