Location-Aware, Context-Driven QoS for IoT Applications
dc.contributor.author | Ahmad, Enas M. | |
dc.contributor.author | Alaslani, Maha S. | |
dc.contributor.author | Dogar, Fahad R. | |
dc.contributor.author | Shihada, Basem | |
dc.date.accessioned | 2019-07-04T12:16:35Z | |
dc.date.available | 2019-07-04T12:16:35Z | |
dc.date.issued | 2019-02-12 | |
dc.identifier.citation | Ahmad, E., Alaslani, M., Dogar, F. R., & Shihada, B. (2020). Location-Aware, Context-Driven QoS for IoT Applications. IEEE Systems Journal, 14(1), 232–243. doi:10.1109/jsyst.2019.2893913 | |
dc.identifier.doi | 10.1109/JSYST.2019.2893913 | |
dc.identifier.uri | http://hdl.handle.net/10754/655920 | |
dc.description.abstract | In this paper, we identify the unique quality of service (QoS) needs of emerging IoT applications and propose SDN-based Application-aware Dynamic Internet of things Quality of service (SADIQ), a software-defined network (SDN) framework that addresses these needs. SADIQ provides location-aware, context-driven QoS for IoT applications by allowing applications to express their requirements using a location-based abstraction and a high-level SQL-like policy language, and the network to support these requirements through recent advances in SDNs. We implement SADIQ using commodity OpenFlow-enabled switches and an open-source SDN controller and evaluate its effectiveness using traces from two real IoT applications. Our results show that SADIQ improves the percentage of regions with error in their reported temperature for the Weather Signal application up to 45x, and improves the percentage of incorrect parking statuses for regions with high occupancy for the Smart Parking application up to 30x, under the same network conditions and drop rates. | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | |
dc.relation.url | https://ieeexplore.ieee.org/document/8640087/ | |
dc.relation.url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8640087 | |
dc.rights | (c) 2019 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. | |
dc.subject | Abstraction | |
dc.subject | Internet of Things (IoT) | |
dc.subject | openflow | |
dc.subject | policies | |
dc.subject | quality of service (QoS) | |
dc.subject | software-defined network (SDN) | |
dc.title | Location-Aware, Context-Driven QoS for IoT Applications | |
dc.type | Article | |
dc.contributor.department | Computer Science | |
dc.contributor.department | Computer Science Program | |
dc.contributor.department | Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division | |
dc.identifier.journal | IEEE Systems Journal | |
dc.eprint.version | Post-print | |
dc.contributor.institution | Department of Computer Science, Tufts University, Medford, MA 02155 USA | |
kaust.person | Ahmad, Enas M. | |
kaust.person | Alaslani, Maha S. | |
kaust.person | Shihada, Basem | |
dc.date.published-online | 2019-02-12 | |
dc.date.published-print | 2020-03 |
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