Software-based Fault-Tolerant Internet of Things (IoT) Multi-Sensor Device using the BEAM Virtual Machine

dc.contributor.advisorBystrov, Alex
dc.contributor.authorAlghamdi, Abdulrahman
dc.date.accessioned2024-12-15T12:35:15Z
dc.date.issued2024-08-22
dc.description.abstractThe use of Internet of Things (IoT) devices in many industries, such as healthcare, agriculture, and transportation, has led to the reliability of such devices to become an essential requirement. It was argued that future business models would be dependent on IoT infrastructure. This project aimed to implement fault-tolerant IoT software using the Erlang virtual machine (BEAM) on the Raspberry Pi. The faults addressed are software faults, stuck-at-fault, and data loss faults. The objective was to build a multi-sensor IoT device that links the sensors to the cloud. It was decided to use the Elixir programming language as it had better support for external dependency and embedded systems. As for hardware, two sensors connected to the Raspberry Pi were used. A supervision tree was implemented using the Elixir language in Raspberry Pi, and experiments were then conducted to test the implementation. The implementation achieved a mean time to recovery (MTTR) of 2.16 milliseconds and 296 milliseconds in publish time. Moreover, it was found that increases in BEAM processes tend to be efficient in CPU usage due to a logarithmic relationship. The results proved BEAM as a substantial solution for IoT to meet digital business needs. The author is confident to recommend the BEAM as the tool for future reliable IoT devices.
dc.format.extent34
dc.identifier.citationIEEE
dc.identifier.urihttps://hdl.handle.net/20.500.14154/74195
dc.language.isoen
dc.publisherNewcastle University
dc.subjectFault detection
dc.subjectFault tolerant systems
dc.subjectInternet of Things
dc.titleSoftware-based Fault-Tolerant Internet of Things (IoT) Multi-Sensor Device using the BEAM Virtual Machine
dc.typeThesis
sdl.degree.departmentSchool of Engineering
sdl.degree.disciplineEmbedded Systems and Internet of Things
sdl.degree.grantorNewcastle University
sdl.degree.nameMaster of Science

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