Relevant bibliographies by topics / Cooperative bandwidth aggregation

Academic literature on the topic 'Cooperative bandwidth aggregation'

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Published: 14 March 2023

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Journal articles on the topic "Cooperative bandwidth aggregation"

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Wang, Xueying, Yan Guo, Juliang Cao, Meiping Wu, Zhenqian Sun, and Chubing Lv. "Simplify Belief Propagation and Variation Expectation Maximization for Distributed Cooperative Localization." Applied Sciences 12, no. 8 (April 11, 2022): 3851. http://dx.doi.org/10.3390/app12083851.

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Only a specific location can make sensor data useful. The paper presents an simplify belief propagation and variation expectation maximization (SBPVEM) algorithm to achieve node localization by cooperating with another target node while lowering communication costs in a challenging environment where the anchor is sparse. A simplified belief propagation algorithm is proposed as the overall reasoning framework by modeling the cooperative localization problem as a graph model. The high-aggregation sampling and variation expectation–maximization algorithm is applied to sample and fit the complicated distribution. Experiments show that SBPVEM can obtain accurate node localization equal to NBP and SPAWN in a challenging environment while reducing bandwidth requirements. In addition, the SBPVEM has a better expressive ability than PVSPA, for SBPVEM is efficient in challenging environments.
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Liu, Yazhi, Dongyu Wei, Chunyang Zhang, and Wei Li. "Distributed Bandwidth Allocation Strategy for QoE Fairness of Multiple Video Streams in Bottleneck Links." Future Internet 14, no. 5 (May 18, 2022): 152. http://dx.doi.org/10.3390/fi14050152.

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In QoE fairness optimization of multiple video streams, a distributed video stream fairness scheduling strategy based on federated deep reinforcement learning is designed to address the problem of low bandwidth utilization due to unfair bandwidth allocation and the problematic convergence of distributed algorithms in cooperative control of multiple video streams. The proposed strategy predicts a reasonable bandwidth allocation weight for the current video stream according to its player state and the global characteristics provided by the server. Then the congestion control protocol allocates the proportion of available bandwidth, matching its bandwidth allocation weight to each video stream in the bottleneck link. The strategy trains a local predictive model on each client and periodically performs federated aggregation to generate the optimal global scheme. In addition, the proposed strategy constructs global parameters containing information about the overall state of the video system to improve the performance of the distributed scheduling algorithm. The experimental results show that the introduction of global parameters can improve the algorithm’s QoE fairness and overall QoE efficiency by 10% and 8%, respectively. The QoE fairness and overall QoE efficiency are improved by 8% and 7%, respectively, compared with the latest scheme.
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Chen, Lien-Wu, Yu-Hao Peng, Yu-Chee Tseng, and Ming-Fong Tsai. "Cooperative Sensing Data Collection and Distribution with Packet Collision Avoidance in Mobile Long-Thin Networks." Sensors 18, no. 10 (October 22, 2018): 3588. http://dx.doi.org/10.3390/s18103588.

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Mobile ad hoc networks (MANETs) have gained a lot of interests in research communities for the infrastructure-less self-organizing nature. A MANET with fleet cyclists using smartphones forms a two-tier mobile long-thin network (MLTN) along a common cycling route, where the high-tier network is composed of 3G/LTE interfaces and the low-tier network is composed of IEEE 802.11 interfaces. The low-tier network may consist of several path-like networks. This work investigates cooperative sensing data collection and distribution with packet collision avoidance in a two-tier MLTN. As numbers of cyclists upload their sensing data and download global fleet information frequently, serious bandwidth and latency problems may result if all members rely on their high-tier interfaces. We designed and analyzed a cooperative framework consisting of a distributed grouping mechanism, a group merging and splitting method, and a sensing data aggregation scheme. Through cooperation between the two tiers, the proposed framework outperforms existing works by significantly reducing the 3G/LTE data transmission and the number of 3G/LTE connections.
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Huang, Chung-Ming, Chia-Ching Yang, and Yu-Cheng Lin. "An Adaptive Video Streaming System Over a Cooperative Fleet of Vehicles Using the Mobile Bandwidth Aggregation Approach." IEEE Systems Journal 10, no. 2 (June 2016): 568–79. http://dx.doi.org/10.1109/jsyst.2014.2326002.

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Negrão, André Pessoa, João Costa, Paulo Ferreira, and Luís Veiga. "Interest Aware Consistency for Cooperative Editing in Heterogeneous Environments." International Journal of Cooperative Information Systems 23, no. 01 (March 2014): 1440002. http://dx.doi.org/10.1142/s0218843014400024.

