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dc.contributor.advisorOtto, Anshus
dc.contributor.authorZhakun, Ilia
dc.date.accessioned2021-12-15T06:32:25Z
dc.date.available2021-12-15T06:32:25Z
dc.date.issued2021-11-15en
dc.description.abstractThe arctic tundra is observed to collect data to be used for climate research. Data can be collected by cyber-physical computers with sensors. However, the arctic tundra has a limited availability of energy. Consequently, the nodes rely on batteries and sleep most of the time to increase the battery-limited operational lifetime. In addition, only a few nodes can expect to be in reach of a back-haul wireless data network. Consequently, the nodes have on-node wireless local area networks to reach nearby neighbor nodes. To increase the availability for remote clients to the data collected by the nodes, a set of shadow nodes are used. These are always on, and always have access to a back-haul network. Data from an edge node on the arctic tundra propagates to the shadow nodes either directly over a back-haul network, or via a neighbor node with a back-haul network. The purpose is to make the data produced by an edge node available to a client even when the edge node sleeps or no network access is available. A statistical analysis is done to characterize the prototype’s behavior under a set of edge-node behaviors. To validate the statistical analysis a prototype system is developed and used in a set of performance-measuring experiments. Experiments are done with 10 to 1,000,000 nodes, different probabilities of nodes being awake, and different probabilities of the back-haul network being available. Edge and shadow nodes are emulated as Go functions and executed on a high-performance computer with thousands of cores. Different wireless networks are emulated albeit in a simplified way. A run-time simulation system is developed to control the prototype and conduct the experiments. The results for the prototype show that if the single synchronization chance is low or the desired time to get the latest data should be minimized, an additional data delivery path should be considered on the edge node’s side. Synchronization via the right neighbor principle adds an extra communication channel which increases the data availability level by 50%-100%, but the resource demand grows by 30% per unit. The time required to get the latest data from edge nodes decreases by a factor of 1.75. The results for the simulation show that the cumulative network throughput of approximately ≈ 2100 MB/s and the Generated Data Amount ≈ 25000 MB/s can be achieved at the cost of ≈ 80 KB RAM per emulated node. The results show that the statistical analysis and the results from the prototype as used by the simulation system match, but the statistical expectation considers a limited range of factors. Statistically derived values can be used as the input for the simulation, where they would be adjusted to get a more comprehensive result. The conclusions are that the Mask provides instant access to data storage for edge nodes. The Mask is fronted to clients which become able to retrieve the data asynchronously, even when edge nodes are offline.en_US
dc.identifier.urihttps://hdl.handle.net/10037/23407
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universitetno
dc.publisherUiT The Arctic University of Norwayen
dc.rights.holderCopyright 2021 The Author(s)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0en_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)en_US
dc.subject.courseIDINF-3990
dc.subjectVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550::Datateknologi: 551en_US
dc.subjectVDP::Technology: 500::Information and communication technology: 550::Computer technology: 551en_US
dc.titleThe Mask: Masking the effects of Edge Nodes being unavailableen_US
dc.typeMastergradsoppgavenor
dc.typeMaster thesiseng


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Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)