Skip to Main content Skip to Navigation
Conference papers

Probabilistic Event Dropping for Intermittently Connected Subscribers over Pub/Sub Systems

Abstract : Internet of Things (IoT) aim to leverage data from multiple sensors, actuators and devices for improving peoples' daily life and safety. Multiple data sources must be integrated, analyzed from the corresponding application and notify interested stakeholders. To support the data exchange between data sources and stakeholders, the publish/subscribe (pub/sub) middleware is often employed. Pub/sub provides additional mechanisms such as reliable messaging, event dropping, prioritization, etc. The event dropping mechanism is often used to satisfy Quality of Service (QoS) requirements and ensure system stability. To enable event dropping, basic approaches apply finite buffers or data validity periods and more sophisticated ones are information-aware. In this paper, we introduce a pub/sub mechanism for probabilistic event dropping by considering the stakeholders' intermittent connectivity and QoS requirements. We model the pub/sub middleware as a network of queues which includes a novel ON/OFF queueing model that enables the definition of join probabilities. We validate our analytical model via simulation and compare our mechanism with existing ones. Experimental results can be used as insights for developing hybrid dropping mechanisms.
Complete list of metadata

Cited literature [28 references]  Display  Hide  Download
Contributor : Georgios Bouloukakis Connect in order to contact the contributor
Submitted on : Wednesday, March 6, 2019 - 1:30:29 AM
Last modification on : Wednesday, June 8, 2022 - 12:50:04 PM
Long-term archiving on: : Friday, June 7, 2019 - 6:12:16 PM


Files produced by the author(s)


  • HAL Id : hal-02058417, version 1



Georgios Bouloukakis, Ioannis Moscholios, Nikolaos Georgantas. Probabilistic Event Dropping for Intermittently Connected Subscribers over Pub/Sub Systems. ICC 2019 - IEEE International Conference on Communications, May 2019, Shanghai, China. ⟨hal-02058417⟩



Record views


Files downloads