A Color-Based Cooperative Caching Strategy for Time-Shifted Live Video Streaming

Okada, Hiroki; Takayuki, Shiroma; Wu, Celimuge; Yoshinaga, Tsutomu

doi:10.1109/candarw.2018.00030

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…When users request content data from the chunks, Shiroma et al [13] demonstrated that network traffic can be reduced by caching popular chunks, based on access frequency, which varies depending on the playback position of content [13]. Okada et al [9] demonstrated that distributed cooperative caching is more efficient by assigning color tags to the segmented chunk data. We further divided the data into chunks and used the data corresponding to the SVC scheme described below.…”

Section: Cache Control Of Content On a Chunk Basismentioning

confidence: 99%

Load-based Content Allocation Scheme for Realizing Efficient Mobile Cooperative Cache

Akiba

Yoshinaga

2023

IJNC

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Owing to the rise in mobile users accessing high-quality video content, content delivery networks are under increased load. Therefore, a distributed cooperative caching technique, in which each mobile device functions as a cache server and shares a cache through deviceto-device communication has been proposed to alleviate the network load. However, efficient content placement on mobile devices is challenging, because the cache capacity of each mobile device is limited and did not remain at a fixed location. In this study, we propose a load-based content allocation (LBCA) method that efficiently distributes cache data to mobile devices based on the load of the base station (BS). The proposed scheme uses scalable video coding (SVC) that subdivides the content data hierarchically and dynamically selects the video quality depending on the network load. Additionally, we propose a multi-stage LBCA (M-LBCA) that divides the BS distribution area into concentric clusters to efficiently manage cache capacity for SVC data while considering the distance from the BS. Simulations demonstrated a decrease in the total number of users unable to continually view content on congested networks when using LBCA and M-LBCA as compared to the existing method in four evaluation environments. Therefore, our experiments demonstrate that the proposed cache control scheme improved the user's quality of experience.

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Section: Cache Control Of Content On a Chunk Basismentioning

confidence: 99%

Load-based Content Allocation Scheme for Realizing Efficient Mobile Cooperative Cache

Akiba

Yoshinaga

2023

IJNC

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“…Taking the communication distance and the number of communication hops as reference indexes for selecting the caching location can also effectively reduce the load of BSs and improve the caching efficiency. Okada et al [ 37 ] calculate the communication volume between users and caching nodes from the access probability and the number of communication hops, and select the caching location based on the communication volume. On the Internet of Vehicles (IoV), Bitaghsir et al [ 38 ] proposed a caching placement algorithm based on Multi-Armed Bandit Learning, which selects the content to be cached in the roadside unit (RSU) according to the content popularity, and then uses the user social characteristics to select the optimal caching path.…”

Section: Placement Optimizationmentioning

confidence: 99%

A Comprehensive Review on Edge Caching from the Perspective of Total Process: Placement, Policy and Delivery

Fan

Wang

et al. 2021

Sensors

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With the explosive growth of smart devices and mobile applications, mobile core networks face the challenge of exponential growth in traffic and computing demand. Edge caching is one of the most promising solutions to the problem. The main purpose of edge caching is to place popular content that users need at the edge of the network, borrow free space to reduce user waiting time, and lighten the network load by reducing the amount of duplicate data. Due to the promising advantages of edge caching, there have been many efforts motivated by this topic. In this paper, we have done an extensive survey on the existing work from our own perspectives. Distinguished from the existing review articles, our work not only investigates the latest articles in this area, but more importantly, covers all the researches of the total process of edge caching from caching placement optimization, policy design, to the content delivery process. In particular, we discuss the benefits of caching placement optimization from the perspective of different stakeholders, detail the delivery process, and conduct in-depth discussions from the five phases, i.e., requested content analysis, user model analysis, content retrieval, delivery, and update. Finally, we put forward several challenges and potential future directions, and hope to bring some ideas for the follow-up researches in this area.

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Live Video Stream Analysis in Real-Time Using Edge Enhanced Clouds

2024

2024 Third International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)

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A Color-Based Cooperative Caching Strategy for Time-Shifted Live Video Streaming

Cited by 3 publications

References 11 publications

Load-based Content Allocation Scheme for Realizing Efficient Mobile Cooperative Cache

Load-based Content Allocation Scheme for Realizing Efficient Mobile Cooperative Cache

A Comprehensive Review on Edge Caching from the Perspective of Total Process: Placement, Policy and Delivery

Live Video Stream Analysis in Real-Time Using Edge Enhanced Clouds

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