NDLI: A behavioral reflective architecture for managing the integration of personal ubicomp systems: automatic SNMP-based discovery and management of behavior context in smart-spaces

Content Provider	Springer Nature Link
Author	Moreira, Rui S. Morla, Ricardo S. Moreira, Luís P. C. Soares, Christophe
Copyright Year	2016
Abstract	Context-aware ubiquitous computing systems should be able to introspect the surrounding environment and adapt their behavior according to other existing systems and context changes. Although numerous ubiquitous computing systems have been developed that are aware of different types of context such as location, social situation, and available computational resources, few are aware of their computational behavior. Computational behavior introspection is common in reflective systems and can be used to improve the awareness and autonomy of ubicomp systems. In this paper, we propose a decentralized approach based on Simple Network Management Protocol (SNMP) and Universal Plug and Play (UPnP), and on state transition models to model and expose computational behavior. Typically, SNMP and UPnP are targeted to retrieve raw operational variables from managed network devices and consumer electronic devices, e.g., checking network interface bandwidth and automating device discovery and plug and play operations. We extend the use of these protocols by exposing the state of different ubicomp systems and associated state transitions statistics. This computational behavior may be collected locally or remotely from ubicomp systems that share a physical environment, and sent to a coordinator node or simply shared among ubicomp systems. We describe the implementation of this behavior awareness approach in a home health-care environment equipped with a VoIP Phone and a drug dispenser. We provide the means for exposing and using the behavior context in managing a simple home health-care setting. Our approach relies on a system state specification being provided by manufacturers. In the case where the specification is not provided, we show how it can be automatically discovered. We propose two machine learning approaches for automatic behavior discovery and evaluate them by determining the expected state graphs of our two systems (a VoIP Phone and a drug dispenser). These two approaches are also evaluated regarding the effectiveness of generated behavior graphs.
Starting Page	229
Ending Page	243
Page Count	15
File Format	PDF
ISSN	16174909
Journal	Personal Technologies
Volume Number	20
Issue Number	2
e-ISSN	16174917
Language	English
Publisher	Springer London
Publisher Date	2016-02-03
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	SNMP- and UPnP-based behavioral reflection Automatic state and behavior graph discovery Autonomous management of ubicomp systems User Interfaces and Human Computer Interaction Computer Science Personal Computing
Content Type	Text
Resource Type	Article
Subject	Management Science and Operations Research Library and Information Sciences Computer Science Applications Hardware and Architecture

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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