TY - JOUR
T1 - Location-Aware, Context-Driven QoS for IoT Applications
AU - Ahmad, Enas M.
AU - Alaslani, Maha S.
AU - Dogar, Fahad R.
AU - Shihada, Basem
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/655920
UR - https://ieeexplore.ieee.org/document/8640087/
UR - http://www.scopus.com/inward/record.url?scp=85081666677&partnerID=8YFLogxK
U2 - 10.1109/JSYST.2019.2893913
DO - 10.1109/JSYST.2019.2893913
M3 - Article
SN - 1932-8184
VL - 14
SP - 1
EP - 12
JO - IEEE Systems Journal
JF - IEEE Systems Journal
IS - 1
ER -