ESTABLISHING A SERVICE COMPOSITION
FRAMEWORK FOR SMART HEALTHCARE SYSTEM
A thesis submitted to the Christ University for the award of the degree of
DOCTOR OF PHILOSOPHY IN
COMPUTER SCIENCE
By
V. ASHOK IMMANUEL (Register Number: 1045001)
UNDER THE SUPERVISION OF
DR. PETHURU RAJ Infrastructure Architect
IBM Global Cloud Center of Excellence
Centre for Research
Christ University, Bengaluru-560029
JULY 2016
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DECLARATION
I, V. Ashok Immanuel, hereby declare that the thesis titled ‘Establishing a Service Composition Framework for Smart Healthcare System’
submitted to Christ University, Bengaluru in partial fulfilment of the requirements for the award of the Degree of Doctor of Philosophy in Computer Science is a record of original and independent research work done by me under the supervision of Dr. Pethuru Raj, Infrastructure Architect, IBM Global Cloud Center of Excellence. I also declare that this thesis or any part of it has not been submitted to any other University/Institute for the award of any degree.
Place: Bengaluru Date:
V. Ashok Immanuel
CERTIFICATE
This is to certify that the thesis titled “Establishing a Service Composition Framework for Smart Healthcare System” submitted by Mr. V. Ashok Immanuel to Christ University, Bengaluru in partial fulfilment of the requirements for the award of the Degree of Doctor of Philosophy in Computer Science is a record of original research work carried out by him under my supervision. The content of this thesis, in full or in parts, has not been submitted by any other candidate to any other University for the award of any degree or diploma.
Place: Bengaluru Dr. Pethuru Raj
Date: Infrastructure Architect,
IBM Global Cloud Center of Excellence
Additional Director/Associate Director
Centre for Research, Christ University, Bengaluru-560029
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ACKNOWLEDGEMENTS
I praise God the Almighty, for every good and perfect gift is from the Father of heavenly lights and He is the source of all wisdom. I thank him for blessing me with good health and leading me to the right people and place for gaining knowledge.
With a grateful heart, I would like to express my gratitude to my supervisor Dr. Pethuru Raj, Infrastructure Architect, IBM Global Cloud Center of Excellence. His passion for research was contagious and was motivating me in my doctoral pursuit. He has been mentoring me since the identification of the research problem until this very moment. My appreciations for his patience during my tough times and contributions for my successful completion.
My sincere thanks to Dr. Fr. Thomas C Mathew, Vice-chancellor, Dr. Fr.
Abraham V M, Pro Vice-chancellor, Dr. Fr. Varghese, Finance Officer and Dr. Anil Pinto, Registrar, of Christ University for providing me with an excellent opportunity, platform, infrastructure and the right ambience to undertake the research work.
I would like to express my gratitude to Dr. Tony Sam George, Additional Director, Dr. Shivappa B Gudennavar, Associate Director, Centre for Research for their support and their guidance. A special word of thanks to Dr. S. SrikantaSwamy, former Additional Director for his kindness.
I would like to thank Prof. Joy Paulose, Head, Department of Computer Science, all my colleagues, Dr. Fr. Jossy P George, Director, Christ Institute of Management, Pune, for their constant, unfailing encouragement they rendered not only during my research work but also ever since I joined the department. I would also like to record my acknowledgement to Jonathan Fidelis Paul and Diganta Das who are currently pursuing Master of Computer Application at the Department of Computer Science, Christ University, Bangalore.
I would like to thank Dr. Guruprasad H S, Professor & Head, and Prof.
Namratha M of the Department of Computer Science and Engineering, BMS College of Engineering for helping in developing and validating the Automata concepts.
I would like to express my since thanks to Staff Nurse Ms. Shiny Mathew, Nurse Intensivist Ms. Mini V.J and Ms. Soly M K of Narayana Hrudayalaya hospital, Bangalore for sharing domain knowledge.
Above all, I am much grateful to my Father, Mr. S.C. Vedasionmani and my mother, Mrs. Joy Sironmani, for raising me and providing me with the right family environment to rise in life. It is their constant fervent prayer that has aided me to stand on firm ground to this day. I also thank my sister, Annie Sylvia for encouraging me.
I thank my Father-in-law, Mr. Deena Sadhu and Mother-in-law Mrs.
Chandra Deena for their constant support and prayer.
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I thank my dearest wife, Sheela Immanuel, for being an enormous strength, lifting my spirit at troubled times and surrounding me with constant support during all these years and the many years to come. I thank my cherished children, the apple of my eyes, Keerthana Immanuel and Kimble Immanuel for bringing joy and happiness by all their actions.
I dedicate this thesis to the Glory of God.
- V. Ashok Immanuel
ABSTRACT
As the idea of location awareness has already matured and numerous applications are flooded in today’s word, the logical next step reasons out, to context-awareness. Though the idea of context-awareness has been in the research field for close to two decades, the recent advancement in Internet of Things has brought a more compelling thrust in its research. Sensor networks integrating billions of sensors and actuators will be prevalent in the near future producing big data. Filtering and analysing this data with the contextual information will yield more significant results. But deducing the context information itself poses many challenges and unresolved research problems. Context-awareness systems involve acquiring, analysing, reasoning the data and composing the services for suitable action. Service composition either by orchestrating or choreographing technique has been deployed in certain applications, however, each domain requires unique methodology. Healthcare has always been the top priority when it comes to applying novel technologies. Applying context-awareness computing in the healthcare service sector is of paramount importance.
The problem context for this research lies in a cardiology speciality hospital’s Intensive Therapy Unit or the post-surgery recovery ward which has lot of scenarios emanating that involves course of actions to be delivered by the healthcare professionals depending on the context. Depending on mere human service may not be adequate. With the available advancements in technologies, it would be possible to leverage optimum service in that
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and act accordingly. The course of actions to be taken involves an amalgamation of understanding the location, presence availability, relevance of and coordination among various departments, machines and personnel.
This can be summarized as “Response” with “Context-Awareness”. The primarily task is to sense the context and then determine and locate the relevant services, which are distributed in the World Wide Web, to achieve a goal situation as a solution to the problem. In order to deliver such a solution we need to develop an exclusive context-aware framework. The existing frameworks will not be adequate to meet such a demanding situation and hence, the research problem is to evolve a comprehensive service composition framework for smart healthcare systems.
In order to solve this problem, a use-case approach was followed. After identifying an appropriate use-case, the solution was first modelled using Automata. The concept of service automata and timed automata were fused to deliver a timed-service automaton which is appropriate to model and test the framework and algorithm for service composition.
