Our multimedia information retrieval Agent handles dynamic online material using an inventive method. It gathers processes, and stores current information in a variety of forms, including text, images, and video, usin...
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We show how the abstract exploration space of possible interactive communication media algorithms arises from implementing networking applications. Specifically, this abstract will describe the challenges to implement...
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The advent of the Internet of Things (IoT) and machine-to-machine (M2M) communication provide a system for collecting and manipulating big data and a platform for sensing, actuating, and automating the environment. Io...
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ISBN:
(纸本)9781665457194
The advent of the Internet of Things (IoT) and machine-to-machine (M2M) communication provide a system for collecting and manipulating big data and a platform for sensing, actuating, and automating the environment. IoT, M2M communication, social networking, and mass multimedia severely strain the communication infrastructure. Thus, the archaic communication frameworks require necessary improvements. One such improvement is the simultaneous usage of parallel communication links of differing radio access networks. This paper presents a Machine Learning (ML) optimization for link selection and use in CoopNet, a horizontal programmable communication architecture. Programmable networking paves the way for advancing communication to improve performance, reliability, security, and policy-based applications, including network decoupling. The ML implementation in CoopNet improves throughput by over 17%, delay by 10%, and reduces individual link utilization.
Mobile Edge computing (MEC) enables computation offloading from resource-constrained mobile devices to edge servers in close vicinity, effectively promoting the user experience on emerging interactive multimedia appli...
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ISBN:
(纸本)9781665491228
Mobile Edge computing (MEC) enables computation offloading from resource-constrained mobile devices to edge servers in close vicinity, effectively promoting the user experience on emerging interactive multimedia applications such as virtual/augmented reality, mobile gaming, and mobile video editing. However, most contemporary MEC offloading research disregards the interdependencies between partitioned subtasks of application. Also, few studies focused on application topologies have neglected to design effective incentives to encourage edge servers to provide offloading services. In this paper, we propose a dependency-aware offloading algorithm based on a multi-round truthful combinatorial reverse auction (MTCRA) to address the social welfare maximization problem in the paradigm of MEC. Building on the topology of directed acyclic graphs (DAGs) modeled from applications, we discuss the complementarity and substitutability of subtasks in the context of combinatorial auction. Theoretical analysis shows that the presented auction mechanism achieves computing efficiency while maintaining desirable economic features like truthfulness, individual rationality, and budget balance. Simulation results demonstrate that the proposed algorithm achieves high social welfare regarding reduced execution time and good economic benefits for MEC servers.
Remote sensing products include the generation of a class of geo-maps known as region-based geo-maps, such as choropleth and heatmaps. Comparing those maps is necessary for various real-time application scenarios and ...
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ISBN:
(纸本)9798350354744;9798350354737
Remote sensing products include the generation of a class of geo-maps known as region-based geo-maps, such as choropleth and heatmaps. Comparing those maps is necessary for various real-time application scenarios and geo-maps time series analysis. A major challenge in this process is the vectorization of the raster images, transforming them into a compact data distribution format, in a way that reflects the color themes and densities of the source raster images which represent the geo-maps captured. Aggregation and grouping in such a process is indispensable, which is computationally expensive. To tackle this problem, in this paper, we showcase the design and prototyping of a novel efficient system GeoMapComp, for comparing a specific kind of remote sensing products efficiently, region-based aggregation geo-maps. We specifically compare geo-maps using proxies that are based on geohash encoding, where we apply geohash encoding to divide the geo-map area into equally-sized rectangles, then apply data distribution comparison metrics to compare those proxies, delineating then the differences between maps in a mathematically principled manner, incorporates the geographical characteristics of geo-maps, and is general-purpose and applicable to several kinds of region-based aggregate geo-maps. The paper further contributes by comparing several distance and point-based metrics such as Jenssen-Shannon, KL Divergence, and RMSE. Our results demonstrate the skills of our system in comparing region-based aggregate geo-maps remote sensing products effectively.
Content transport fashions for allotted and Cooperative Media Algorithms in cellular Networks (DC-MAMR) is a unique technique to providing multimedia content material in mobile networks, the use of disbursed and coope...
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Malware may be classified into various families according to several factors, such as the method of delivery to an infected computing system, behaviors performed by the malware on an infected system, or through the pr...
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Metaverse system facilitated by Extended Reality (XR) requires extensive computing and communication resources to provide seamless services for users and has to resist jamming attacks. In this paper, we propose a rein...
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ISBN:
(纸本)9798350303582;9798350303599
Metaverse system facilitated by Extended Reality (XR) requires extensive computing and communication resources to provide seamless services for users and has to resist jamming attacks. In this paper, we propose a reinforcement learning based Metaverse resource allocation scheme against jamming, which optimizes the rendering mode, transmit channel, and power to fulfill the quality of experience (QoE) requirements for Metaverse services. This scheme incorporates both the background resolution, determined by the linear model of visual acuity decline, and the background correlation into the state formulation and rendering process, with both factors influencing the data size of the rendering task. Based on the required resolution, the background resolution, the data size of foreground and background, the background correlation, and the radio channel gain, the 2-level hierarchical architecture evaluates the expected utility of the rendering policy in the first level, and the transmission policy in the second level, and estimates the risk value depending on the latency to mitigate the risk of user experience disruption. Simulation results show that our proposed scheme reduces the service latency, conserves energy consumption, and enhances the QoE of Metaverse users.
Software-defined networking (SDN) has revolutionized the way in which current modern networks are constructed. SDN offers dynamic and centralized administration resources that are available for the network, but multim...
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The 5G network promised transformative services across various industries, yet its integration has mostly been limited to existing 4G services like IMS-based multimedia and IoT. This paper identifies two key reasons f...
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