engleski

Energy efficient task allocation for service provisioning in Machine-to-Machine systems

Machine-to-Machine (M2M) communication systems enable autonomous communication between heterogeneous devices. In many applications those devices are used to obtain measurements from sensors connected to them. By integrating M2M with the Internet of things (IoT) paradigm, sensors and the data they obtain can be easily accessed via Internet infrastructure. This novelty, along with the advancement of processing power on small devices and the possibility to connect more sensors to one sensing device, poses new challenges and opens new opportunities in the area. This paper presents an algorithm and a protocol devised for task allocation to nodes of the M2M architecture where M2M devices are battery powered. The presented mechanism tackles some of the identified challenges within the area. First challenge is to determine the right node for performing data analysis. Certain data analysis tasks can be performed on device, instead of only on servers, which is a traditional approach. Another challenge is to relate the process of obtaining measurements with user needs, i.e. to collect data only when users have interest in it. The last identified challenge is to extend lifetime of services with higher priority, instead of prolonging lifetime of all devices within the network. Adoption of the proposed mechanism is justified on specific services in a smart home environment.

Machine-to-Machine systems, task allocation, energy efficiency

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