Managing sensitive data in dynamic and high-stakes environments,such as healthcare,requires access control frameworks that offer real-time adaptability,scalability,and regulatory compliance.BIG-ABAC introduces a trans...Managing sensitive data in dynamic and high-stakes environments,such as healthcare,requires access control frameworks that offer real-time adaptability,scalability,and regulatory compliance.BIG-ABAC introduces a transformative approach to Attribute-Based Access Control(ABAC)by integrating real-time policy evaluation and contextual adaptation.Unlike traditional ABAC systems that rely on static policies,BIG-ABAC dynamically updates policies in response to evolving rules and real-time contextual attributes,ensuring precise and efficient access control.Leveraging decision trees evaluated in real-time,BIG-ABAC overcomes the limitations of conventional access control models,enabling seamless adaptation to complex,high-demand scenarios.The framework adheres to the NIST ABAC standard while incorporating modern distributed streaming technologies to enhance scalability and traceability.Its flexible policy enforcement mechanisms facilitate the implementation of regulatory requirements such as HIPAA and GDPR,allowing organizations to align access control policies with compliance needs dynamically.Performance evaluations demonstrate that BIG-ABAC processes 95% of access requests within 50 ms and updates policies dynamically with a latency of 30 ms,significantly outperforming traditional ABAC models.These results establish BIG-ABAC as a benchmark for adaptive,scalable,and context-aware access control,making it an ideal solution for dynamic,high-risk domains such as healthcare,smart cities,and Industrial IoT(IIoT).展开更多
Purpose:Policies have often,albeit inadvertently,overlooked certain scientific insights,especially in the handling of complex events.This study aims to systematically uncover and evaluate pivotal scientific insights t...Purpose:Policies have often,albeit inadvertently,overlooked certain scientific insights,especially in the handling of complex events.This study aims to systematically uncover and evaluate pivotal scientific insights that have been underrepresented in policy documents by leveraging extensive datasets from policy texts and scholarly publications.Design/methodology/approach:This article introduces a research framework aimed at excavating scientific insights that have been overlooked by policy,encompassing four integral parts:data acquisition and preprocessing,the identification of overlooked content through thematic analysis,the discovery of overlooked content via keyword analysis,and a comprehensive analysis and discussion of the overlooked content.Leveraging this framework,the research conducts an in-depth exploration of the scientific content overlooked by policies during the COVID-19 pandemic.Findings:During the COVID-19 pandemic,scientific information in four domains was overlooked by policy:psychological state of the populace,environmental issues,the role of computer technology,and public relations.These findings indicate a systematic underrepresentation of important scientific insights in policy.Research limitations:This study is subject to two key limitations.Firstly,the text analysis method—relying on pre-extracted keywords and thematic structures—may not fully capture the nuanced context and complexity of scientific insights in policy documents.Secondly,the focus on a limited set of case studies restricts the broader applicability of the conclusions across diverse situations.Practical implications:The study introduces a quantitative framework using text analysis to identify overlooked scientific content in policy,bridging the gap between science and policy.It also highlights overlooked scientific information during COVID-19,promoting more evidence-based and robust policies through improved science-policy integration.Originality/value:This paper provides new ideas and methods for excavating scientific information that has been overlooked by policy,further deepens the understanding of the interaction between policy and science during the COVID-19 period,and lays the foundation for the more rational use of scientific information in policy-making.展开更多
Smart cars are promising application domain for ubiquitous computing. Context-awareness is the key feature of a smart car for safer and easier driving. Despite many industrial innovations and academic progresses have ...Smart cars are promising application domain for ubiquitous computing. Context-awareness is the key feature of a smart car for safer and easier driving. Despite many industrial innovations and academic progresses have been made, we find a lack of fully context-aware smart cars. This study presents a general architecture of smart cars from the viewpoint of context- awareness. A hierarchical context model is proposed for description of the complex driving environment. A smart car prototype including software platform and hardware infrastructures is built to provide the running environment for the context model and applications. Two performance metrics were evaluated: accuracy of the context situation recognition and efficiency of the smart car. The whole response time of context situation recognition is nearly 1.4 s for one person, which is acceptable for non-time critical applications in a smart car.展开更多
