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2017
DOI: 10.1109/mcom.2017.1600614
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Self-Organized Connected Objects: Rethinking QoS Provisioning for IoT Services

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Cited by 21 publications
(12 citation statements)
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“…Traffic load and the computational delay has been considered as QoS metrics for analysis. Elhammouti et al [169] form a game theory problem named satisfaction equilibrium with an objective function to optimize energy instead of maximizing QoS. The authors have highlighted key motivation for optimizing energy subject to achieve satisfactory QoS constraint.…”
Section: B Quality Of Service (Qos) Aware Architecturementioning
confidence: 99%
“…Traffic load and the computational delay has been considered as QoS metrics for analysis. Elhammouti et al [169] form a game theory problem named satisfaction equilibrium with an objective function to optimize energy instead of maximizing QoS. The authors have highlighted key motivation for optimizing energy subject to achieve satisfactory QoS constraint.…”
Section: B Quality Of Service (Qos) Aware Architecturementioning
confidence: 99%
“…In the second stage, h i fetches the remained (1 − x if )L f bits from S k , and then delivers these (1 − x if )L f bits to the CR i. In general, highest QoE levels may cause a significant amount of energy consumption in IoT scenarios [23]. Hence, it is more meaningful to jointly achieve the satisfactory QoE performance and energy saving.…”
Section: Content Deliverymentioning
confidence: 99%
“…automation, sensing, machine-to-machine communication, etc. ), promises to improve and to optimize our daily life and forms the infrastructure that allows intelligent sensors and smart objects to communicate and work together [11].…”
Section: Introductionmentioning
confidence: 99%