Understanding the effectiveness of video ads

Krishnan, Srinivas; Sitaraman, Ramesh K.

doi:10.1145/2504730.2504748

Cited by 58 publications

(53 citation statements)

References 11 publications

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“…The US portion of video streaming is 14% 13 and the number of US Unique IPv4 connected addresses is 17% [62]. The streaming workload is comprised of live streaming and on-demand streaming, with the relative fractions of 6% and 94% respectively [46]. Other predictions support similar ratios, 12% live-streaming and 88% for on-demand.…”

Section: On-demand Streaming and Cdnmentioning

confidence: 94%

“…On-demand streaming constitutes up to 85% of Internet traffic consumption [46]. On-demand streaming content is managed and distributed by content service providers.…”

Section: Enabling Green Content Distribution Network By Cloud Orchestmentioning

confidence: 99%

“…Also, video streams delivered by mobile terminals grew as mobile connectivity improved [62]. Video streaming is expected to constitute up to 85% of Internet consumers traffic [46] within a few years. The US portion of video streaming is 14% 13 and the number of US Unique IPv4 connected addresses is 17% [62].…”

Section: On-demand Streaming and Cdnmentioning

confidence: 99%

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Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

2017

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CLOUD COMPUTING COST AND ENERGY OPTIMIZATION THROUGH FEDERATED CLOUD SOSThe two most significant differentiators amongst contemporary Cloud Computing service providers have increased green energy use and datacenter resource utilization. This work addresses these two issues from a system's architectural optimization viewpoint. The proposed approach herein, allows multiple cloud providers to utilize their individual computing resources in three ways by:(1) cutting the number of datacenters needed, (2) scheduling available datacenter grid energy via aggregators to reduce costs and power outages, and lastly by (3) utilizing, where appropriate, more renewable and carbon-free energy sources. Altogether our proposed approach creates an alternative paradigm for a Federated Cloud SoS approach. The proposed paradigm employs a novel control methodology that is tuned to obtain both financial and environmental advantages. It also supports dynamic expansion and contraction of computing capabilities for handling sudden variations in service demand as well as for maximizing usage of time varying green energy supplies. Herein we analyze the core SoS requirements, concept synthesis, and functional architecture with an eye on avoiding inadvertent cascading conditions. We suggest a physical architecture that diminishes unwanted outcomes while encouraging desirable results. Finally, in our approach, the constituent cloud services retain their independent ownership, objectives, funding, and sustainability means.This work analyzes the core SoS requirements, concept synthesis, and functional architecture.It suggests a physical structure that simulates the primary SoS emergent behavior to diminish unwanted outcomes while encouraging desirable results. The report will analyze optimal computing generation methods, optimal energy utilization for computing generation as well as a procedure for building optimal datacenters using a unique hardware computing system design based on the openCompute community as an illustrative collaboration platform. Finally, the research concludes with ii security features cloud federation requires to support to protect its constituents, its constituents tenants and itself from security risks.iii ACKNOWLEDGEMENTS

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Section: On-demand Streaming and Cdnmentioning

confidence: 94%

“…On-demand streaming constitutes up to 85% of Internet traffic consumption [46]. On-demand streaming content is managed and distributed by content service providers.…”

Section: Enabling Green Content Distribution Network By Cloud Orchestmentioning

confidence: 99%

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Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

2017

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“…On-demand streaming constitutes up to 85% of Internet traffic consumption [5]. On-demand streaming content is managed and distributed by content service providers.…”

Section: Enabling Green Content Distribution Network By Cloud Orchestmentioning

confidence: 99%

“…Also, video streams delivered by mobile terminals grew as mobile connectivity improved [12]. Video streaming is expected to constitute up to 85% of Internet consumers traffic [5] within a few years. The US portion of video streaming is 14%…”

Section: On-demand Streaming and Cdnmentioning

confidence: 99%

Clean Energy Use for Cloud Computing Federation Workloads

Biran¹,

Pasricha²,

Collins³

et al. 2017

Adv. sci. technol. eng. syst. j.

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Cloud providers seek to maximize their market share. Traditionally, they deploy datacenters with sufficient capacity to accommodate their entire computing demand while maintaining geographical affinity to its customers. Achieving these goals by a single cloud provider is increasingly unrealistic from a cost of ownership perspective. Moreover, the carbon emissions from underutilized datacenters place an increasing demand on electricity and is a growing factor in the cost of cloud provider datacenters. Cloud-based systems may be classified into two categories: serving systems and analytical systems. We studied two primary workload types, on-demand video streaming as a serving system and MapReduce jobs as an analytical systems and suggested two unique energy mix usage for processing that workloads. The recognition that on-demand video streaming now constitutes the bulk portion of traffic to Internet consumers provides a path to mitigate rising energy demand. On-demand video is usually served through Content Delivery Networks (CDN), often scheduled in backend and edge datacenters. This publication describes a CDN deployment solution that utilizes green energy to supply on-demand streaming workload. A cross-cloud provider collaboration will allow cloud providers to both operate near their customers and reduce operational costs, primarily by lowering the datacenter deployments per provider ratio. Our approach optimizes cross-datacenters deployment. Specifically, we model an optimized CDN-edge instance allocation system that maximizes, under a set of realistic constraints, green energy utilization. The architecture of this cross-cloud coordinator service is based on Ubernetes, an open source container cluster manager that is a federation of Kubernetes clusters. It is shown how, under reasonable constraints, it can reduce the projected datacenter's carbon emissions growth by 22% from the currently reported consumption. We also suggest operating datacenters using energy mix sources as a VoltDB-based fast data system to process offline workloads such as MapReduce jobs. We show how cross-cloud coordinator service can reduce the projected datacenters carbon emissions growth by 21% from the currently expected trajectory when processing offline MapReduce jobs.

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