As a solution to the research problem, a composition based framework of a context-aware smart healthcare system has been presented. It will guide software developers to deploy services for critical healthcare, under the umbrella of Service Oriented Architecture. The matured concept of Automata has been tweaked to present novel timed-service automata which will enable service composition precisely for meeting the time constrained demands of modern healthcare service requirements. It has been tested with UPPAAL verification tool for validity and concurrency. A prototype has
been implemented to study the validity of the established framework.
Apache JMeter tool was used to test the strength of the services and engine developed based on the proposed algorithm for effective service composition.
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CONTENTS
DECLARATION ... ii
CERTIFICATE... iii
ACKNOWLEDGEMENTS... iv
ABSTRACT ... vii
CONTENTS ...x
LIST OF TABLES... xiii
LIST OF FIGURES ... xiv
CHAPTER 1 - INTRODUCTION ...2
1.1. Location Awareness and Context awareness ...2
1.2. Internet Of Things ...7
1.3. Healthcare Domain ...9
1.4. Context-awareness in Healthcare ...12
1.5. Service Composition and Context-awareness ...13
1.6. Web Service and Service composition...14
1.7. A use case scenario from a post-heart-surgery ward...17
1.8. Research questions summary ...19
1.9. Organization of the thesis...19
CHAPTER 2 - LITERATURE REVIEW ...22
2.1. Introduction ...22
2.2. Context Awareness...23
2.2.1 Context...23
2.2.2 Context-Awareness...25
2.2.3 Context Aware Computing...27
2.3 Context-aware applications ...28
2.3.1 General context-aware applications ...30
2.3.2. Healthcare related applications ...30
2.4 Service Oriented Architecture and Service Composition...33
2.4.1 Service automata ...35
2.4.2 Timed Automata...36
2.4.3 Service Composition ...38
2.5 Medical Device Integration ...39
2.6 Context-Aware Framework ...40
2.7 Research Gap...43
2.8 Objectives ...44
2.9 Research Workflow ...45
CHAPTER 3 - SERVICE, TIMED & TIMED-SERVICE AUTOMATA ...47
3.1 Introduction ...47
3.2. Research Work Carried out ...48
3.2.1 Automata for chk_weight service...49
3.2.2 Automata for alert_on service ...50
3.3 Timed-Service automata...51
3.4 Composite Timed-Service automata ...55
CHAPTER 4–CONTEXT-AWARE FRAMEWORK AND IMPLEMENTATION ...63
4.1 Introduction ...63
4.2 Context framework ...64
4.3 Implementation...66
4.3.1Service Oriented Architecture (SOA) ...68
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4.3.2 Web Services (WS) ...68
4.3.3 PHP and NUSOAP ...69
4.3.4 UDDI ...71
4.4 Smart Ward System Implementation ...74
4.5 Algorithm for service composition to achieve target situation ...80
4.6 Context Space, Attributes and Situations...81
CHAPTER 5 - RESULTS VALIDATION AND DISCUSSION ...84
5.1 Introduction ...84
5.2 Discussions on JMeter Results ...84
CHAPTER 6 - SUMMARY AND CONCLUSIONS ...105
6.1 Summary...105
6.2 Key Contributions ...106
6.3 Conclusion ...106
6.3 Future Work...107
BIBLIOGRAPHY...109
PUBLICATIONS AND PROCEEDINGS………..121
LIST OF TABLES
Table 1.1 Schmidt’s sensor technologies...8
Table 1.2 Features of RESTful approaches...16
Table 2. 1 Context-awareness models ...26
Table 2.2 Comparison of three major healthcare frameworks ...40
Table 3.1 State Transition table for ‘chk_weight’ automata...49
Table 3.2 State Transition table for alert_on automata ...51
Table 3.3 State transition table for Timed-Service Automata...54
Table 3.4 A comparison of Automata(A), Service Automata(SA) and Timed Automata(TA)...60
Table 4.1 List of web services required for a smart ITU ward ...70
Table 4.2 Context Attributes ...76
Table 4.3 Sample Data sheet ...78
Table 4.4 Johns Hopkins Cardiac Surgery and post-surgery team ...79
Table 5.1 Aggregate report tabulated by JMeter ...90
Table 5.2 Summary report produced by JMeter...91
Table 5.3 Response Time, Latency and Transaction Data ...95
Table 5.4 Server Hits per second over time ...96
Table 5.5 Response Time over Time...100
Table 5.6 Time and Space data...102
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LIST OF FIGURES
Figure 1.1 Evolution of Ubiquitous Computing...4
Figure 1.2 Context lifecycle ...6
Figure 1.3 Layers in context deduction ...7
Figure 1.4 Projected growth of connected devices...9
Figure 1.5 Healthcare sector growth...10
Figure 1.6 Growth rate of Medical Device Market ...11
Figure 1.7 Architectural Style ...15
Figure 2.1 A Timed Automaton ...37
Figure 2.2 Components for Context determination...42
Figure 3.1 Service automata for chk_weight service ...49
Figure 3.2 Service automata for alert_on service...50
Figure 3.3 Automata for the composed service...51
Figure 3.4 A Timed-Service automata representation...54
Figure 3.5 UPPAAL tool verifying the automata for concurrency ...58
Figure 4.1 Framework Architecture for SHW...66
Figure 4.2 Smart ward with six beds simulation ...67
Figure 4.3 UDDI Registration ...71
Figure 4.4 PHP code for Drain service implementation ...75
Figure 4.5 PHP code for server implementation ...76
Figure 4.6 Extracts from the WSDL file ...76
Figure 5.1 Bedside display ...85
Figure 5.2 Sequence Diagram for Context Aware Smart ward system ...87
Figure 5.3 JMeter Testing Screen...88
Figure 5.4 Throughput plot *JMeter ...89
Figure 5.5 Evaluation of ITU engine *JMeter...91
Figure 5.6 Graph for Minimum, Average and Maximum time...92
Figure 5.7 Chart Graph Visualizer *JMeter ...92
Figure 5.8 Chart for Spline Visualizer *JMeter ...93
Figure 5.9 Chart depicting the Latency ...94
Figure 5.10 Chart illustrating the evaluation of ITU engine *JMeter...97
Figure 5.11 Response Time Graph *JMeter...98
Figure 5.12 Transaction per second *JMeter ...99
Figure 5.13 Composite graph of overall response time *JMeter ...101
Figure 5.14 Active Threads over time *JMeter...102
Figure 5.15 Average and Maximum data received in Kilo Bytes ...103
Chapter 1
Introduction
CHAPTER 1 INTRODUCTION
Mankind’s constant aspiration is to expand his intelligence by empowering the systems and services, with which he interacts often, to a degree of expecting similar portrayal of intelligence. He has constantly built pragmatic and distinctly powerful systems. The birth of semantic web is an undisputed example of the notion presented above. A semantic web is an attempt to enable a machine understands itself. This would be possible as more smartness is bestowed to enable cognitive adaptation for their actions and reactions. Systems and services are to become smarter by becoming aware of the surroundings and situations. Context-awareness seems to be an answer in attempting to create a smarter world. Also it is a study under the umbrella of Artificial Intelligence. The problem of determining the context possesses all the characteristics of an artificial intelligence problem. In this pursuit of expecting a delectable and desirable behaviour, the most challenging activity is to sense and understand the context that is unfolding, model it and present it to the system dynamically. Therefore researchers are expounding means of viable mechanisms to streamline the task of situation-awareness.
