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Loop Parallelism Maximization for multimedia data processing in Mobile Vehicular Clouds

IEEE TRANSACTIONS ON CLOUD COMPUTING 2019年第1期7卷 250-258页

作者： Qiu, Meikang Dai, Wenyun Vasilakos, Athanasios V. Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Peoples R China Pace Univ Seidenberg Sch Comp Sci & Informat Syst New York NY 10038 USA Univ Western Macedonia Kozani 50100 Greece

Mobile vehicular cloud has become popular with the rapid development of cloud computing and mobile computing. Nested loops are usually the most critical part in multimedia and high performance Digital Signal processing (DSP) systems which are widely used in vehicular applications and systems. In order to further explore the parallelism in nested loops, we study how to maximize the system performance with considering the energy reduction for applications on Chip Multiprocessor (CMP) architectures. We propose an algorithm Energy-Aware Loop Parallelism Maximization (EALPM) to maximize the system performance with the consideration of energy reduction for applications with multidimensional nested loops. Our experiment shows that using the EALPM algorithm significantly improves both performance and energy consumption on average in comparision to other algorithms.

关键词： Loop parallelization mobile vehicular cloud energy-aware nested loops multimedia data processing

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Evaluation and Analysis of System Latency of Edge Computing for multimedia data processing 5

Evaluation and Analysis of System Latency of Edge Computing ...

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5th IEEE Global Conference on Consumer Electronics

作者： Imagane, Kentaro Kanai, Kenji Katto, Jiro Tsuda, Toshitaka Waseda Univ Dept Comp Sci & Commun Engn Tokyo Japan

In order to analyze system latency of edge computing for multimedia data processing, we propose a model of system latency of two different distributed processing scenarios: pipeline and parallel processing. We validat... 详细信息

ISBN: (纸本)9781509023332

关键词： Edge Computing multimedia data processing Distribution processing

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Supervised and Unsupervised data Engineering for multimedia data 1

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2024年

作者： Suman Kumar Swarnkar J P Patra Sapna Singh Kshatri Yogesh Kumar Rathore Tien Anh Tran

SUPERVISED and UNSUPERVISED data ENGINEERING for multimedia data Explore the cutting-edge realms of data engineering in multimedia with Supervised and Unsupervised data Engineering for multimedia data, where expert co... 详细信息

ISBN: (数字)9781119786443

ISBN: (纸本)9781119786344

关键词： multimedia data processing computing artificial intelligence data engineering healthcare sector machine learning data analysis computer science technology applications AI applications healthcare technology information systems data analytics data mining computer vision pattern recognition multimedia applications

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A closed-loop healthcare processing approach based on deep reinforcement learning

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multimedia TOOLS AND APPLICATIONS 2022年第3期81卷 3107-3129页

作者： Dai, Yinglong Wang, Guojun Muhammad, Khan Liu, Shuai Hunan Normal Univ Hunan Prov Key Lab Intelligent Comp & Language In Changsha 410081 Hunan Peoples R China Guangzhou Univ Sch Comp Sci Guangzhou 510006 Peoples R China Sejong Univ Dept Software Seoul 143747 South Korea

In healthcare, the human body is a controlled input-output system, which generates different observations with the variations of external interventions. The intervention acts as the input, and the output is the phenotype observation that reflects the latent health state of the body system. The objective of healthcare is to determine effective intervention strategies that can nurse an unhealthy human body to a healthy state. With the advances of Internet-of-Things (IoT) and body sensor networks, it becomes convenient to observe the multimedia data of the human body anywhere and anytime. To aid healthcare decision making, we put forward to construct the human body simulators based on deep neural networks (DNNs) for healthcare research. At first, we formulate the model of the human body system based on DNNs. During our analysis, we realize that DNN-based models could simulate practical situations, e.g. some health states are unreachable. Then, we combine deep reinforcement learning (DRL) with conceptual embedding techniques to explore effective healthcare strategies for simulated human bodies. We implement a virtual human body simulator, which can take interventions and represent its hidden states by high-dimensional images, and a DRL-based treatment module, which can diagnose latent health state through the image observations and choose interventions to nurse the simulated body to a target state. By combining the body simulator and treatment module, we create a dynamic closed-loop for healthcare information processing. Experimental simulations are performed to validate the feasibility of the offered approach.

