Novel Pre-pushing Scheme for Peer-Assisted Streaming Network based on Multi-leader Multi-follower Stackelberg Model

Lin, Fuhong; Zhou, Xianwei; Xing, Lu; Song, Wei

doi:10.1007/s11277-014-2009-3

Cited by 4 publications

(2 citation statements)

References 20 publications

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“…Compared with network-level QoS metrics, the metrics at application level are more generally applicable in diverse network contexts. They can manage the application-level QoS metrics through respective technology, such as service selection in content delivery network (CDN) [2], prepushing scheme in P2P network [43,44], and caching technique in fog computing [4,45,46], and then optimize user engagement based on the application-level QoS metrics involved in the QoE model.…”

Section: The Metric Of Qosmentioning

confidence: 99%

An Engagement Model Based on User Interest and QoS in Video Streaming Systems

Tan

Guo

Orgun

et al. 2018

Wireless Communications and Mobile Computing

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With the surging demand on high-quality mobile video services and the unabated development of new network technology, including fog computing, there is a need for a generalized quality of user experience (QoE) model that could provide insight for various network optimization designs. A good QoE, especially when measured as engagement, is an important optimization goal for investors and advertisers. Therefore, many works have focused on understanding how the factors, especially quality of service (QoS) factors, impact user engagement. However, the divergence of user interest is usually ignored or deliberatively decoupled from QoS and/or other objective factors. With an increasing trend towards personalization applications, it is necessary as well as feasible to consider user interest to satisfy aesthetic and personal needs of users when optimizing user engagement. We first propose an Extraction-Inference (E-I) algorithm to estimate the user interest from easily obtained user behaviors. Based on our empirical analysis on a large-scale dataset, we then build a QoS and user Interest based Engagement (QI-E) regression model. Through experiments on our dataset, we demonstrate that the proposed model reaches an improvement in accuracy by 9.99% over the baseline model which only considers QoS factors. The proposed model has potential for designing QoE-oriented scheduling strategies in various network scenarios, especially in the fog computing context.

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Section: The Metric Of Qosmentioning

confidence: 99%

An Engagement Model Based on User Interest and QoS in Video Streaming Systems

Tan

Guo

Orgun

et al. 2018

Wireless Communications and Mobile Computing

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“…Generally, pricing mechanisms mainly concentrate on motivating users to share resource with others and not declining other users' requests by relating their behaviors to a financial utility or mechanism. Several interesting pricing approaches have been presented for P2Ps in recent years, for example, the lottery-based scheme (Zghaibeh and Harmantzis, 2008), the Lagrangian multiplier method (Eger and Killat, 2007;Koutsopoulos and Iosifidis, 2010;Neely and Golubchik, 2011), the microeconomics-based approach (Kumar et al, 2011;Analoui and Rezvani, 2011), auction-based mechanisms Zuo and Zhang, 2013), and game-based ones (Park and Van Der Schaar, 2010;Nakano and Okaie, 2010;Okaie and Nakano, 2012;Kang and Wu, 2015;Lin et al, 2015). In this paper we propose a pricing scheme to achieve reasonable resource allocation in P2P file-sharing networks.…”

mentioning

confidence: 99%

A scheme of resource allocation and stability for peer–to–peer file–sharing networks

Sun

Chengguo

et al. 2016

International Journal of Applied Mathematics and Computer Science

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Peer-to-peer (P2P) networks offer a cost-effective and easily deployable framework for sharing content. However, P2P file-sharing applications face a fundamental problem of unfairness. Pricing is regarded as an effective way to provide incentives to peers to cooperate. In this paper we propose a pricing scheme to achieve reasonable resource allocation in P2P file-sharing networks, and give an interpretation for the utility maximization problem and its sub-problems from an economic point of view. We also deduce the exact expression of optimal resource allocation for each peer, and confirm it with both simulation and optimization software. In order to realize the optimum in a decentralized architecture, we present a novel price-based algorithm and discuss its stability based on Lyapunov stability theory. Simulation results confirm that the proposed algorithm can attain an optimum within reasonable convergence times.

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Multilevel Optimisation

Antoniou¹,

Korošec²

2020

Optimization Under Uncertainty With Applications to Aerospace Engineering

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Novel Pre-pushing Scheme for Peer-Assisted Streaming Network based on Multi-leader Multi-follower Stackelberg Model

Cited by 4 publications

References 20 publications

An Engagement Model Based on User Interest and QoS in Video Streaming Systems

An Engagement Model Based on User Interest and QoS in Video Streaming Systems

A scheme of resource allocation and stability for peer–to–peer file–sharing networks

Multilevel Optimisation

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