Al-Azez, ZTS, Lawey, AQ, El-Gorashi, TEH et al. (1 more author) (2015) Virtualization Framework for Energy Efficient IoT Networks. In: Proceedings of 2015 IEEE 4th International Conference on Cloud Networking (CloudNet). Cloud Networking (CloudNet), 2015 IEEE 4th International Conference on, 05-07 Oct 2015, Niagara Falls, ON, Canada. IEEE , pp. 74-77.
Abstract
In this paper, we introduce a Mixed Integer Linear Programming (MILP) model to design an energy efficient cloud computing platform for Internet of Things (IoT) networks. In our model, the IoT network consisted of four layers. The first (lowest) layer consisted of IoT devices, e.g. temperature sensors. The networking elements (relays, coordinators and gateways) are located within the upper three layers, respectively. These networking elements perform the tasks of data aggregation and processing of the traffic produced by IoT devices. The processing of IoT traffic is handled by Virtual Machines (VMs) hosted by distributed mini clouds and located within the IoT networking elements. We optimized the number of mini clouds, their location and the placement of VMs to reduce the total power consumption induced by traffic aggregation and processing. Our results showed that the optimal distribution of mini clouds in the IoT network could yield a total power savings of up to 36% compared to processing IoT data in a single mini cloud located at the gateway layer.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | (c) 2015, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works. |
Keywords: | IoT; cloud computing; virtualization; energy efficiency |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/H040536/1 EPSRC EP/K016873/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 Jan 2016 16:21 |
Last Modified: | 12 Apr 2017 10:48 |
Published Version: | http://dx.doi.org/10.1109/CloudNet.2015.7335284 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/CloudNet.2015.7335284 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:92732 |