1.1. LOCATION-AWARENESS AND CONTEXT-AWARENESS
The idea of location awareness or presence technology has paved the way for the building of numerous applications which has rather simplified the tasks of human beings. The idea of actively or passively locating a device or an instrument has added immense power in efficiently cataloguing and
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and the concept of location awareness together have opened doors for two classes of applications. The first set of applications helps in identifying the location of a particular entity and controlling the objects remotely while the other set of applications determine the objects and entity which are surrounding the user giving knowledge about the neighbourhood.
In the last decade, much research focus was on providing information on the surroundings of a user by using location awareness. One of the practical applications such as Maps has been an enormous help for the users. The application triangulates the user’s location and builds route map to various destinations. It gives information such as restaurants, bus / railway stations, ATM machines and important landmarks within a certain radius. The information automatically updates as the user’s location changes. Services such as automatically prompting the user of nearby restaurants when the time is close to lunch hour, indicating the time it requires to travel to work or to an airport based on traffic conditions with respect to the current location of the user or an approaching storm and the actions or the route to be taken to have minimal impact will assist the human beings immensely.
Location Awareness technique has been much useful for the crime investigation agencies also. The movement of a criminal using the mobile towers to which he had been connected and location of a GPS enabled vehicle had always been much useful in solving criminal cases. Another recent prominent usage of this technology is in the retail applications. These applications sense the user location in a department store or hypermarket to advertise or suggest products to the consumers Gabay (2015).
However, a mere aware of the location of the user without knowing the context in which the user is prevailing can result in the annoying instruction of the application in the user’s action. For instance, if a service interrupts a user during an important discussion or client meeting to present a list of the restaurants around his location because it is lunch hour there is could be embarrassing or annoying the user. Or if the user is in the midst of a presentation with the client and the phone rings because the user has forgotten to switch the phone to silent mode, might become an undesired situation for the user. Instead, knowing the location of the user and understanding the context of the user, if the phone automatically replies the caller with a voice or text message explaining the situation or, at least, switch the phone to silent mode would be portraying more intelligence.
Thus, applications involving context awareness and context-aware computing will yield much better solutions for the future. Figure 1.1 illustrates the evolution of Ubiquitous computing since the Distributed computing paradigm Linnhoff-Popien and Strang (2004).
Figure 1.1 Evolution of Ubiquitous Computing
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“Context refers to a situation in the physical or the virtual world that may be utilized by an application for the purpose of dynamic adaptation, for example, to acquiring resources and services needed in a given location”
Devdatta, et al. (2010). They suggest that such applications involve multiple entities including users, sensors and other devices based on Computer- Supported Cooperative Work (CSCW) which requires (a). Dynamic integration of application components. (b). Ambient resources. (c).
Infrastructure services. Consolvo, et al. (2004) first proposed a working model for assisted living among aged. The system was designed to understand the context changes from its users and respond to changing scenarios.
Past researches has resulted in custom building context-aware applications which are very specific in nature and fails to deliver a generic framework.
Some of them include context-sensitive city tour guide by Davies et al.
(2001), context-aware communication facilities by Henricksen and Indulska (2004) and interactive context-aware museums by Fleck et al. (2002). These applications involve designs which are highly specific in nature. Following this strategy leads to higher development and programming cost. Also it would be very difficult to introduce design changes or upgrade with technological advancements.
Most of the research works are based on the following definition of context and context-awareness by Dey (2001). Abowd et al. (1999) proposed two definitions of context which are widely accepted.
“Context is any information that can be used to characterise the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves.”
“A system is context-aware if it uses context to provide relevant information and/or services to the user, where relevancy depends on the user’s task.”
Figure 1.2 Context lifecycle
Context form a real world is determined by following four major steps as illustrated in Figure 1.2. Following the above definitions, it can be generalized that any context awareness framework defined should provide a methodology for data acquisition, data representation, context delivery and reaction to the determined situation. The core features of context awareness are pervasive and ubiquitous systems which have been researched since early 1990. Computing applications have evolved over the years from desktop to web than to mobile and now pervasive ubiquitous computing.
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With the recent advancement in the Inter of Things (IoT), context-aware computing has regained its momentum in the research space. Figure 1.3 shows steps in understanding a context and presenting a raw data which is acquired from a sensor or sensor network is transformed and passed on to a context-aware system by a path of reasoning and adapting to a situation Perera, et al. (2013).
Figure 1.3 Layers in context deduction
1.2. INTERNET OF THINGS
The modern world life is surrounded by ubiquitous sensors enabled by Wireless Sensor Network (WSN) technologies. It provides the capabilities to easily measure and deduce the indicators of the environment. Internet of Things (IoT) is the result of the proliferation of devices enabled with seamlessly blending sensors and actuators in the communicating environment network around us. The information emanating from the network is shared across platforms to develop a Common Operating Picture
(COP) Gubbi, et al. (2013).Some of the prevalent and widely used sensors which are utilized in determining context information according to Schmidt are tabulated in Table 1.1 Schmidt,et al. (2014).
Table 1.1 Schmidt’s sensor technologies
Sensor What to sense
Photo-diode, colour sensor, IR and UV sensor Optical/Vision Mercury switches, angular sensors and
accelerometers Motion
GPS, active badges Location
Pulse sensor, galvanic skin response measure,
blood pressure sensor Bio-sensors
Touch sensor, thermometer, barometer Specialized sensors The projected growth of connected devices by the year 2020 is illustrated in Figure 1.4. Worldwide industries expect that about fifty billion devices would be connected by that time. These devices are going to produce a big data. To collect, analyse and interpret these data requires a lot of computation power. Moreover, it may not be required to process all the available data for the fact that all data may not be relevant for the current situation. Therefore, it is important that the data accumulated should be first understood in the context and processed to deduce the correct interpretation.