The service recommendation mechanism as a key enabling technology that provides users with more proactive and personalized service is one of the important research topics in mobile social network （MSN）. Meanwhile, M...The service recommendation mechanism as a key enabling technology that provides users with more proactive and personalized service is one of the important research topics in mobile social network （MSN）. Meanwhile, MSN is susceptible to various types of anonymous information or hacker actions. Trust can reduce the risk of interaction with unknown entities and prevent malicious attacks. In our paper, we present a trust-based service recommendation algorithm in MSN that considers users＇ similarity and friends＇ familiarity when computing trustworthy neighbors of target users. Firstly, we use the context information and the number of co-rated items to define users＇ similarity. Then, motivated by the theory of six degrees of space, the friend familiarity is derived by graph-based method. Thus the proposed methods are further enhanced by considering users＇ context in the recommendation phase. Finally, a set of simulations are conducted to evaluate the accuracy of the algorithm. The results show that the friend familiarity and user similarity can effectively improve the recommendation performance, and the friend familiarity contributes more than the user similarity.展开更多
The rapid development of information and communication technologies(ICTs)and cyber-physical systems(CPSs)has paved the way for the increasing popularity of smart products.Context-awareness is an important facet of pro...The rapid development of information and communication technologies(ICTs)and cyber-physical systems(CPSs)has paved the way for the increasing popularity of smart products.Context-awareness is an important facet of product smartness.Unlike artifacts,various bio-systems are naturally characterized by their extraordinary context-awareness.Biologically inspired design(BID)is one of the most commonly employed design strategies.However,few studies have examined the BID of context-aware smart products to date.This paper presents a structured design framework to support the BID of context-aware smart products.The meaning of context-awareness is defined from the perspective of product design.The framework is developed based on the theoretical foundations of the situated function-behavior-structure ontology.A structured design process is prescribed to leverage various biological inspirations in order to support different conceptual design activities,such as problem formulation,structure reformulation,behavior reformulation,and function reformulation.Some existing design methods and emerging design tools are incorporated into the framework.A case study is presented to showcase how this framework can be followed to redesign a robot vacuum cleaner and make it more context-aware.展开更多
This paper discussed the differences of context-aware service between the cloud computing environment and the traditional service system.Given the above differences,the paper subsequently analyzed the changes of conte...This paper discussed the differences of context-aware service between the cloud computing environment and the traditional service system.Given the above differences,the paper subsequently analyzed the changes of context-aware service during preparation,organization and delivery,as well as the resulting changes in service acceptance of consumers.Because of these changes,the context-aware service modes in the cloud computing environment change are intelligent,immersive,highly interactive,and real-time.According to active and responded service,and authorization and non-authorized service,the paper drew a case diagram of context-aware service in Unified Modeling Language(UML) and established four categories of context-aware service modes.展开更多
Autonomic networking is one of the hot research topics in the research area of future network architectures.In this paper, we introduce context-aware and autonomic attributes into DiffServ QoS framework, and propose a...Autonomic networking is one of the hot research topics in the research area of future network architectures.In this paper, we introduce context-aware and autonomic attributes into DiffServ QoS framework, and propose a novel autonomic packet marking(APM) algorithm.In the proposed autonomic QoS framework, APM is capable of collecting various QoS related contexts, and adaptively adjusting its behavior to provide better QoS guarantee according to users' requirements and network conditions.Simulation results show that APM provides better performance than traditional packet marker, and significantly improves user's quality of experience.展开更多
With the development of communication and ubiquitous computing technologies, context-aware services, which acquire contextual information of users and environment, have become critical applications providing customiza...With the development of communication and ubiquitous computing technologies, context-aware services, which acquire contextual information of users and environment, have become critical applications providing customization in mobile commerce. Meanwhile, tourism has attracted increasing attention as a high value-added service and a hot academic topic. However, the research on how to provide tour services based on context-aware services is in fact still at an early stage, limited to concept elaboration, service framework discussion, prototype system development etc. In this paper, we summarized the previous researches on context-aware services to establish the research foundation, put forward a way of analyzing a tour planning problem with a modified model of Traveling Salesman Problem （TSP） and Vehicle Routing Problem （VRP）, and we applied an innovated Resource Constrain Project Scheduling Problem （RCPSP） mathematical model to solve the tour planning problem based on context information. The simulation under branch and bound algoritban evaluated the validity of our solution.展开更多