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Cooperative editing applications enable geographically distributed users to concurrently edit a shared document space over a computer network. These applications present several technical challenges related to the scalability of the system and the promptness with which relevant updates are disseminated to the concerned users. This paper presents Cooperative Semantic Locality Awareness (CoopSLA), a consistency model for cooperative editing applications that is scalable and efficient with regards to user needs. In CoopSLA, updates to different parts of the document have different priorities, depending on the relative interest of the user in the region in which the update is performed; updates that are considered relevant are sent to the user promptly, while less important updates are postponed. As a result, the system makes a more intelligent usage of the network resources, since (1) it saves bandwidth by merging postponed updates and (2) it issues fewer accesses to the network resources as a result of both update merging and message aggregation. We have implemented a collaborative version of the open source Tex editor TexMaker using the CoopSLA approach. We present evaluation results that support our claim that CoopSLA is very effective regarding network usage while fulfilling user needs (e.g. ensuring that relevant updates are disseminated in time).
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Qin, Jiuren, Zhaoxue Wang, Kai Gao, and Lujie Zhong. "Failure-Aware and Delay-Predicted Multipath Virtual Queue Scheduling for Multimedia Transmission in Edge IoT." Mobile Information Systems 2020 (November 26, 2020): 1–12. http://dx.doi.org/10.1155/2020/6673134.

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The spread of Edge Internet of Things (IoT) radically changes our lifestyle. However, the multimedia services in edge IoT are still stuck by inefficiency. The dynamic typologies perplex the transmission of massive real-time data. To solve this problem, multipath transmission control protocol (MPTCP) which has a natural advantage in transmission robustness and bandwidth aggregation is becoming a good choice. In this paper, failure-aware and delay-predicted multipath virtual queue scheduling (FD-MVQS) is proposed to optimize the MPTCP performance in edge IoT. FD-MVQS constructs a two-plane cooperative scheduling system. In the control plane, the transmission failure estimation and chaos theory-based arrival delay prediction methods are introduced to provide the foundation for prescheduling. In the data plane, the multipath virtual queue scheduling is designed to allocate segments to different subflows. Simulation results showed that the proposed FD-MVQS performed better than standard and typical multipath transmission solutions in throughput, delay, and segment disorder.
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Fang, Chao, Tianyi Zhang, Jingjing Huang, Hang Xu, Zhaoming Hu, Yihui Yang, Zhuwei Wang, Zequan Zhou, and Xiling Luo. "A DRL-Driven Intelligent Optimization Strategy for Resource Allocation in Cloud-Edge-End Cooperation Environments." Symmetry 14, no. 10 (October 12, 2022): 2120. http://dx.doi.org/10.3390/sym14102120.

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Complex dynamic services and heterogeneous network environments make the asymmetrical control a curial issue to handle on the Internet. With the advent of the Internet of Things (IoT) and the fifth generation (5G), the emerging network applications lead to the explosive growth of mobile traffic while bringing forward more challenging service requirements to future radio access networks. Therefore, how to effectively allocate limited heterogeneous network resources to improve content delivery for massive application services to ensure network quality of service (QoS) becomes particularly urgent in heterogeneous network environments. To cope with the explosive mobile traffic caused by emerging Internet services, this paper designs an intelligent optimization strategy based on deep reinforcement learning (DRL) for resource allocation in heterogeneous cloud-edge-end collaboration environments. Meanwhile, the asymmetrical control problem caused by complex dynamic services and heterogeneous network environments is discussed and overcome by distributed cooperation among cloud-edge-end nodes in the system. Specifically, the multi-layer heterogeneous resource allocation problem is formulated as a maximal traffic offloading model, where content caching and request aggregation mechanisms are utilized. A novel DRL policy is proposed to improve content distribution by making cache replacement and task scheduling for arriving content requests in accordance with the information about users’ history requests, in-network cache capacity, available link bandwidth and topology structure. The performance of our proposed solution and its similar counterparts are analyzed in different network conditions.
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Liu, Zhenpeng, Zilin Gao, Jingyi Wang, Qiannan Liu, and Jianhang Wei. "PPEFL: An Edge Federated Learning Architecture with Privacy-Preserving Mechanism." Wireless Communications and Mobile Computing 2022 (November 11, 2022): 1–10. http://dx.doi.org/10.1155/2022/1657558.

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The emergence of federal learning makes up for some shortcomings of machine learning, and its distributed machine learning paradigm can effectively solve the problem of data islands, allowing users to collaboratively model without sharing data. Clients only need to train locally and upload model parameters. However, the computational power and resources of local users are frequently restricted, and ML consumes a large amount of computer resources and generates enormous communication consumption. Edge computing is characterized by low latency and low bandwidth, which makes it possible to offload complicated computing tasks from mobile devices and to execute them by the edge server. This paper is dedicated to reducing the communication cost of federation learning, improving the communication efficiency, and providing some privacy protection for it. An edge federation learning architecture with a privacy protection mechanism is proposed, which is named PPEFL. Through the cooperation of the cloud server, the edge server, and the edge device, there are two stages: the edge device and the edge server cooperate to complete the training and update of the local model, perform several lightweight local aggregations at the edge server, and upload to the cloud server and the cloud server aggregates the uploaded parameters and updates the global model until the model converges. The experimental results show that the architecture has good performance in terms of model accuracy and communication consumption and can well protect the privacy of edge federated learning.
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Dissertations / Theses on the topic "Cooperative bandwidth aggregation"

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DUAN, YUFENG. "Cooperative data transfers for 5G networks." Doctoral thesis, Politecnico di Torino, 2017. http://hdl.handle.net/11583/2667613.