Smart connectivity and context-aware computation would be an integral part of the future. The computing paradigm will have to radically change the contemporary approach to mobile computing to connecting devices and implanting intelligence into our day-to-day activities. Needless to say,
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contextual information is imperative to filter the right volume of data for analytics and meaningful interpretation. As we migrate from static web to social web to ubiquitous web the need for intuitively sophisticated data queries will increase.
Figure 1.4 Projected growth of connected devices
1.3. HEALTHCARE DOMAIN
Healthcare is one of the largest revenue, projected at US$280 billion by 2020 in India alone, and employment generation sector in the world. Figure 1.5 illustrates the projected growth pattern in Indian Healthcare sector. In the last decade, health monitoring has received tremendous attention from the researchers. Medical engineering realm is flooded with newer technologies and patient monitoring systems. The dense heterogeneous medical devices available in the intensive therapy units pose a challenge of medical device
integration. Needless to say, a lot of research work has gone into devising techniques for integrating these systems for exchange of data.
Figure 1.5 Healthcare sector growth
However mere device integration does not exploit the modern technologies until meaningful and critical information is presented to doctors and patient care personals adapting to the changes in the patient condition. Pervasive ubiquitous computing with the internet of things has gained immense importance in the research world.
With the advent of m-health and e-health patient health record monitoring and reporting and personal health monitoring and reporting applications have been developed. Solutions for assisted living environments have also
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been well accepted not only in developed countries but their need is also being felt in developing countries. In today’s healthcare industry, exchange of data among hospitals for second opinion or for expert knowledge sharing is highly encouraged. Also it reduces the patient’s burden of carrying records along with him during all his visits. It aids in improving access for the doctors towards medical records for consultation, diagnosis and research.
Figure 1.6 Growth rate of Medical Device Market
Market researchers project market growth of Medical sensors and devices to be $9.5BN by 2022 which is illustrated in Figure 1.6. Medical devices have become key enablers in setting new standards in personal healthcare and assisted healthcare. Also, it widely promotes decentralized healthcare systems. Recent breakthrough in nano electronics and development of novel
sensors have increased our capabilities even to study emotions, deduce human behaviour from voice analysis and monitor vital signs from facial expressions Happich (2013).
1.4. CONTEXT-AWARENESS IN HEALTHCARE
Health monitoring and healthcare service quality can be improved by incorporating context information. It will result in utilizing human resources efficiently and serving the patients based on the current medical condition.
Recent researchers have produced numerous prototypes and applications for health monitoring under various challenging scenarios. The context of the patient can be derived from numerous sources namely Electronic Health Record (HER) and by monitoring the patient's current activities, changes in vital signs. With networked devices and context-aware wireless monitoring systems, it would be possible to cater to the needs of diverse patients with different medical conditions. There are numerous challenges and questions which are yet to be dealt and answered convincingly. However, a study of the research activities in this domain promises that soon a context-aware healthcare service will be optimized and efficiently real.
In order to realize this, a use case in a smarter hospital environment has been identified and timed-service automata have been used to demonstrate the manner by which its mainstream feature comes handy in enabling and fulfilling the intrinsic needs of context-awareness. The use-case approach, which eventually ends up as a reusable framework, can be tweaked in order to be highly extensible. The leverage of time-testing automata-based solution is turning out to be a strategically sound factor. The goal of this
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Architecture in acquiring, analysing and assisting doctors and nurses with the necessary information for easy and critical time-saving decision making.
This work presents an implementation of the identified web services which can be consumed during a treatment at the Intensive Therapy Unit (ITU).
Patient monitoring is a tedious and critical activity for today’s health professionals. Modern ITU’s are supported by a large number of heterogeneous devices with very few interconnected message passing systems. Patient monitoring, especially in the first few hours immediately after a surgery where the patient is recovering and is still under sedated state involves monitoring and recording a large number of readings of vitals from various monitors. Also, it demands rapid sensible action in case of emergency situations where the patient’s vital readings breach life threatening critical values. In many scenarios, it involves message passing and coordination among various medical units. There are systems which raise enough warning signals for the health professionals but presenting information, such as health records, and coordinating units, such as operation theatre, are largely resting on human efforts.
1.5. SERVICE COMPOSITION AND CONTEXT-AWARENESS
Ubiquitous computing along with Internet of Things will be the most appreciable and needed a paradigm shift for the next generation healthcare programming. Patient care would involve data aggregation from numerous heterogeneous devices, sensors and actuators which will eventually be coordinated with or without much human intervention through effective service composition. Service composition poses numerous challenges.
Services are modular software systems or applications which are loosely coupled and designed to participate in the device to device information interaction and interchange. They are Discovered, Orchestrated and coupled to form applications. With numerous heterogeneous devices in a hospital environment, it becomes imperative that device to device communication exists and it is indispensable. The healthcare domain is set for a major revolution with the research on Internet of Things (IoT) beaming to greater achievements. Hence, a thorough understanding of service composition is of paramount importance when it comes to programming for the next generation of healthcare applications that are IoT-enabled.
Service Oriented Architecture(SOA) has matured in building cross- enterprise solutions using web services. In this research work the unique capabilities of service automata in composing atomic and discrete actions into context information is combined with verification capabilities of timed automata on which the designated system trusts and forges ahead in accomplishing what is initially intended. The result is a timed-service automaton which will result in composing services while ensuring that the composition happens in a stipulated time. This attribute of timed-service automat is in particular very crucial for real-time systems and time-critical systems. Context-aware systems will be a game-changing concept for the future era of knowledge systems.
1.6. WEB SERVICE AND SERVICE COMPOSITION
In the last decade, web service composition has taken a centre stage in modern software building paradigm involving integrating business-to-
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optimized method of integrating homogeneous and heterogeneous software applications. The most attractive property of this paradigm is these services are light weight, adaptable and scalable. With the introduction of RESTful services, it has now become more visible and reliable. Roy (2000) introduced Representational State Transfer (REST), a design architecture style to interface with external web resources through Uniform Resource Identifier (URI).
Figure 1.7 Architectural Style
RESTful services rely on the stateless communication protocol. REST differs from SOAP and XML-RPC based services by having its entire API as Resource form. It can accommodate MIME-TYPE and can return text, image, XML and JSON type data. It also supports HTTP methods such as POST and GET.
Table 1.2 Features of RESTful approaches
Feature Description
Lightweight
RESTful services use HTTP protocol by which no extra encapsulation is required since the resource itself is the response to the RESTful service invocation Vinoski (2007).