In recent years, several researchers have applied workflow technologies for service automation on ubiquitous compating environments. However, most context-aware workflows do not offer a method to compose several workf...In recent years, several researchers have applied workflow technologies for service automation on ubiquitous compating environments. However, most context-aware workflows do not offer a method to compose several workflows in order to get mare large-scale or complicated workflow. They only provide a simple workflow model, not a composite workflow model. In this paper, the autorhs propose a context-aware workflow model to support composite workflows by expanding the patterns of the existing context-aware wrY：flows, which support the basic woddlow patterns. The suggested workflow model of. fers composite workflow patterns for a context-aware workflow, which consists of various flow patterns, such as simple, split, parallel flows, and subflow. With the suggested model, the model can easily reuse few of existing workflows to make a new workflow. As a result, it can save the development efforts and time of context-aware workflows and increase the workflow reusability. Therefore, the suggested model is expected to make it easy to develop applications related to context-aware workflow services on ubiquitous computing environments.展开更多
Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the c...Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the continual exchange of vehicle motion-state information, such as position, speed, and heading, which enables each vehicle to track its neighboring vehicles in real time. This work presents a context-aware adaptive beaconing scheme that dynamically adapts the beaconing repetition rate based on an estimated channel load and the danger severity of the interactions among vehicles. The safety, efficiency, and scalability of the new scheme is evaluated by simulating vehicle collisions caused by inattentive drivers under various road traffic densities. Simulation results show that the new scheme is more efficient and scalable, and is able to improve safety better than the existing non-adaptive and adaptive rate schemes.展开更多
The digital technologies that run based on users’content provide a platform for users to help air their opinions on various aspects of a particular subject or product.The recommendation agents play a crucial role in ...The digital technologies that run based on users’content provide a platform for users to help air their opinions on various aspects of a particular subject or product.The recommendation agents play a crucial role in personalizing the needs of individual users.Therefore,it is essential to improve the user experience.The recommender system focuses on recommending a set of items to a user to help the decision-making process and is prevalent across e-commerce and media websites.In Context-Aware Recommender Systems(CARS),several influential and contextual variables are identified to provide an effective recommendation.A substantial trade-off is applied in context to achieve the proper accuracy and coverage required for a collaborative recommendation.The CARS will generate more recommendations utilizing adapting them to a certain contextual situation of users.However,the key issue is how contextual information is used to create good and intelligent recommender systems.This paper proposes an Artificial Neural Network(ANN)to achieve contextual recommendations based on usergenerated reviews.The ability of ANNs to learn events and make decisions based on similar events makes it effective for personalized recommendations in CARS.Thus,the most appropriate contexts in which a user should choose an item or service are achieved.This work converts every label set into a Multi-Label Classification(MLC)problem to enhance recommendations.Experimental results show that the proposed ANN performs better in the Binary Relevance(BR)Instance-Based Classifier,the BR Decision Tree,and the Multi-label SVM for Trip Advisor and LDOS-CoMoDa Dataset.Furthermore,the accuracy of the proposed ANN achieves better results by 1.1%to 6.1%compared to other existing methods.展开更多
Opportunistic networking-forwarding messages in a disconnected mobile ad hoc network via any encountered nodes offers a new mechanism for exploiting the mobile devices that many users already carry. However, forwardin...Opportunistic networking-forwarding messages in a disconnected mobile ad hoc network via any encountered nodes offers a new mechanism for exploiting the mobile devices that many users already carry. However, forwarding messages in such a network is trapped by many particular challenges, and some protocols have contributed to solve them partly. In this paper, we propose a Context-Aware Adaptive opportunistic Routing algorithm（CAAR）. The algorithm firstly predicts the approximate location and orientation of the destination node by using its movement key positions and historical communication records, and then calculates the best neighbor for the next hop by using location and velocity of neighbors. In the unpredictable cases, forwarding messages will be delivered to the more capable forwarding nodes or wait for another transmission while the capable node does not exist in the neighborhood. The proposed algorithm takes the movement pattern into consideration and can adapt different network topologies and movements. The experiment results show that the proposed routing algorithm outperforms the epidemic forwarding（EF） and the prophet forwarding（PF） in packet delivery ratio while ensuring low bandwidth overhead.展开更多
