Paper Info
Title
A Cooperative Learning Framework for Mobility-Aware Resource Management in Multi-Inhabitant Smart Homes
Abstract
The essence of pervasive (ubiquitous) computing lies in the creation of smart environments saturated with computing and communication capabilities, yet gracefully integrated with human users. 驴Context Awareness驴 is perhaps the most important feature of such an intelligent computing paradigm. The mobility and activity of the inhabitants play significant roles in forming the context at any instance of time. In order to extract the best performance and efficacy of smart computing environments, one needs a technology-independent, context-aware platform spanning over multiple inhabitants. In this paper, we have developed a framework for mobility-aware resource (in particular, energy consumption) management in a multi-inhabitant smart home, based on a dynamic, cooperative reinforcement learning technique. The inhabitants驴 mobility creates uncertainty of his location and activity. Using the proposed cooperative game-theory based framework, all the inhabitants currently present in the house attempt to minimize this overall uncertainty in the form of utility functions associated with them. Joint optimization of the utility function corresponds to the convergence to Nash equilibrium and helps in accurate prediction of inhabitants驴 future locations and activities. This results in adaptive control of automated devices and temperature of the house, thus providing an amicable environment and sufficient comfort to the inhabitants. Simulation results point out that our framework can adaptively control the smart environment, while reducing the energy consumption and enhancing the comfort.
Year
DOI
Venue
2005
10.1109/MOBIQUITOUS.2005.1
MobiQuitous
Keywords
Field
DocType
smart environment,house attempt,intelligent computing paradigm,energy consumption,mobility-aware resource management,multi-inhabitant smart homes,adaptive control,smart computing environment,multi-inhabitant smart home,amicable environment,cooperative learning framework,cooperative reinforcement,overall uncertainty,convergence,pervasive computing,game theory,energy management,cooperative learning,ubiquitous computing,groupware,smart home,nash equilibrium,learning artificial intelligence,resource management,reinforcement learning,uncertainty
Resource management,Energy management,Smart environment,Computer security,Computer science,Context awareness,Human–computer interaction,Ubiquitous computing,Cooperative learning,Energy consumption,Reinforcement learning,Distributed computing
Conference
ISBN
Citations 
PageRank 
0-7695-2375-7
8
1.15
References 
Authors
8
4
Name
Order
Citations
PageRank
Nirmalya Roy140542.11
Abhishek Roy2969.45
Sajal K. Das38086745.54
Kalyan Basu466268.91