Journal of Innovation in Digital Ecosystems最新文献

Several solutions have been proposed till date to achieve effective replication policies and admission control methods that can ensure a high Quality of Service (QoS) to Video on Demand (VoD) systems. In this paper, we have chosen to study admission control and a replication strategy in a video on demand system called Feedback Control Architecture for Distributed Multimedia Systems (FCA-DMS). The proposed approaches are founded on (i) the supervision and auto-adaptation of the system load, (ii) continued knowledge of the network and of the video servers’ workload, and (iii) the development of a dynamic replication strategy of segments for popular video, that remade to replica-placement problem by discussing the problem of the replicas number to create (Replication Degree). The workload of video servers and of network are calculated by a QoS controller. The proposed approach takes into account of replica detail and offers a replica removal policy to avoid waste and for a good management of storage space. The goal is to maintain an updated broad view of the system’s behaviour from the collected measurements to databases of available videos and databases of available video servers. To demonstrate the efficiency and feasibility of our approaches and validate the results obtained, we conducted a series of experiments based on a simulator that we implemented.

In this paper, a new method for the detection of switching time is proposed for discrete-time linear switched systems, whose switching mechanism is unknown. The switching instant estimation problem consists to predict the mode switching for discrete behavior from a finite set of input–output data. First, the proposed method use a clustering and classification approach define the number of submodels and the data repartition. Then, by the use of statistical learning approach, we define the linear boundary separator of each validity region. Finally, a technique of detection given an explicitly estimation of switching time. A numerical example was reported to evaluate the proposed method.

The need for protecting a huge amount of digital images on the internet has become an important requirement against different kind of attacks in order to insure transmitted process in a secure way. Cryptography introduces many security goals to achieve privacy of image include confidentiality, authentication and integrity. Encryption process may applied on the result of JPEG DCT-based encoding process, which are DC and AC coefficients, where DC coefficients present the average of the overall magnitude of the input image and AC coefficients present the higher frequency components of image. In this paper, we develop a new model for securing the transmitted images via wireless network by parsing JPEG bitstream to encrypting both DC and AC coefficients in each 8×8 block of image. This work utilizes the features of DCT-based encoding process preserving low complexity, efficient compression, and robustness to protect the image integrity. The experiments result shows that the proposed approach gives an interesting and a significant robustness ratio reaching a range of 60.3 dB for Peak Signal-to-Noise Ratio (PSNR) and a 0.006% for Bit Error Rate (BER) in average. The obtained results are discussed in details.

A watermarking field is necessary to prove the copyright, ownership, authenticity and other related security aspects of the electronic data. Semi-Blind watermarking refers to need the watermark image during the extraction process. While, informed watermarking generates the watermark data from the original image itself. Moreover, Tamper detection is useful to discover the tamper zone in the image. In this paper, we propose a semi blind and informed watermarking approach. We build the watermark from the original image using Weber Law. Our approach aims to provide a high robustness and imperceptibility with perfectly tamper detection zone. We divide the original image into blocks and the main pixel is chosen for watermark insertion, where the embedding/extraction operates in the spatial domain. The tamper detection is tested by tampering watermarked image, and then based on the extracted attacked watermark; we can discover the tamper area. Also, the robustness watermarking aspect is proved against different kind of geometric and non-geometric attacks. Based on the experimental results, the imperceptibility and robustness of our watermarking approach are proven and showing perfectly the detection of the tamper zones.

Processing specifications is an issue of crucial importance when developing critical complex systems. In particular, establishing rigorous specifications broadly impacts the subsequent engineering phases. This paper discusses a refinement technique for processing informal specifications expressed in a literal shape, with the aim to generate formal specifications appropriate to automatic processing. The developed technique carries out an iterative process which relies on a set of basic refinement patterns that we have established, and ends up with a formalization step which actually generates logical CTL* formulas. Furthermore, the method implements traceability facilities, which allow for a tidy backtracking of the whole process. The concepts introduced to set up the various mechanisms are discussed and a case study featuring an embedded railway control system is used to illustrate our technique.