In many wireless sensor networks(WSNs)applications,the preservation of source-location privacy plays a critical role in concealing context information,otherwise the monitored entities or subjects may be put in danger....In many wireless sensor networks(WSNs)applications,the preservation of source-location privacy plays a critical role in concealing context information,otherwise the monitored entities or subjects may be put in danger.Many traditional solutions have been proposed based on the creation of random routes,such as random walk and fake sources approach,which will lead to serious packet delay and high energy consumption.Instead of applying the routing in a blind way,this article proposes a novel solution for source location privacy in WSNs by utilizing sensor ability of perceiving the presence a mobile attacker nearby,for patient attackers in particular to increase the safety period and decrease the data delivery delay.The proposed strategy forms an intelligent silent zone(ISZ)by sacrificing only a minority of sensor nodes to entice patient attackers away from real packet routing path.The analysis and simulation results show that the proposed scheme,besides providing source location privacy energy efficiently,can significantly reduce real event reporting latency compared with the existing approaches.展开更多
In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to an...In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to analyze and describe the relationships between animation data.Second,a novel context model which is able to keep the context-awareness was proposed to facilitate data organization and storage.In our context model,all the main animation elements in a scene are operated as a whole.Then sketch is utilized as the main interactive method to describe the relationships between animation data,edit the context model and make some other user operations.Finally,a context-aware computer animation data description system based on sketch is generated and it also works well in animation generation process.展开更多
Recent years have witnessed the expeditious evolution of intelligentsmart devices and autonomous software technologies with the expandeddomains of computing from workplaces to smart computing in everydayroutine life a...Recent years have witnessed the expeditious evolution of intelligentsmart devices and autonomous software technologies with the expandeddomains of computing from workplaces to smart computing in everydayroutine life activities. This trend has been rapidly advancing towards the newgeneration of systems where smart devices play vital roles in acting intelligently on behalf of the users. Context-awareness has emerged from the pervasive computing paradigm. Context-aware systems have the ability to acquirecontextual information from the surrounding environment autonomously,perform reasoning on it, and then adapt their behaviors accordingly. With theproliferation of context-aware systems and smart sensors, real-time monitoring of environmental situations (context) has become quite trivial. However,it is often challenging because the imperfect nature of context can cause theinconsistent behavior of the system. In this paper, we propose a contextaware intelligent decision support formalism to assist cognitively impairedpeople in managing their routine life activities. For this, we present a semanticknowledge-based framework to contextualize the information from the environment using the protégé ontology editor and Semantic Web Rule Language(SWRL) rules. The set of contextualized information and the set of rulesacquired from the ontology can be used to model Context-aware Multi-AgentSystems (CMAS) in order to autonomously plan all activities of the users andnotify users to act accordingly. To illustrate the use of the proposed formalism,we model a case study of Mild Cognitive Impaired (MCI) patients usingColored Petri Nets (CPN) to show the reasoning process on how the contextaware agents collaboratively plan activities on the user’s behalf and validatethe correctness properties of the system.展开更多
Service-Oriented Communication(SOC)is a key research issue to enable media communications using the Service-Oriented Architecture(SOA).Motivated by the necessity to guarantee the service quality of our webbased multim...Service-Oriented Communication(SOC)is a key research issue to enable media communications using the Service-Oriented Architecture(SOA).Motivated by the necessity to guarantee the service quality of our webbased multimedia conferencing system,we present a Comprehensively Context-Aware(CoCA)approach in this paper.One major problem in the existing end-to-end Quality of Service(QoS)management solutions is that they analyse and exploit the relationships between the QoS metrics and corresponding contexts in an isolated manner.In this paper,we propose a novel approach to leveraging such relationships in a comprehensive manner based on Bayesian networks and the fuzzy set theory.This approach includes three phases:1)information feedback and training,2)QoS-to-context mapping,and3)optimal context adaption.We implement the proposed CoCA in the real multimedia conferencing system and compare its performance with the existing bandwidth aware and playback buffer aware schemes.Experimental results show that the proposed CoCA outperforms the competing approaches in improving the average video Peak Signal-to-Noise Ratio(PSNR).It also exhibits good performance in preventing the playback buffer starvation.展开更多
The recommendation system can efficiently solve the information overload in mobile Internet. Thus, how to effectively utilize context information to improve the accuracy of recommendation becomes the research focus in...The recommendation system can efficiently solve the information overload in mobile Internet. Thus, how to effectively utilize context information to improve the accuracy of recommendation becomes the research focus in the field. This article puts forward a novel approach to realize the context-aware recommendation in mobile environments. It first gets users’ interest resonance with a hash-based interest resonance mining algorithm. Then, it calculates the association degree between the user and the item and then predicts the user’s rating on the item. Finally, it comprehensively figures out the recommending index. Moreover, this article also designs a personal recommendation model for the users and provides relevant decision-making coefficients. Experiments have demonstrated that our approach is superior to the traditional ones （RMP, RSTE, MD and BBBs） in both performance and efficiency.展开更多
