A Novel Distribution Service Policy for Crowdsourced Live Streaming in Cloud Platform

Dong, Chongwu; Yin, Jun; Peng, Haitao; Yang, Xiaoxing; Wen, Weisong

doi:10.1109/tnsm.2018.2800751

Cited by 16 publications

(12 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To derive the problem P1 with the above constraints, we can design a centralized strategy by applying the dual decomposition [34] to transform the above constrained problem to an equivalent, unconstrained Lagrangian. However, the dual decomposition converges slowly owing to its huge variable space, and should collect the information of all users.…”

Section: Modeling and Formulationmentioning

confidence: 99%

Joint Optimization for Task Offloading in Edge Computing: An Evolutionary Game Approach

Dong

Wen

2019

Sensors

Self Cite

View full text Add to dashboard Cite

The mobile edge computing (MEC) paradigm provides a promising solution to solve the resource-insufficiency problem in mobile terminals by offloading computation-intensive and delay-sensitive tasks to nearby edge nodes. However, limited computation resources in edge nodes may not be sufficient to serve excessive offloading tasks exceeding the computation capacities of edge nodes. Therefore, multiple edge clouds with a complementary central cloud coordinated to serve users is the efficient architecture to satisfy users’ Quality-of-Service (QoS) requirements while trying to minimize some network service providers’ cost. We study a dynamic, decentralized resource-allocation strategy based on evolutionary game theory to deal with task offloading to multiple heterogeneous edge nodes and central clouds among multi-users. In our strategy, the resource competition among multi-users is modeled by the process of replicator dynamics. During the process, our strategy can achieve one evolutionary equilibrium, meeting users’ QoS requirements under resource constraints of edge nodes. The stability and fairness of this strategy is also proved by mathematical analysis. Illustrative studies show the effectiveness of our proposed strategy, outperforming other alternative methods.

show abstract

Section: Modeling and Formulationmentioning

confidence: 99%

Joint Optimization for Task Offloading in Edge Computing: An Evolutionary Game Approach

Dong

Wen

2019

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…He et al in [18] and Dong et al in [19] consider fluctuation in the number of audio and video sources. In these two works, they consider numerous users as video broadcasters which live stream their video content such as their mobile camera feed or online game scenes.…”

Section: ) Non-conferencing Related Cloud Resource Allocation Solutionsmentioning

confidence: 99%

“…They only consider transcoding as a media handling service in their study. The authors in [19] propose an algorithm that makes a tradeoff between QoE of users and the total cost for a media service provider. None of these two works consider having a video mixing service.…”

Section: ) Non-conferencing Related Cloud Resource Allocation Solutionsmentioning

confidence: 99%

See 1 more Smart Citation

Resource Allocation Mechanism for Media Handling Services in Cloud Multimedia Conferencing

Soltanian

Naboulsi

Glitho

et al. 2019

IEEE J. Select. Areas Commun.

View full text Add to dashboard Cite

Multimedia conferencing is the conversational exchange of multimedia content between multiple parties. It has a wide range of applications (e.g., Massively Multiplayer Online Games (MMOGs) and distance learning). Media handling services (e.g., video mixing, transcoding, and compressing) are critical to multimedia conferencing. However, efficient resource usage and scalability still remain important challenges. Unfortunately, the cloud-based approaches proposed so far have several deficiencies in terms of efficiency in resource usage and scaling, while meeting Quality of Service (QoS) requirements. This paper proposes a solution which optimizes resource allocation and scales in terms of the number of participants while guaranteeing QoS. Moreover, our solution composes different media handling services to support the participants' demands. We formulate the resource allocation problem mathematically as an Integer Linear Programming (ILP) problem and design a heuristic for it. We evaluate our proposed solution for different numbers of participants and different participants' geographical distributions. Simulation results show that our resource allocation mechanism can compose the media handling services and allocate the required resources in an optimal manner while honoring the QoS in terms of end-to-end delay.

show abstract

“…Dong et al [17] have introduced a streaming-based method for constructing a data forwarding architecture to enhance the cloud service provider capacity. The presented study has used game theory using Nash equilibrium with an aid of a unique negotiation-based approach for the purpose of cost modeling of CDN system.…”

Section: Existing Approaches Of Cdnmentioning

confidence: 99%

An Investigational Study and Analysis of Cloud-based Content Delivery Network: Perspectives

Jayakumar¹,

Prakash²,

Akki³

2018

ijacsa

View full text Add to dashboard Cite

The content management includes a major technical strategy in the network paradigm of the internet which is called a Content delivery network. The design and the deployment of the CDN shall ensure optimal Quality of services (QoS). This paper aims to brief the taxonomy of the CDN along with its typical architecture. Much latest advancement in smartphones and smart devices which are content hungry require more efficient and reliable mechanism for the costeffective delivery of the contents irrespective of bottleneck constraints that leads to redesign the entire architecture of CDN on the cloud as CCDN or a new business model of CCDN as a service. The challenges of design for CCDN along with the evolved architecture are discussed in this paper.

show abstract

A Novel Distribution Service Policy for Crowdsourced Live Streaming in Cloud Platform

Cited by 16 publications

References 33 publications

Joint Optimization for Task Offloading in Edge Computing: An Evolutionary Game Approach

Joint Optimization for Task Offloading in Edge Computing: An Evolutionary Game Approach

Resource Allocation Mechanism for Media Handling Services in Cloud Multimedia Conferencing

An Investigational Study and Analysis of Cloud-based Content Delivery Network: Perspectives

Contact Info

Product

Resources

About