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The demand for higher capacity, higher data rate and larger bandwidth has driven the research and industrial world to develop next generation wireless communication technology, namely, the 5G. Among all the approaches proposed for such a high demand, only the cooperative communication approach promises to significantly improve of the performances (capacity, data rate, bandwidth, etc.) with a low cost. In this thesis, we propose a D2D communication scheme as a solution for the out-door scenario and a cooperative scheme among the access infrastructures as the in-door scenario solution. In the first part, we address the implementation of content-centric routing in a D2D architecture for Android devices based on WiFi Direct, a protocol recently standardised by the Wi-Fi Alliance. After discussing the creation of multiple D2D groups, we introduce novel paradigms featuring intra- and inter-group bidirectional communication. We then present the primitives involved in content advertising and requesting among members of the multi-group network. In addition to the communications, we also devise a mechanism to enable the devices to spontaneously establish the multi-group D2D network. Finally, we evaluate the performance of our architecture and the network formation mechanism in a real testbed consisting of Android devices. In the second part, we propose, implement and evaluate a bandwidth aggregation service for residential users that allows to improve the upload throughput of the ADSL connection by leveraging the unused bandwidth of neighboring users. The residential access gateway adopts the 802.11 radio interface to simultaneously serve the local home users and to share the broadband connectivity with neighboring access gateways. Differently from previous works, our aggregation scheme is transparent both for local users, who are not required to modify their applications or device drivers, and for neighboring users, who do not experience any meaningful performance degradation. In order to evaluate the achievable performance and tune the parameters driving the traffic balancing, we developed a fluid model which was shown experimentally to be very accurate. Our proposed scheme is amenable to efficient implementation on Linux networking stack. Indeed, we implemented it and tested in some realistic scenarios, showing an efficient exploitation of the whole available bandwidth, also for legacy cloud storage applications.
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Hsiao-YuLin and 林孝諭. "A K-hop Member-based Cooperative Video Streaming System Using the Bandwidth Aggregation Scheme over Vehicular Networks." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/46703241528619335784.

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ChingYang, Chia, and 楊嘉慶. "QoS-awarely cooperative video streaming control protocols using wireless mobile networks’ bandwidth aggregation schemes over vehicular networks." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/64245912351872921061.

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博士
國立成功大學
資訊工程學系
102
With the development of vehicular networks, new types of networking services arise for automotive users. Since vehicles have high mobility, it is difficult to keep stable and reliable network connections between vehicles. With regard to multimedia streaming services, a vehicle may not have good QoS of video streaming using its own individual 3G/3.5G wireless interface. This dissertation is motivated to investigate the cooperative streaming scenario in the vehicular network. When a vehicle, which is called requester, requests a video stream from the Internet using its 3G/3.5G network, it asks helps from vehicles within its k-hop transmission range, in which these vehicles are called helpers, to download the requested video data cooperatively through these vehicles' 3G/3.5G network and then forward these downloaded video to the requested vehicle through V2V Dedicated Short-Range Communication (DSRC) networks. Since the topology of a vehicular network may change dynamically, a QoS-awarely cooperative video streaming control protocol is proposed to have better throughput of cooperative video streaming. We simulate the proposed schemes over (1) the 1-hop non-fleet based cooperative video streaming system, (2) the 1-hop fleet based cooperative video streaming system and (3) the k-hop fleet based cooperative video streaming system.
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Book chapters on the topic "Cooperative bandwidth aggregation"

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Taghikhaki, Zahra, Yang Zhang, Nirvana Meratnia, and Paul J. M. Havinga. "QoS-Aware Chain-Based Data Aggregation in Cooperating Vehicular Communication Networks and Wireless Sensor Networks." In Transportation Systems and Engineering, 874–96. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8473-7.ch044.

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Vehicular Communication Networks (VCNs) and Wireless Sensor Networks (WSNs) are emerging types of networks, which have individually been extensively explored. However, their cooperation and exploring advantages offered by their integration are poorly explored. Such integration helps better investigate impacts of human mobility and transportation behaviors on safety and well-being of cities, their residents, their surrounding environments, and ecology. In this chapter, the authors propose a QoS-Aware Chain-based data Aggregation (QoS-ACA) technique for wireless sensor networks cooperating with vehicular communication networks, which fast, reliably, and energy efficiently aggregates sensor data and sends the aggregated value to the road side units. Ensuring quality of service parameters has been put forward as an essential consideration for wireless sensor networks, which are often deployed in unattended and open environments and are characterized by their limited resources. To this end, in-network data aggregation is an efficient solution to save energy and bandwidth and to provide meaningful information to end-users.
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Conference papers on the topic "Cooperative bandwidth aggregation"

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Huang, Chung-Ming, Chia-Ching Yang, and Hsiao-Yu Lin. "A Bandwidth Aggregation Scheme for Member-Based Cooperative Networking over the Hybrid VANET." In 2011 IEEE 17th International Conference on Parallel and Distributed Systems (ICPADS). IEEE, 2011. http://dx.doi.org/10.1109/icpads.2011.1.

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