Understandable
The URIs which is used to identify the services is self-descriptive and hence makes them easily understandable and accessible Richardson and Ruby, (2008)
Scalable
REST supports server-side caching and load balancing which results enables integrating services without affecting performance and availability Cristian, et al. (2016).
Declarative
Instead of describing the functions, the focus is to describe the resources.
Cristian, et al. (2016).
Figure 1.7 available in http://vaassudevan.blogspot.in/p/rest-architectural- style-for-web.html,illustrates the architectural style of RESTful services. Wu and Chiu (2016) deployed RESTful services to exchange Electronic
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implementation, a MIME envelope over the REST services, proved that a combination of S/MIME and RESTful services is good for secured solutions compared to Virtual Private Networks (VPN). The success of service composition relies on its ability to adapt to constantly to changing environments in terms of standards, architectures and platforms and it ability to scale up to the every expanding requirements and applications. REST based services have proved its capabilities in composing visible and reliable Web-scale applications. Table 1.2 lists the features of RESTful service composition approaches.
1.7. A USE CASE SCENARIO FROM A POST-HEART-SURGERY WARD
The motivation for this research work lies in the Intensive Therapy Unit (ITU) which is the recovery ward for most critically ill and post-surgery recovering patients Peberdy, et al. (2010). Typically heart surgery hospitals will have on an average of 30 to 35 bed ITUs. Each day there could be nearly 20 heart procedures. Each ITU is manned by 20 nurses.
Immediately after a heart surgery, the patient is very critical during the first 48 hours. The patient has to be closely monitored and numerous vital readings of body condition have to be logged. During the surgery, mediastinal tube (drain tube) is placed in the pericardial space which serves the purpose of draining post-operative bleeding and pericardial effusion Obney, et al. (2000). Another drain tube known as the pleural tube is also placed during the operation to drain blood and pleural fluid. Monitoring the pleural tube is very crucial Patti, et al. (2006). An excessive collection of blood indicates that a blood vessel would not have been properly cauterized
or it might indicate a ruptured graft. In both cases, if unchecked, the patient may go into a coma and eventually die. During the first hour after surgery a maximum of 150 ml would have drained, if it is in excess of 150 ml then the drain is watched for one more hour. If the drain continues to see an increase of more than 150 ml then the staff nurse Cavalcante, et al. (2015), surgeon is alerted to the situation. Meanwhile, blood samples are drawn and fed into Arterial Blood Gas (ABG) analyzer machine. The ABG primarily measures the Potassium, Carbon Dioxide, Bicarbonate, arterial oxygen tension and oxyhemoglobin saturation levels. If the hemoglobin level is below 9g/dl and the hematocrit levels fall below 30% then blood transfusion has to be done for the patient. In order to do a blood transfusion, the blood sample is again drawn and sent to the blood bank for cross matching and checking for availability. Once the doctor arrives at the ward, the x-ray which was taken just after the surgery is studied for fluid collection. If the doctor requires an Echocardiogram is also taken for analysis. Depending on the condition the doctor decides either for a blood transfusion or re-operation for the patient Mat and Andrew, (2013).
If the doctor decides for a blood transfusion, then the patient record has to be checked for the blood group Despotis, et al. (1996); Leal, et al. (2001). Also, alternate blood group information is also determined. The nurse places a request for the blood and the units required to the hospital blood bank. If the required blood group or the number of units required is not available then the officer in charge would try with other blood bank agencies. If the doctor decides for a re-operation, then the availability of the operation theatre has to be checked. Other members like anaesthetist and operation assistants have to notified. If the theatre is busy, approximate time of availability or in an
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emergency other nearby hospital should be contacted. The above-mentioned scenario calls for alert patient care personal and quick decision-making environment. For effective and optimized decision-making process the doctor and the nurse should be presented with adequate and accurate information Bricon and Newman, (2007). Human errors due to fatigue have zero tolerance in these scenarios Görges, Markewitz and Westenskow, (2009). Therefore, a context-aware system which would eventually react to the changes in the context, log the actions and parameters for learning and analysis and provide information for decision making is eminent and utilizing the Service Oriented Architecture for this particular use case domain seems to be of paramount importance.
1.8. RESEARCH QUESTIONS SUMMARY
This research work aims at answering the following research questions.
1. What service composition technique will be best adapted to a time- critical hospital environment context-aware system?
2. What are the components which are mandatory for a comprehensive context-aware framework which will aide rapid application development for a smarter healthcare?
3. What are the contexts found in a hospital environment where context- aware based applications will be of paramount importance?
1.9. ORGANIZATION OF THE THESIS The thesis is organized as follows:
Chapter 1 introduces various terms and definitions related to location- awareness, Internet of Things and context-awareness. A brief account of
healthcare domain and industry’s past and future direction has been presented.
Chapter 2 details the literature review conducted and categorises the review into four main headings. They are Context and Context-Awareness, Service composition, Context-Aware framework and Context Aware medical applications.
Chapter 3 presents a brief idea on the automata-based service composition modelling, namely service, timed and the proposed timed-service automata.
It also presents the verification result of the constructed automata.
Chapter 4 is a detailed presentation of the proposed context-aware framework for smart healthcare services. It also presents an algorithm for effective time bound service composition.
Chapter 5 is a discussion on the results achieved for the prototype implementation built using the proposed framework.
Chapter 2
Literature review
CHAPTER 2
LITERATURE REVIEW
2.1. INTRODUCTION
This chapter presents the background and related work on context-aware computing paradigm. The first step is to understand “context” in context- awareness and in context-aware computing, which will eventually help in exploring the applications which have been proposed or deployed in various domains. These applications in the context of IoT will be service driven;
therefore, it is very imperative that one understands the Service Oriented Architecture. The technique in composing these services is best modelled by using automata theory. One of the most vital areas where computer applications have a lot of social benefits is the healthcare domain. A casual study itself would reveal the numerous medical devices which are available in today’s market. In the next generation,these medical devices will possess the capabilities to communicate with each other through medical web services Rainer and Schahram, (2005).
Therefore the need, for a framework which will help application developers to rapidly develop healthcare applications driven by context awareness.
Choreographing web services is complex task, however workflow technique offers as an alternative architecture Adam, et al. (2009). The literature on the topic of context awareness, service composition techniques, and medical devices are extensive. The relevant literature has been studied and categorised into the following sections.
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Section 2.1 Context Awareness. The section, presents various definitions of Context, Context-Awareness, and Context-Aware Computing.
