Optical wireless network convergence in support of energy-efficient mobile cloud services

Mobile computation offloading has been identified as a key-enabling technology to overcome the inherent processing power and storage constraints of mobile end devices. To satisfy the low-latency requirements of content-rich mobile applications, existing mobile cloud computing solutions allow mobile...

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Bibliographic Details
Published in:Photonic network communications Vol. 29; no. 3; pp. 269 - 281
Main Authors: Anastasopoulos, Markos P., Tzanakaki, Anna, Rofoee, Bijan Rahimzadeh, Peng, Shuping, Yan, Yan, Simeonidou, Dimitra, Landi, Giada, Bernini, Giacomo, Ciulli, Nicola, Riera, Jordi Ferrer, Escalona, Eduard, Katsalis, Kostas, Korakis, Thanasis
Format: Journal Article
Language:English
Published: New York Springer US 01.06.2015
Subjects:
Characterization and Evaluation of Materials
Computer Communication Networks
Computer Science
Electrical Engineering
Mobile cloud computing
Converged infrastructures
Energy efficiency
Queuing theory
Virtual infrastructure planning
ISSN:1387-974X, 1572-8188
Online Access:Get full text
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Summary:Mobile computation offloading has been identified as a key-enabling technology to overcome the inherent processing power and storage constraints of mobile end devices. To satisfy the low-latency requirements of content-rich mobile applications, existing mobile cloud computing solutions allow mobile devices to access the required resources by accessing a nearby resource-rich cloudlet, suffering increased capital and operational expenditures. To address this issue, in this paper, we propose an infrastructure and architectural approach based on the orchestrated planning and operation of optical data center networks and wireless access networks. To this end, a novel formulation based on a multi-objective nonlinear programming model is presented that considers energy-efficient virtual infrastructure planning over the converged wireless, optical network interconnecting DCs with mobile devices, taking a holistic view of the infrastructure. Our modelling results identify trends and trade-offs relating to end-to-end service delay, mobility, resource requirements and energy consumption levels of the infrastructure across the various technology domains.
ISSN:1387-974X
1572-8188
DOI:10.1007/s11107-015-0494-2