A Distributed Approach towards Improved Dissemination Protocol for Smooth Handover in MediaSense IoT Platform

Distributed joint congestion control and routing optimization has received a significant amount of attention recently. To date, however, most of the existing schemes follow a key idea called the back-pressure algorithm. Despite having many salient features, the first-order sub gradient nature of the back-pressure based schemes results in slow convergence and poor delay performance. To overcome these limitations, the present study was made as first attempt at developing a second-order joint congestion control and routing optimization framework that offers utility-optimality, queue-stability, fast convergence, and low delay. Contributions in this project are three-fold. The present study propose a new second-order joint congestion control and routing framework based on a primal-dual interior-point approach and established utility-optimality and queue-stability of the proposed second-order method. The results of present study showed that how to implement the proposed second-order method in a distributed fashion.

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Computer supported collaborative learning in schools: a distributed approach

British Journal of Educational Technology ◽

10.1111/j.1467-8535.1995.tb00130.x ◽

1995 ◽

Vol 26 (2) ◽

pp. 131-140 ◽

Cited By ~ 7

Author(s):

Helen Tomlinson ◽

William Henderson

Keyword(s):

Collaborative Learning ◽

Computer Supported Collaborative Learning ◽

Distributed Approach

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Boltzmann Distributed Replicator Dynamics: Population Games in a Microgrid Context

Games ◽

10.3390/g12010008 ◽

2021 ◽

Vol 12 (1) ◽

pp. 8

Author(s):

Gustavo Chica-Pedraza ◽

Eduardo Mojica-Nava ◽

Ernesto Cadena-Muñoz

Keyword(s):

Control Method ◽

Optimization Problems ◽

Replicator Dynamics ◽

Boltzmann Distribution ◽

Full Information ◽

Multi Agent Systems ◽

Q Learning ◽

Population Games ◽

Distributed Approach ◽

Multi Agent

Multi-Agent Systems (MAS) have been used to solve several optimization problems in control systems. MAS allow understanding the interactions between agents and the complexity of the system, thus generating functional models that are closer to reality. However, these approaches assume that information between agents is always available, which means the employment of a full-information model. Some tendencies have been growing in importance to tackle scenarios where information constraints are relevant issues. In this sense, game theory approaches appear as a useful technique that use a strategy concept to analyze the interactions of the agents and achieve the maximization of agent outcomes. In this paper, we propose a distributed control method of learning that allows analyzing the effect of the exploration concept in MAS. The dynamics obtained use Q-learning from reinforcement learning as a way to include the concept of exploration into the classic exploration-less Replicator Dynamics equation. Then, the Boltzmann distribution is used to introduce the Boltzmann-Based Distributed Replicator Dynamics as a tool for controlling agents behaviors. This distributed approach can be used in several engineering applications, where communications constraints between agents are considered. The behavior of the proposed method is analyzed using a smart grid application for validation purposes. Results show that despite the lack of full information of the system, by controlling some parameters of the method, it has similar behavior to the traditional centralized approaches.

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A Wireless and Distributed Approach to Humiture Control Using an Adaptive Controller Model

Scientific African ◽

10.1016/j.sciaf.2021.e00922 ◽

2021 ◽

pp. e00922

Author(s):

ONIBONOJE Moses Oluwafemi

Keyword(s):

Adaptive Controller ◽

Distributed Approach

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Low-code from frontend to backend: Connecting conversational user interfaces to backend services via a low-code IoT platform

CUI 2021 - 3rd Conference on Conversational User Interfaces ◽

10.1145/3469595.3469632 ◽

2021 ◽

Author(s):

Irene Weber

Keyword(s):

User Interfaces ◽

Iot Platform

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IoT Platform for Energy Sustainability in University Campuses

Sensors ◽

10.3390/s21020357 ◽

2021 ◽

Vol 21 (2) ◽

pp. 357

Author(s):

Pedro Moura ◽

José Ignacio Moreno ◽

Gregorio López López ◽

Manuel Alvarez-Campana

Keyword(s):

Energy Demand ◽

New Technologies ◽

Low Cost ◽

Sustainable Use ◽

High Energy ◽

Appropriate Technology ◽

Monitoring And Control ◽

Energy Sustainability ◽

University Campuses ◽

Iot Platform

University campuses are normally constituted of large buildings responsible for high energy demand, and are also important as demonstration sites for new technologies and systems. This paper presents the results of achieving energy sustainability in a testbed composed of a set of four buildings that constitute the Telecommunications Engineering School of the Universidad Politécnica de Madrid. In the paper, after characterizing the consumption of university buildings for a complete year, different options to achieve more sustainable use of energy are presented, considering the integration of renewable generation sources, namely photovoltaic generation, and monitoring and controlling electricity demand. To ensure the implementation of the desired monitoring and control, an internet of things (IoT) platform based on wireless sensor network (WSN) infrastructure was designed and installed. Such a platform supports a smart system to control the heating, ventilation, and air conditioning (HVAC) and lighting systems in buildings. Furthermore, the paper presents the developed IoT-based platform, as well as the implemented services. As a result, the paper illustrates how providing old existing buildings with the appropriate technology can contribute to the objective of transforming such buildings into nearly zero-energy buildings (nZEB) at a low cost.

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