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dc.contributor.authorWang, Qian
dc.contributor.authorLee, Brian
dc.contributor.authorMurray, Niall
dc.contributor.authorQiao, Yuansong
dc.identifier.citationWang, Q., Lee, B., Murray, N., Qiao, Y. (2023). IEEE Internet of Things Journal (Early Access). 11 May 2023. doi: 10.1109/JIOT.2023.3275179en_US
dc.description.abstract—Exactly-once data processing/delivery can be guaranteed in traditional big data processing systems, e.g. Apache Flink. Checkpoint is commonly used as the solution. Each operator in these systems can restart from the last successfully saved state whenever a failure happens. It is not necessary to restore the logical job graph onto the same device(s) in traditional datacentre scenarios with powerful servers close to each other. However, the datacentre oriented solutions are not suitable for IoT collaborative edge computing scenarios. The logical job graph is tightly coupled to the physical topology in IoT networks. Data processing task(s) cannot be placed at a random edge device to recover from a network failure as it needs to evaluate the benefits of transmitting data versus processing/aggregating the data. To address the above challenges, this paper proposes an Information Centric Networking based solution and correspondent protocols to provide Exactly-oncecomputation for the Collaborative Edge in IoT (ECE). It contains a job execution scheme to deliver IoT jobs with exactly once data computation guarantee and a recovery procedure to dynamically change the IoT job execution graph while experiencing link failures. The protocol also provides a checking procedure on data state (received/un-received and computed/un-computed) to prevent any data loss or duplicated data processing due to the updated job graph. A data identification approach based on the job graph is devised to support the ECE functionality. A testbed has been developed on ndnSIM and the simulation results have verified the feasibility and scalability of ECE design. It also evaluates the overhead incurred by the ECE protocol to guarantee exactly once data computation.en_US
dc.relation.ispartofIEEE Internet of Things Journalen_US
dc.rightsAttribution 3.0 United States*
dc.subjectCollaborative edge computingen_US
dc.subjectInternet of Things (IoT)en_US
dc.subjectInformation Centric Networking (ICN)en_US
dc.titleECE: Exactly-Once-Computation for Collaborative Edge in IoT using Information Centric Networkingen_US
dc.contributor.affiliationTechnological University of the Shannon: Midlands Midwesten_US
dc.contributor.sponsorTechnological University of the Shannon under the Staff Development Programme, and Science Foundation Ireland (SFI) under Grant Number SFI 16/RC/3918, co-funded by the European Regional Development Fund. Ren_US
dc.subject.departmentSoftware Research Institute TUS:MMen_US

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Attribution 3.0 United States
Except where otherwise noted, this item's license is described as Attribution 3.0 United States