Al-Azez, ZT, Lawey, AQ orcid.org/0000-0003-3571-4110, El-Gorashi, TEH et al. (1 more author) (2019) Energy Efficient IoT Virtualization Framework with Peer to Peer Networking and Processing. IEEE Access, 7. pp. 50697-50709. ISSN 2169-3536
Abstract
In this paper, an energy efficient IoT virtualization framework with peer-to-peer (P2P) networking and edge processing is proposed. In this network, the IoT task processing requests are served by peers. The peers in our work are represented by IoT objects and relays that host virtual machines (VMs). We have considered three scenarios to investigate the saving in power consumption and the system capabilities in terms of task processing. The first scenario is a ‘relays only’ scenario, where the task requests are processed using relays only. The second scenario is an ‘objects only’ scenario, where the task requests are processed using the IoT objects only. The last scenario is a hybrid scenario, where the task requests are processed using both IoT objects and VMs. We have developed a mixed integer linear programming (MILP) model to maximize the number of processing tasks served by the system, and minimize the total power consumed by the IoT network. Based on the MILP model principles, we developed an energy efficient virtualized IoT P2P networks heuristic (EEVIPN). Our results show that the hybrid scenario serves up to 77% (57% on average) processing task requests, but with higher energy consumption compared to the other scenarios. The relays only scenario serve 74% (57% on average) of the processing task requests with 8% saving in power consumption compared to the hybrid scenario. In contrast, 28% (22% on average) of task requests can be handled by the objects only scenario with up to 62% power saving compared to the hybrid scenario.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | IoT; P2P; VMs; energy efficiency |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/K503836/1 EPSRC EP/H040536/1 EPSRC EP/K016873/1 EPSRC EP/R511717/1 EPSRC EP/S016570/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Apr 2019 16:04 |
Last Modified: | 13 Jun 2019 08:13 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/ACCESS.2019.2911117 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144649 |