Distributed intelligent illumination control in the context of probabilistic graphical models

Lighting systems based on light-emitting diodes (LEDs) possess many benefits over their incandescent counterparts including longer lifespans, lower energy costs, better quality of light and no toxic elements, all without sacrificing consumer satisfaction. Their lifespan is not affected by switching frequency allowing for better illumination control and system efficiency. In this paper, we present a fully distributed energy-saving illumination dimming control strategy for the system of a lighting network which consists of a group of LEDs and user-Associated devices. In order to solve the optimization problem, we are using a distributed approach that utilizes factor graphs and the belief propagation algorithm. Using probabilistic graphical models to represent and solve the system model provides for a natural description of the problem structure, where user devices and LED controllers exchange data via line-of-sight communication

Network function computation as a service in future 5G machine type communications

The 3GPP machine type communications (MTC) service is expected to contribute a dominant share of the IoT traffic via the upcoming fifth generation (5G) mobile cellular systems. MTC has ambition to connect billions of devices to communicate their data to MTC applications for further processing and data analysis. However, for majority of the applications, collecting all the MTC generated data is inefficient as the data is typically fed into application-dependent functions whose outputs determine the application actions. In this paper, we present a novel MTC architecture that, instead of collecting raw large-volume MTC data, offers the network function computation (NFC) as a service. For a given application demand (function to be computed), different modules (atomic nodes) of the communication infrastructure are orchestrated into a (reconfigurable) directed network topology, and each module is assigned an appropriately defined (reconfigurable) atomic function over the input data, such that the desired global network function is evaluated over the MTC data and a requested MTC-NFC service is delivered. We detail practical viability of incorporating MTC-NFC within the existing 3GPP architecture relying on emerging concepts of Network Function Virtualization and Software Defined Networking. Finally, throughout the paper, we point to the theoretical foundations that inspired the presented architecture highlighting challenges and future directions for designing 3GPP MTC-NFC service

Network function computation as a service in future 5G machine type communications

The 3GPP machine type communications (MTC) service is expected to contribute a dominant share of the IoT traffic via the upcoming fifth generation (5G) mobile cellular systems. MTC has ambition to connect billions of devices to communicate their data to MTC applications for further processing and data analysis. However, for majority of the applications, collecting all the MTC generated data is inefficient as the data is typically fed into application-dependent functions whose outputs determine the application actions. In this paper, we present a novel MTC architecture that, instead of collecting raw large-volume MTC data, offers the network function computation (NFC) as a service. For a given application demand (function to be computed), different modules (atomic nodes) of the communication infrastructure are orchestrated into a (reconfigurable) directed network topology, and each module is assigned an appropriately defined (reconfigurable) atomic function over the input data, such that the desired global network function is evaluated over the MTC data and a requested MTC-NFC service is delivered. We detail practical viability of incorporating MTC-NFC within the existing 3GPP architecture relying on emerging concepts of Network Function Virtualization and Software Defined Networking. Finally, throughout the paper, we point to the theoretical foundations that inspired the presented architecture highlighting challenges and future directions for designing 3GPP MTC-NFC service