Section 2.2 Context-aware applications. This section presents a study of the selected software implementations using context-aware paradigm.
Section 2.3 Service Composition. With IoT, each device may pose a couple of services which have to communicate with other services in other devices. The challenge being the heterogeneity of the devices in terms of hardware, platform, language and data format. This section studies the various techniques researchers have proposed and deployed to establish communication between them.
Section 2.4 Medical device integrations. This section specifically presents the study on available devices available in a hospital and how they are integrated.
Section 2.5 Context-aware framework. This section presents an overview and a comparison of the available context-aware frameworks.
2.2. CONTEXT AWARENESS 2.2.1 CONTEXT
The word context can be lexically defined as a set of activities that are a result of a situation or event. Even though there is not much consensus about the idea or definition of context still most of the research work on context- awareness is based on the following definitions.
“Any information that can be used to characterize the situation of entities that are considered relevant to the interaction between a user and an application, including the user and the application themselves”Dey, (2001).
Henricksen et al. (2002) divides the idea of context into two major types, namely Static and Dynamic context. Static Context: is one in which the context never changes during the context period as in the case of the personal-calendar, contacts in a phonebook, user profile, user preference and hardware profile. But with the dynamic context, information is highly variable. Some of the dynamic context variablesinclude location, time, surrounding resources and system status Henricksen, et al. (2002). The researchers working on the idea of context awareness are two schools of thoughts: The positivist theory and Phenomenological theory. However, the fundamental work on context awareness heavily depends on the definition by Dey (2001), Mostéfaoui (2004), Gu (2005) and Baldauf (2007).
Two prominent views exist: Positivist theory which defines context as,
“Context can be described independently of the actions done” while Phenomenological theory defines context as, “Context emerges from the activity and cannot be described independently” Dourish (2004). Some of the most important definitions of context and context-aware computing are as follows:
“Something is context because of the way it is used in interpretation”Winograd (2001).
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“A pattern of behaviour or relations among variables that are outside of the subjects of design manipulation and potentially affect user behaviour and system performance” Sato (2003).
The purpose of defining context is widely understood as the presentation of information and services to a user. These services can be executed or context could be tagged with information for later retrieval. Three main classes of context items of information are People (location and identity), Environment (time) and Activities.
2.2.2 CONTEXT-AWARENESS
Applications based on context-awareness have certain design principles.
Various models have been proposed for representing contextual information.
Conditions such as local or remote sensors, the possible number of users, and involvement of mobile devices or personal computers are all considered while designing context-aware systems. Based on the data structures used, Linnhoff-Popien and Strang (2004) classified context awareness which is summarized and tabulated in Table 2.1 McCarthy and Buvac (1997); Hofer, et al. (2002); Sheng and Benatalla, (2005)
When a system is context-aware, there would be the enrichment of communication and useful services can be unearthed. To determine Context- awareness it follows subprocesses namely context acquisition, processing, and usage. Data is first acquired from sensors like temperature, pressure, etc.
then in the next step, four actions are mandatory. At context processing stage, removal of Noise in the data, calibration of data, interpretation and prediction of context are processed Gite, et al. (2016).
Table 2.1 Context-awareness models
Model Features
Key-Value Models
Simple data structure. Mainly used in service frameworks. Describes the capabilities of a service as key-value pairs.
Markup Models
Hierarchical data structure using markup scheme model. Profiles are created using markup tags, attributes, and content.
Graphical Models Context data is modelled using Unified Modelling Language (UML).
Object-Oriented Models
Context data represented using this technique offers encapsulation, inheritance and reusability.
Context attributes like Location, Temperature, etc. are defined as objects.
Logic-based Models
The context model is defined using rules, facts, and expressions. Context reasoning, new facts, are derived using existing rules.
Ontology-based Models
Context data is represented as relationships with their concepts. Ontology reasoning techniques and formal expressions are used in modelling the contextual data.
User-Context perception Model
Context data derived as sensory information should be constantly relayed back to the user to avoid a mismatch between user’s sensory perception and sensory input.
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2.2.3 CONTEXT AWARE COMPUTING
Objects or entities involved in a situation would indicate the context either explicitly or implicitly. Therefore, the pressing need of the context-aware application developer is to reduce the human effort to understand the context. Mark Weiser introduced the term context-aware computing which resulted from the research work on ubiquitous computing Weiser (1999).
Weiser defined is as “the most profound technologies are those that disappear”. The idea aims in integrating devices, mainly sensors, and actuators, seamlessly and offer anywhere and anytime communication and computation with anything allowing users to stay decoupled from devices Schilit and Theimer, (1994); Dey (2001); Hill, et al. (2004); Hong, et al.
(2009). “An application’s ability to adapt to changing circumstances and responds according to the context of use” Dey (2001).
It envisions multisensory perception and interaction with the intelligence and sense to interpret the information acquired from the sensors connected to an environment of seamless networking. Pervasive computing is being deployed in healthcare and this service is widely known as Pervasive healthcare Sriram, et al. (2015).
Any context-aware system should have the following context-oriented functionalities. It should be able to accommodate a variety of sensor-based devices. Should be able to understand context as it emanates from a distributed heterogeneous sources. Contextual data should be abstracted, while the interpretation of applications should be transparent. Context storage should be maintained well and data flow should be efficiently controlled Chitra and Adane, (2015).
Linnhoff-Popien and Strang (2004) states that context-aware systems have demanded the following terms.
1. Distributed Composition: absence of a central system for coordinating data maintenance and service provisioning.
2. Partial Validation: since it is recommended to be a distributed system, it is well known that complete contextual information will not be available in any particular node; however, it is still desirable to validate the information to make it error-free.
3. Richness and Quality of information: context-aware systems rely heavily on sensors which are hardware components and in due times are prone to give deteriorated quality of information. Also, sensors from different vendors may give the different richness of information.
4. Incompleteness and ambiguity: Interpolation of data might be required since data gathered from sensor networks might be incomplete or ambiguous.
5. The level of formality: Presenting contextual facts with their relationships is quite a challenge. In other words, interpretation should be common among all the participating objects of context.
6. Applicability of existing environments: context models should be within the available infrastructure.
2.3 CONTEXT-AWARE APPLICATIONS
According to Dey (2001), a system is said to be a context-aware system if,
“A system is context-aware if it uses context to provide relevant information and/or services to the user, where relevancy depends on the user’s task”
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for developing context-aware systems. Based on the way the steps of context acquisition, pre-processing, storing and reasoning are performed, three models have been proposed.
No application-level context model: All actions are performed within the application boundaries.