In this paper, we describe a method for automatic detection and manual localization of four compositional translation errors and shifts between automatically aligned segments in source and target languages. The automatic detection of errors and shifts is based on a content word precision algorithm which measures the equality of information content between source and target segments. The manual localization of errors and shifts within the segments is based on the compositionality principle. The method allows for the detection and localization of two potential errors; omission and addition, as well as two translation shifts required to avoid a translation error such as over-translation (when a correct translation results in more content words than in the source segment) and under-translation (when a correct translation results in less content words than in the source segment). Because of manual localization within bilingual pairs of segments, the method is not intended for automatic error detection but for human-assisted revision of translations. The analysis, described with the method and the algorithm is applied to real translation examples culled from a state-of-the-art translation corpus sampled for various translation errors. The algorithm and the localization method have implications for the development of more content-oriented natural language processing as well as for the training of professional translators; they can also be useful for formal and systematic description of content-based translation errors.

Cost models are broadly used in query processing to drive the query optimization process, accurately predict the query execution time, schedule database query tasks, apply admission control and derive resource requirements to name a few applications. The main role of cost models is to estimate the time needed to run the query on a specific machine. In a multi-cloud environment, cost models should be easily calibrated for a wide range of different physical machines, and time estimates need to be complemented with monetary cost information, since both the economic cost and the performance are of primary importance. This work aims to serve as the first proposal for a bi-objective query cost model suitable for queries executed over resources provided by potentially multiple cloud providers. We leverage existing calibrating modeling techniques for time estimates and we couple such estimates with monetary cost information covering the main charging options for using cloud resources. Moreover, we explain how the cost model can become part of an optimizer. Our approach is applicable to more generic data flow graphs, the execution plans of which do not necessarily comprise relational operators. Finally, we give a concrete example about the usage of our proposal and we validate its accuracy through real case studies.

Due to the many advantages offered by the cloud computing paradigm, it is fast becoming an enabling technology for many organizations, and even individual users. Flexibility and availability are two of the most important features that promote the wide spread adoption of this technology. In cloud-based data storage scenarios, where the data is controlled by a third party (i.e. the cloud service provider), the data owner usually does not have full control of its data at all stages. Consequently, this poses a prime security threat, and a major challenge is the development of a secure protocol for data storage, sharing, and retrieval. In recent years, a number of research works have targeted this problem. In this paper, we discuss some of the major approaches for secure data sharing in the cloud computing environment. The goal is to provide a concise survey of existing solutions, discuss their benefits, and point out any shortcomings for future research. Specifically, we focus on the use of encryption schemes, and provide a comparative study of the major schemes, through implementation of some representative frameworks.

In this paper, we present a flexible, modular, consistent, and coherent approach for language and text processing engineering. Each processing chain dedicated to text processing is regarded as a serial or parallel assembly of modules, underlying particular tasks a user wants to apply to a text. Users, according to their needs and perspectives might want to build and validate their own processing chain by assembling a set of modules according to a certain configuration. In this paper, we suggest a theoretical formal system based on the model of the typed applicative grammars and the combinatory logic. This approach allows providing a general framework in which users would be able to build multiple language and text analysis processes according to their own objectives. It will also systematize the verification of the logical consistency of the sequence of modules in the assembly that characterizes a given processing chain.

Ubiquitous sensing and actuating devices are now everywhere in our living environment as part of the global cyber–physical ecosystem. Sensing and actuating capabilities can be modeled as services to compose intelligent Internet of Things (IoT) applications. An issue for perpetually running and managing these IoT devices is the energy cost. One energy saving strategy is to co-locate several services on one device in order to reduce the computing and communication energy. In this paper, we propose a service merging strategy for mapping and co-locating multiple services on devices. In a multi-hop network, the service co-location problem is formulated as a quadratic programming problem. We show a reduction method that reduces it to the integer programming problem. In a single hop network, the service co-location problem can be modeled as the Maximum Weighted Independent Set (MWIS) problem. We show the algorithm to transform a service flow to a co-location graph, then use known heuristic algorithms to find the maximum independent set which is the basis for making service co-location decisions. The performance of different co-location algorithms are evaluated by simulation in this paper.