Headlight Prefetching and Dynamic Chaining for Cooperative Media Streaming in Mobile Environments

Wu, Shuang; Hsu, Jungchu; Chen, Chieh-Ming

doi:10.1109/tmc.2008.104

Cited by 23 publications

(1 citation statement)

References 40 publications

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“…Wu et al [6] proposed a prefetching technique that addresses several issues regarding handovers in mobile networks: (1) it continuously identifies the proper set of cells to prefetch the content to, (2) it prefetches more segments to the cells that are more likely to be visited, and (3) it determines the right timing to start and stop the prefetching to avoid possible stalls (rebuffering events).…”

Section: Related Workmentioning

confidence: 99%

SPACE: Segment Prefetching and Caching at the Edge for Adaptive Video Streaming

2023

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Multi-access Edge Computing (MEC) is a new paradigm that brings storage and computing close to the clients. MEC enables the deployment of complex network-assisted mechanisms for video streaming that improve clients' Quality of Experience (QoE). One of these mechanisms is segment prefetching, which transmits the future video segments in advance closer to the client to serve content with lower latency. In this work, for HAS-based (HTTP Adaptive Streaming) video streaming and specifically considering a cellular (e.g., 5G) network edge, we present our approach Segment Prefetching and Caching at the Edge for Adaptive Video Streaming (SPACE). We propose and analyze different segment prefetching policies that differ in resource utilization, player and radio metrics needed, and deployment complexity. This variety of policies can dynamically adapt to the network's current conditions and the service provider's needs. We present segment prefetching policies based on diverse approaches and techniques: past segment requests, segment transrating (i.e., reducing segment bitrate/quality), Markov prediction model, machine learning to predict future segment requests, and super-resolution. We study their performance and feasibility using metrics such as QoE characteristics, computing times, prefetching hits, and link bitrate consumption. We analyze and discuss which segment prefetching policy is better under which circumstances, as well as the influence of the client-side Adaptive Bit Rate (ABR) algorithm and the set of available representations ("bitrate ladder") in segment prefetching. Moreover, we examine the impact on segment prefetching of different caching policies for (pre-)fetched segments, including Least Recently Used (LRU), Least Frequently Used (LFU), and our proposed popularity-based caching policy Least Popular Used (LPU).INDEX TERMS Adaptive video streaming, content delivery, HAS, edge computing, cellular network edge, MEC, segment prefetching, segment caching.

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Section: Related Workmentioning

confidence: 99%

SPACE: Segment Prefetching and Caching at the Edge for Adaptive Video Streaming

2023

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Energy management control for supplying partner selection protocol in mobile peer‐to‐peer three‐dimensional streaming

Maamar

Alonso

Boukerche

et al. 2011

Concurrency and Computation

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SUMMARY In recent years, three‐dimensional (3D) streaming over thin mobile devices has received very little attention from the research community. The 3D streaming‐based class of applications uses either a centralized or a distributed approach. whereas the former presents several drawbacks such as latency, server's bottleneck, and networks congestion; the latter, that is, peer‐to‐peer, has to deal with the supplying partner issue that consists in selecting the source that will be responsible for streaming the required 3D data. Given that frequent 3D streaming overuses the mobile device's resources and dissipates its energy, the energy factor should be taken into consideration during the selection of the supplier. In this paper, we propose two energy management control protocols for supplying partner selection in peer‐to‐peer 3D streaming that we refer to as one‐level energy‐based and two‐level energy‐based. We also propose a new source load estimator that takes into account two factors namely the source's residual energy and its number of served requests. In one‐level energy‐based, the requester uses the source's load information to prioritize the sources in an ascending order and distribute the requests starting with the least loaded sources. In two‐level energy‐based, both the requester and the supplier have important and complementary roles and participate in the energy management control. We then report on the performance evaluation of our energy management control protocols using an extensive set of simulation experiments with the NS2 tool. Copyright © 2011 John Wiley & Sons, Ltd.

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A performance evaluation of mobility management and multihop supplying partner strategies for 3D streaming systems over thin mobile devices

Maamar

Boukerche

Petriu

2013

Concurrency and Computation

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Summary The recent advances in technology and mobile computing led to the rapid growth of networked 3D streaming applications. The emerging services can involve augmented reality, virtual environment walkthrough, multiplayer gaming just to mention a few. Because of the limited network bandwidth of the client‐server approach, research works are now turning toward mobile ad hoc networks‐based streaming, where the resources of each peer are used during the streaming service. Peer‐to‐peer technologies are considering the solution to adapt for scalable applications. Yet, supplying partner selection and 3D data delivery are still significant challenges to face because of the dynamic wireless environment that causes link breakages, high packet loss, an adverse impact on the quality of the 3D media, and a low user satisfaction. In this paper, we propose a supplying partner selection technique coupled with a content delivery technique for peer‐to‐peer 3D streaming over thin mobile devices. Our proposed protocol, which we refer to as MULTIPLY, considers multihop suppliers in order to alleviate the load on the server and uses the signal strength measurement to analyze the wireless link when sending back the 3D data. Given the high dynamicity of the network due to the mobility of the users, the streaming can be greatly affected. We therefore study the impact of the mobility on MULTIPLY. The performance evaluation of our protocol obtained using an extensive set of simulation experiments is then reported. Copyright © 2013 John Wiley & Sons, Ltd.

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Headlight Prefetching and Dynamic Chaining for Cooperative Media Streaming in Mobile Environments

Cited by 23 publications

References 40 publications

SPACE: Segment Prefetching and Caching at the Edge for Adaptive Video Streaming

SPACE: Segment Prefetching and Caching at the Edge for Adaptive Video Streaming

Energy management control for supplying partner selection protocol in mobile peer‐to‐peer three‐dimensional streaming

A performance evaluation of mobility management and multihop supplying partner strategies for 3D streaming systems over thin mobile devices

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