Implicit context model: All actions are performed by using frameworks, toolkits, and libraries. Provides standard design for rapid application building.
Explicit context model: Context management infrastructure or middleware solution is used resulting in stages being outside the application boundaries. The management and application are separated and can be developed and extended independently.
Schilit, et al.(1994) and Pascoe (1998) presented three important features that any context-aware system should process and Charith, et al. (2013) extended the features to accommodate IoT.
Presentation: Context-aware systems should decide on the information and service that are presented to the user based on location, time and other context attributes Carnot (2011); Moses (2012).
Execution: Context-aware systems should execute the services automatically without or with minimum human interference.
Tagging: Context-aware systems should be able to annotate or tag the data collected from numerous sensors as these data has to be fused together.
2.3.1 GENERAL CONTEXT-AWARE APPLICATIONS
A context-aware smart home, proposed by Xiaopeng and Zhiliang (2016), details the services that can be provided for the homeowners. The paper proposes a UML and Colored Petri Net (CPN) based hybrid Context-aware modelling approach. The work mainly focuses on the technique of avoiding deadlocks and formally verifying the model.
Road safety and transportation network are indispensable today and one of the key networks which help them with this mission is the Vehicular Ad-hoc Networks (VANETs). Services such as traffic alert, collision alert, convenient alert and unmanned vehicle driving have been designed based on this network. The paper proposes a framework for applications to be developed on this network considering the environment, application, and context Vahdat, et al. (2016).
2.3.2. HEALTHCARE RELATED APPLICATIONS
Context-awareness in healthcare would help in utilizing the human resource and device resource more efficiently and promote quality of service considering the patient’s condition and need. Some of the context-aware medical applications are: VOCERACOMMUNICATION SYSTEM which got experimented at St. Vincent Hospital, Birmingham, USA uses communicator badge system for mobile user Push-to-call button, small text screen, voice dialling, and hands-free conversation which are biometrically secured with speaker verification Stanford (2003).
STROKE ANGEL experiment was conducted at Bad Neustadt, Germany (November 2005-May 2008). The main aim of this system is to shorten the
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time requirement for the entire process. That is from discovery and diagnosing the stroke victim to the patient’s admission and treatment in hospitals. This is the main goal is to meet the short time frame in which to treat the stroke patient the first 3 hours after the stroke Orwat, et al. (2010).
In INTELLIGENT HOSPITAL SOFTWARE, University of Cambridge, UK an experimental prototype has been implemented after the study of needs at the Accident & Emergency Department of the Royal London Hospital. The system includes remote consultation, tracking of patients and equipment, notification of awareness and patient data Mitchel, et al. (2000). One more study was conducted for a period of 8 months in mid-size public hospitals in the city of Ensenada, Mexico. The emphasis was done on the activities performed by three roles. They are Nurses, Physicians and the medical interns Favela, et al. (2006).
A decision-level data fusion technique for monitoring and reporting critical health conditions of hypertensive patients. H-SAUDE (Health Support in Aware and Ubiquitous Domestic Environments) proposes an architectural framework for individualization of treatment, influence of the patient activity and of the home environment, relaxation (or loosening) of the limits of each monitored variable Copetti, et al. (2009). Hospital based prototypes involve the design of a context-aware pill container and a context-aware hospital bed, both of which reacts and adapts according to what is happening in their context Bardram, (2004).
MobileWARD (Mobile Electronic Patient Record, Denmark) project supports morning procedure tasks in a hospital ward, information, and
functionalities according to the location of the nurse and the time. Few other prototypes include medication consumption, distant monitoring and new assistants Skov and Hegh, (2006). The afore-mentioned research works reveal three relevant classes of information which have been identified to gather through the pervasive device. These are Environmental, Psychological, and Behavioural.
Erik et al. (2016) in their work, applied context awareness to e-Health and m-Health catering to the needs of households. An implementation of social sensor prototype to exhibit their flexibility, complexity and cost features which use a Bluetooth transceiver is described. Data acquisition from multiple sensors has been demonstrated in the work.
A context-aware framework illustrates abstracted layers which could be envisaged in a system that claims to be context-aware. A framework or an architecture supporting context-aware system or a context-aware middleware should either be built or capable of building by incorporating this abstracted model. The above said higher level abstractions are only possible to be built from a lower level abstraction or context management.
Any context management should possess the features such as context acquisition, aggregation and fusion, dissemination, discovery. Context acquisition can be made from various sources namely; sensors, social media, web databases. The acquired data can be filtered to form the high level abstraction of the context. The next step of dissemination involves passing on the context to the other entities. Situation recognition entities and Reasoning engines along with objects involved in recognizing situations should find sources of context and publish it. The challenge in designing
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grows bigger when the context dissemination and discovery is over a distributed system. Therefore ensuring quality in the acquired and reasoned out context is an absolute required feature of context management.
Context-aware systems manage context on different levels of abstraction.
Contextual information can be represented by a single scalar value such as
“body temperature is 101.6 degrees Fahrenheit” which represents the raw output of a sensor. Contextual information can also be a higher-level semantic description of a situation such as “Patient is having fever”.
Therefore, a context-aware system should be capable of interpreting from a raw sensor data meaningful information abstracted appropriately. There should be a transformation of low-level sensing to high-level context provision Baker (2009).
2.4 SERVICE ORIENTED ARCHITECTURE AND SERVICE COMPOSITION
One of the main ingredients of Service Oriented Architecture is the web services. With the explosion of web services in the internet, it becomes important to pave way for service discovery and service integration and it is a very pressing problem Pejman, et al. (2012). “Web services are modular, self-describing, self-contained and loosely coupled applications that can be published, located and invoked across the web” Narges, et al. (2013).
Artificial Intelligence planning has proved good in web service choreography in distributed environment Guobing, et al. (2014).
Vincenzo et al. (2005) designed and implemented design principles for service discovery technique in pervasive environment. Angelo and Eugenio (2014) proposed a model to generated context-aware service compositions
involving planning. It highlighted the need for rules evaluation especially when multiple services satisfy post-condition. From the literature survey we can understand that there are some immense and fundamental challenges for the supporting infrastructure for scenarios of this type
These are pervasive adaptive systems that respond to things around them with no centralised authority.
Services provided are more dynamic requiring discovery, ad-hoc composition, and orchestration.
It is a more knowledge-based infrastructure that attempts to recognise situations and reason about the environment.
From the above literature review, it can be concluded that–
A context-aware system by definition is able to sense, adapt and respond.
Representing, learning and reasoning about situations and circumstances of the real world is the key fit any context-aware system.
