Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105022
Title: Dynamic request redirection and elastic service scaling in cloud-centric media networks
Authors: Tang, Jianhua
Tay, Wee Peng
Wen, Yonggang
Keywords: DRNTU::Engineering::Electrical and electronic engineering
User Request Redirection
Service Capacity Scaling
Issue Date: 2014
Source: Tang, J., Tay, W. P., & Wen, Y. (2014). Dynamic request redirection and elastic service scaling in cloud-centric media networks. IEEE Transactions on Multimedia, 16(5), 1434-1445. doi:10.1109/TMM.2014.2308726
Series/Report no.: IEEE Transactions on Multimedia
Abstract: We consider the problem of optimally redirecting user requests in a cloud-centric media network (CCMN) to multiple destination Virtual Machines (VMs), which elastically scale their service capacities in order to minimize a cost function that includes service response times, computing costs, and routing costs. We also allow the request arrival process to switch between normal and flash crowd modes to model user requests to a CCMN. We quantify the trade-offs in flash crowd detection delay and false alarm frequency, request allocation rates, and service capacities at the VMs. We show that under each request arrival mode (normal or flash crowd), the optimal redirection policy can be found in terms of a price for each VM, which is a function of the VM's service cost, with requests redirected to VMs in order of nondecreasing prices, and no redirection to VMs with prices above a threshold price. Applying our proposed strategy to a YouTube request trace data set shows that our strategy outperforms various benchmark strategies. We also present simulation results when various arrival traffic characteristics are varied, which again suggest that our proposed strategy performs well under these conditions.
URI: https://hdl.handle.net/10356/105022
http://hdl.handle.net/10220/47845
ISSN: 1520-9210
DOI: 10.1109/TMM.2014.2308726
Rights: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TMM.2014.2308726.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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