关键词： Deep neural networks Deep reinforcement learning Healthcare Simulation multimedia data processing

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Improving communication skills of children with autism through support of applied behavioral analysis treatments using multimedia computing: a survey

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UNIVERSAL ACCESS IN THE INFORMATION SOCIETY 2021年第1期20卷 13-30页

作者： Heath, Corey D. C. McDaniel, Troy Venkateswara, Hemanth Panchanathan, Sethuraman Arizona State Univ Sch Comp Informat & Decis Syst Engn 699 S Mill Ave Tempe AZ 85251 USA

Naturalistic applied behavior analysis (ABA) techniques have been shown to help children with autism improve their communication skills. Recognizing that individuals who interact with children regularly are in the position to utilize treatments with profound effects, researchers have examined methodologies for training parents, teachers, and peers to implement treatments. These programs are time intensive and often unable to support trainees after training. Technologies need to be examined to determine how they can aid in the educational and support process. Academic publications and publicly available training programs were reviewed to determine the types of participants, methodologies, and training durations that have been reported for instructing interventionists. These resources illustrate a need to make programs more accessible. To address this, selected computer science research is applied to methods of evaluating ABA implementations in order to recommend how the technologies could be utilized to make training and support programs more accessible. Review results of instructional programs, both in research and available in the community, illustrate the challenges in providing training in ABA methodologies. Modern research in multimedia data processing and machine learning could be applied to reduce the human cost of training and support individuals implementing ABA techniques. Utilizing machine learning techniques to analyze video probes of naturalistic ABA treatment implementation could alleviate the human cost of evaluating fidelity, allowing for greater support for individuals interested in the treatments. These technologies could be used in the future to expand data collection to provide more perspective on the treatments.

关键词： Applied behavior analysis Pivotal response treatment Autism spectrum disorder Parent training multimedia data processing Machine learning

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Pushing the Boundary of multimedia Big data: An Overview of IEEE MIPR

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IEEE multimedia 2019年第2期26卷 87-91页

作者： Su, Guan-Ming Zhang, Chengcui Wang, Haohong Chen, Min Kankanhalli, Mohan Lienhart, Rainer Dolby Labs Imaging Appl Res San Francisco CA 94103 USA Univ Alabama Dept Comp Sci Tuscaloosa AL 35487 USA TCL Res Amer San Jose CA USA Univ Washington Bothell Sch STEM Comp & Software Syst Bothell WA USA Natl Univ Sch Comp Singapore Singapore Univ Augsburg Comp Vis Lab Multimedia Comp Augsburg Germany

New forms of multimedia data (such as text, numbers, tags, networking, signals, geo-tagged information, graphs/relationships, three-dimensional/VR/AR and sensor data, etc.) have emerged in many applications in addition to traditional multimedia data (image, video, audio). multimedia has become the biggest of big data as the foundation of today's data-driven discoveries. Almost all disciplines of science and engineering, as well as social sciences, involve multimedia data in some forms, such as recording experiments, driverless cars, unmanned aerial vehicles, smart communities, biomedical instruments, security surveillance. Some recent events demonstrate the power of real-time broadcast of unfolding events on social networks. multimedia data is not just big in volume, but also multi-modal and mostly unstructured. Storing, indexing, searching, integrating, and recognizing from the vast amounts of data create unprecedented challenges. Even though significant progress has been made processing multimedia data, today's solutions are inadequate in handling data from millions of sources simultaneously. The IEEE International Conference on multimedia Information processing and Retrieval (IEEE-MIPR) aims to provide a forum for original research contributions and practical system design, implementation, and applications of multimedia information processing and retrieval for single modality or multiple modalities. The target audiences are university researchers, scientists, industry practitioners, software engineers, and graduate students who want to become acquainted with technologies for big data analytics, machine intelligence, information fusion in multimedia information processing and retrieval. Following a successful debut in Miami, Florida in 2018, the second MIPR, held in San Jose, California, attracted over 140 submissions and more than 100 attendees-a big growth from its inaugural event and an indication of its growing visibility and popularity in the multimedia resea

关键词： Big data data Analysis Information Retrieval multimedia Computing IEEE MIPR Big data Analytics multimedia Big data multimedia data processing multimedia Information processing And Retrieval data Handling IEEE International Conference Machine Intelligence Information Fusion Streaming Media multimedia Computing Computer Vision Technological Innovation Big data Information Retrieval data Analysis

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Adaptive Computing-Plus-Communication Optimization Framework for multimedia processing in Cloud Systems

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2020年第4期8卷 1162-1175页

作者： Shojafar, Mohammad Canali, Claudia Lancellotti, Riccardo Abawajy, Jemal Univ Modena & Reggio Emilia Comp Engn Dept Enzo Ferrari Via Vivarelli 10-1 I-41121 Modena MO Italy Deakin Univ Fac Sci Engn & Built Environm Burwood Vic 3146 Australia

