MDP-Based Reliability Analysis of an Ambient Assisted Living System

The proliferation of ageing population creates heavy burdens to all industrialised societies. Smart systems equipped with ambient intelligence technologies, also known as Ambient Assisted Living AAL Systems are in great needs to improve the elders' independent living and alleviate the pressure on caregivers/family members. In practice, these systems are expected to meet a certain reliability requirement in order to guarantee the usefulness. However, this is challenging due to the facts that AAL systems come with complex behaviours, dynamic environments and unreliable communications. In this work, we report our experience on analysing reliability of a smart healthcare system named AMUPADH for elderly people with dementia, which is deployed in a Singapore-based nursing home. Using Markov Decision Process MDP as the reliability model, we perform reliability analysis in three aspects. Firstly, we judge the AAL system design by calculating the overall system reliability based on the reliability value of each component. Secondly, to achieve the required system reliability, we perform the reliability distribution to calculate the reliability requirement for each component. Lastly, sensitivity analysis is applied to find which component affects the system reliability most significantly. Our evaluation shows that the overall reliability of reminders to be sent correctly in AMUPADH system is below 40%, and improving the reliability of Wi-Fi network would be more effective to improve the overall reliability than other components.

[1]  Christel Baier,et al.  Principles of model checking , 2008 .

[2]  Jit Biswas,et al.  A Semantic Plug&Play Based Framework for Ambient Assisted Living , 2012, ICOST.

[3]  Eila Niemelä,et al.  Survey of reliability and availability prediction methods from the viewpoint of software architecture , 2007, Software & Systems Modeling.

[4]  Mark Donnelly,et al.  Impact Analysis of Solutions for Chronic Disease Prevention and Management , 2012, Lecture Notes in Computer Science.

[5]  Swapna S. Gokhale,et al.  Architecture-Based Software Reliability Analysis: Overview and Limitations , 2007, IEEE Transactions on Dependable and Secure Computing.

[6]  Katerina Goseva-Popstojanova,et al.  Architecture-based approach to reliability assessment of software systems , 2001, Perform. Evaluation.

[7]  Christel Baier,et al.  Principles of Model Checking (Representation and Mind Series) , 2008 .

[8]  Jin Song Dong,et al.  ACARP: Auto Correct Activity Recognition Rules Using Process Analysis Toolkit (PAT) , 2012, ICOST.

[9]  Mignon Park,et al.  Aging Friendly Technology for Health and Independence, 8th International Conference on Smart Homes and Health Telematics, ICOST 2010, Seoul, Korea, June 22-24, 2010. Proceedings , 2010, ICOST.

[10]  Lin Gui,et al.  Combining model checking and testing with an application to reliability prediction and distribution , 2013, ISSTA.

[11]  Aditya P. Mathur,et al.  Comparison of architecture-based software reliability models , 2001, Proceedings 12th International Symposium on Software Reliability Engineering.

[12]  Kateriana Goýeva-Popstojanova,et al.  Many architecture-based software reliability modelsComparison of Architecture-Based Software Reliability Models , 2001 .

[13]  Arkady B. Zaslavsky,et al.  On Uncertainty in Context-Aware Computing: Appealing to High-Level and Same-Level Context for Low-Level Context Verification , 2004, IWUC.

[14]  Dai Pan,et al.  Architecture-based software reliability modeling , 2006, J. Syst. Softw..

[15]  Marta Z. Kwiatkowska,et al.  PRISM 4.0: Verification of Probabilistic Real-Time Systems , 2011, CAV.

[16]  Roy H. Campbell,et al.  Reasoning about Uncertain Contexts in Pervasive Computing Environments , 2004, IEEE Pervasive Comput..

[17]  Jin Song Dong,et al.  Mild Dementia Care at Home - Integrating Activity Monitoring, User Interface Plasticity and Scenario Verification , 2010, ICOST.

[18]  Roger C. Cheung,et al.  A User-Oriented Software Reliability Model , 1978, IEEE Transactions on Software Engineering.

[19]  Swapna S. Gokhale,et al.  Reliability prediction and sensitivity analysis based on software architecture , 2002, 13th International Symposium on Software Reliability Engineering, 2002. Proceedings..

[20]  Swapna S. Gokhale,et al.  An analytical approach to architecture-based software performance and reliability prediction , 2004, Perform. Evaluation.

[21]  Arthur I. Karshmer,et al.  Living assistance systems: an ambient intelligence approach , 2006, ICSE.

[22]  James H. Aylor,et al.  Computer for the 21st Century , 1999, Computer.

[23]  Jun Sun,et al.  Formal Analysis of Pervasive Computing Systems , 2012, 2012 IEEE 17th International Conference on Engineering of Complex Computer Systems.