Context-aware systems need to monitor people and devices to sense and react to changes.
Lifecycle of Web services
There are 5 steps included in lifecycle of Web services
1. Advertisement: The service provider publishes its description and endpoints of the web service in the directory called service registry.
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2. Discovery: The service consumer or the service requestor locates all the Web services and its description to check if it matches their functional requirements.
3. Selection: The service requestor selects the most suitable web service out of all the web services in the service registry based on application dependent metrics.
4. Composition: After selecting the suitable web services the service requestor integrates all the web services into a complex process.
5. Invocation: In this final step the web services or complex process is invoked and set for execution by providing all the inputs.
2.4.1 SERVICE AUTOMATA
Service automata have been suggested to be used for service discovery and composition problem in context-aware systems Gay, et al. (2011); Zhichao, et al. (2012). In this technique a context space comprising the context, situation, services and user preference are unified and dealt. The desired goal situation is predicted by the user preference and the situation faced by the user. A service composition is achieved by emphasizing the relationship between context and services and by formalizing semantic web services as automata. Further by using a composite service automaton, services are composed to achieve the goal situation.
Service automata are defined as a tuple: <C,∑, Q, δ, I, F, V> where:
C=<CPre, CEff> is a pair which represents the Context Attributes (CA) of Context Space (CSP) related to the service. CPre and CEff represent CAs related to precondition and effect of the service respectively. CEff denotes the CAs that the service can change.
∑= AI ⋃ AO ⋃ AH is a finite set of actions. AI represents input action; AO represents output action and AH represents service’s inner actions.
Q is a finite set of states of the automata (Q ≠∅) which represents the Context State (CS) of C.
δ is the transition function, that is, Q× ∑
I am a finite set of initial states and
F is finite set of final states and
V is an assignment function, e.g. V: (value range of the corresponding CAs in CSP)
The transition function (δ) in service automata is defined as ak
(δ) = qiqj ak = set of actions
qi = state: immediate predecessor
qj = state: immediate successor of the action ‘a’
2.4.2 TIMED AUTOMATA
Timed automata takes into consideration explicit timing constraints present in real-life situations and always the time considered is finite because they are measurable quantities Bengtsson and Yi, (2004); Patricia (2005);
Béatrice (2013). In Finite automata terms, the node must have a reachable property. Time domain is considered here as the set of all positive real numbers. A timed word is a set of alphabets from the given alphabet * time values provided. Also ‘r’, a finite set of variables called clock values is considered.
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There is always a mapping between clock and time domain values. Usually, clock value which is bounded can have values between –k and +k (k- bounded clock). The final state is reached from the initial state using ‘n’
edges which are the path of the automata in a finite amount of time taking into consideration clock constraints. The time constraint need not be single value it can be a range of values. The only difference of timed automata from the normal finite automata is the clock function. Deadlines are present to complete each task while acceptance is reached. Figure 2.1 illustrate the design of timed automata, in which, we use a threshold value as the limiter for each state transition. If the value is greater than threshold then the transition to next state doesn’t occur and the machine/automata must again perform the set of operations to reach the next state from the beginning. If the value of the time duration less than or equal to threshold then there is a transition to next state. The main advantage of using a clock function here enables the user to perform the set of operations and reach the final state in a finite amount of time in all situations. Each service is completed in a finite amount of time. All these finite values added up also gives a finite value hence the transition from the start state to final state is also finite.
Figure 2.1 A Timed Automaton
A timed automaton is defined as a tuple TA=<∑, Q, T, I, F, X> where:
∑= AI⋃AO⋃AH is a finite set of actions. AI represents input action;
AOrepresents output action; AHrepresents service’s inner actions.
Q is a finite set of states of the automata (Q≠∅) which represents the CS of C.
T is the transition function, that is, Q×∑
I am a finite set of initial states and
F is finite set of final states and
X is a clock
The transition function (T) in timed automata is defined as g, a, Y
qiqj
g = clock constraints a = set of actions Y = subset of clocks
qi= state: immediate predecessor
qj= state: immediate successor of the action ‘a’
2.4.3 SERVICE COMPOSITION
The web service composition techniques by industry standards are two varieties namely Syntactic Web Service composition and Semantic Web Service composition. The Syntactic Web Service composition is an XML- based approach which is further divided into Web Service Orchestration and Web Service Choreography. WS Orchestration – Combines available WSs by adding a central coordinator (the orchestrator) which invokes and combines the single sub-activities. WS Choreography - Overall activity is
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achieved by the composition of peer-to-peer interactions among the collaborating WSs. Semantic WS Composition (ontology-based) describe various aspects of WSs by using explicit, machine-understandable semantics, and as such automate all stages of the WS lifecycle Beeket,et al.
(2013); McIlraith, et al. (2001).
By Formal methods, the Web Service composition problem can be approached by using Petri nets, Process Algebras, and Automata. Petri nets is a framework to model concurrent systems Baker, (2009). Their main attraction is the natural way of identifying basic aspects of concurrent systems, both mathematically and conceptually. Process Algebras comes with a rich theory to establish whether two processes have equivalent behaviours Gay, et al. (2011). Automata uses Timed Automata Zhichao, et al. (2012); Bengtsson and Yi, (2004); Patricia (2005); Béatrice (2013) and Service Automata.
2.5 MEDICAL DEVICE INTEGRATION
NASS (Network-Aware Supervisory System) proposes a framework prototype for medical device integration systems Kim,et al. (2012).The necessities and feasibilities of integrating biomedical, implantable medical devices and micro-nano systems are explored. The paper further suggests the need for a multi-sensor and heterogeneous 3D integration, flexible and biocompatible packaging Deterre (2012).
A prototype is presented based on real equipment and the Devices Profile to show the feasibility of medical device communication in an interoperable and plug & play like manner Gregorczyk, et al. (2012)
2.6 CONTEXT-AWARE FRAMEWORK
Context-Aware Real-time Assistant (CARA). This system gathers and understands context-aware information from the acquired data. To achieve this, context aware hybrid reasoning framework gives by case based reasoning and fuzzy rule-based reasoning Bingchuan and Herbert, (2014);
Yuan and Herbert, (2012). Ubiquitous Context-aware Healthcare Service System (UCHS). This framework gives the overview of the natural medical service in semantic web combines the technical application of SOA.
Table 2.2 Comparison of three major healthcare frameworks
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The system provides strong auxiliary utility to support the user while they have some complex problem Lo, et al. (2011). Table 2.2 is an excerpt summary of a detailed comparison on the most recent healthcare framework by Sriram et al. (2015).