A clear trend in the evolution of network-based services is the ever-increasing amount of multimedia data involved. This trend towards big-data multimedia processing finds its natural placement together with the adoption of the cloud computing paradigm, that seems the best solution to cope with the demands of a highly fluctuating workload that characterizes this type of services. However, as cloud data centers become more and more powerful, energy consumption becomes a major challenge both for environmental concerns and for economic reasons. An effective approach to improve energy efficiency in cloud data centers is to rely on traffic engineering techniques to dynamically adapt the number of active servers to the current workload. Towards this aim, we propose a joint computing-plus-communication optimization framework exploiting virtualization technologies, called MMGreen. Our proposal specifically addresses the typical scenario of multimedia data processing with computationally intensive tasks and exchange of a big volume of data. The proposed framework not only ensures users the Quality of Service (through Service Level Agreements), but also achieves maximum energy saving and attains green cloud computing goals in a fully distributed fashion by utilizing the DVFS-based CPU frequencies. To evaluate the actual effectiveness of the proposed framework, we conduct experiments with MMGreen under real-world and synthetic workload traces. The results of the experiments show that MMGreen may significantly reduce the energy cost for computing, communication and reconfiguration with respect to the previous resource provisioning strategies, respecting the SLA constraints.

关键词： multimedia data processing cloud resource management load balancing dynamic voltage and frequency scaling (DVFS) traffic engineering

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multimedia Independent Multipath Routing Algorithms for Internet of Things Based on a Node Hidden Communication Model

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FUTURE INTERNET 2019年第11期11卷 240-240页

作者： Wu, Cong Yang, Jianhui Zhoukou Normal Univ Sch Comp Sci & Technol Zhoukou 466001 Peoples R China Zhoukou Normal Univ Sch Math & Stat Zhoukou 466001 Peoples R China

In order to achieve a multi-path routing algorithm with time delay and energy consumption balance to alleviate the energy holes around a sink, a multimedia independent multipath routing algorithm for internet of things (IoT) based on node hidden communication model is proposed in this paper. On the premise of satisfying the application delay, a multi-source multi-path routing algorithm is proposed by using the idea of software definition and fitting multiple curves to form independent multi-path routing. Through a sink node centralized programming control source node routing, according to the priority of the source node, the dynamic angle of the source node can be allocated, which effectively reduces the energy consumption of the network. In addition, considering that the Internet of Things has more perceptive nodes, limited computing and storage capacity, frequent joining and exiting operations and other factors, a hidden communication model of nodes is designed for the IoT. It is helpful to improve the level of privacy protection in the IoT, and to effectively improve the ability of nodes to resist attacks in the IoT. The experimental results show that the proposed algorithm avoids the interference between paths and various network attacks to the greatest extent, and the energy consumption is relatively low under the requirement of quality of service (QoS) delay.

关键词： independent multipath routing algorithm the Internet of things wireless multimedia sensor network (WMSNs) multimedia data processing node concealment communication model multimedia security the network energy consumption

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multimedia data processing algorithm development environment (MADE)

Multimedia data processing algorithm development environment...

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Conference on Visual data Exploration and Analysis VI

作者： Lee, J Chae, O Kyung Hee Univ Dept Comp Engn YongIn Si 449701 KyungKi Do South Korea

ISBN: (纸本)0819431141

This paper presents the system called "MADE". MADE is an object-oriented software environment for research and application development for multimedia data processing. It is an integrated environment that supports algorithm development, management, and testing. It provides tools for image, sound, and graphic data processing even though the main emphasis is on image processing. The proposed system adopts a true object-oriented approach supporting well-separated data classes similar to IUE classes and provides multiple user interfaces for various classes of users. By separating the interface layer from data processing functions, it allows algorithm developers to write their functions without worrying about user interface programming. It is specially designed to work with both graphic and image objects in the same domain. It can display and edit image features in the graphic domain and process them in the image domain.

关键词： IUE algorithm development tool visual programming tool multimedia data processing C interpreter object-oriented programming

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CONCURRENCY-CONTROL WITH PERMISSIBLE SERIALIZABILITY IN multimedia data processingS

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 1995年第4期E78D卷 336-344页

作者： SAKAUE, Y MIYAO, J Hiroshima Univ Higashihiroshima-shi Japan

Recent advances of processing speed and window systems in computers, especially workstations, accelerate multi-media data processing (MMDP). Then. a variety of data such as numerics, characters, voice, video, animation and so on, are processed concurrently in a workstation. In data processings. concurrent execution of transactions is a key to improve throughputs. However, concurrent execution without concurrency control may cause inconsistent results. Thus. the concurrency control must be introduced in such systems. However? in MMDP it is ineffective to adopt previous concurrency control methods for ordinal databases since multi-media data are huge and possess a real-time property. This paper discusses concurrency control for MMDP. We propose some new concepts for MMDP. and define a new serializability class called Permissible Serializability which provides high concurrency in MMDP compared with ordinal classes. Then, we propose a concurrency control algorithm TYPE for the Permissible Serializability, and show some simulation results.

关键词： multimedia data processing CONCURRENCY CONTROL REAL-TIME SCHEDULING AND dataBASE SYSTEMS

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