Communication or the lack of it has been complained to be a major contributor to medical errors in healthcare.To enhance communication in hospital,diverse communication mechanisms are proposed.However,human directed c...Communication or the lack of it has been complained to be a major contributor to medical errors in healthcare.To enhance communication in hospital,diverse communication mechanisms are proposed.However,human directed communication in a complex clinical setting in which many people play diverse roles and need to collaborate in many parallel tasks is always in chaos and inefficient.Context-aware communication which can help target who should be communicated and what information should be provided for different scenarios has the potential to improve the communication in hospital.This paper proposes a flexible,automated and asynchronous context-aware medical instant message(IM)middleware which support dispatch,forward and routing different message to the right person in the right time based on the context information.A prototype of this IM communication middleware was implemented in real clinical setting for evaluation.The preliminary results demonstrate its novel features and clinical feasibility.展开更多
文摘Managing sensitive data in dynamic and high-stakes environments,such as healthcare,requires access control frameworks that offer real-time adaptability,scalability,and regulatory compliance.BIG-ABAC introduces a transformative approach to Attribute-Based Access Control(ABAC)by integrating real-time policy evaluation and contextual adaptation.Unlike traditional ABAC systems that rely on static policies,BIG-ABAC dynamically updates policies in response to evolving rules and real-time contextual attributes,ensuring precise and efficient access control.Leveraging decision trees evaluated in real-time,BIG-ABAC overcomes the limitations of conventional access control models,enabling seamless adaptation to complex,high-demand scenarios.The framework adheres to the NIST ABAC standard while incorporating modern distributed streaming technologies to enhance scalability and traceability.Its flexible policy enforcement mechanisms facilitate the implementation of regulatory requirements such as HIPAA and GDPR,allowing organizations to align access control policies with compliance needs dynamically.Performance evaluations demonstrate that BIG-ABAC processes 95% of access requests within 50 ms and updates policies dynamically with a latency of 30 ms,significantly outperforming traditional ABAC models.These results establish BIG-ABAC as a benchmark for adaptive,scalable,and context-aware access control,making it an ideal solution for dynamic,high-risk domains such as healthcare,smart cities,and Industrial IoT(IIoT).
基金financially supported by the Ningbo University of Technology New Faculty Research Fundthe 2023 Interdisciplinary Innovation Research Cultivation Program of School of Interdisciplinary Studies,RUCKey Project of the National Social Science Foundation of China(21ATQ008)。
文摘Purpose:Policies have often,albeit inadvertently,overlooked certain scientific insights,especially in the handling of complex events.This study aims to systematically uncover and evaluate pivotal scientific insights that have been underrepresented in policy documents by leveraging extensive datasets from policy texts and scholarly publications.Design/methodology/approach:This article introduces a research framework aimed at excavating scientific insights that have been overlooked by policy,encompassing four integral parts:data acquisition and preprocessing,the identification of overlooked content through thematic analysis,the discovery of overlooked content via keyword analysis,and a comprehensive analysis and discussion of the overlooked content.Leveraging this framework,the research conducts an in-depth exploration of the scientific content overlooked by policies during the COVID-19 pandemic.Findings:During the COVID-19 pandemic,scientific information in four domains was overlooked by policy:psychological state of the populace,environmental issues,the role of computer technology,and public relations.These findings indicate a systematic underrepresentation of important scientific insights in policy.Research limitations:This study is subject to two key limitations.Firstly,the text analysis method—relying on pre-extracted keywords and thematic structures—may not fully capture the nuanced context and complexity of scientific insights in policy documents.Secondly,the focus on a limited set of case studies restricts the broader applicability of the conclusions across diverse situations.Practical implications:The study introduces a quantitative framework using text analysis to identify overlooked scientific content in policy,bridging the gap between science and policy.It also highlights overlooked scientific information during COVID-19,promoting more evidence-based and robust policies through improved science-policy integration.Originality/value:This paper provides new ideas and methods for excavating scientific information that has been overlooked by policy,further deepens the understanding of the interaction between policy and science during the COVID-19 period,and lays the foundation for the more rational use of scientific information in policy-making.
基金Project supported by the National Hi-Tech Research and Develop-ment Program (863) of China (Nos. 2006AA01Z198, and2008AA01Z132)the National Natural Science Foundation of China(No. 60533040)the National Science Fund for Distinguished Young Scholars of China (No. 60525202)
文摘Smart cars are promising application domain for ubiquitous computing. Context-awareness is the key feature of a smart car for safer and easier driving. Despite many industrial innovations and academic progresses have been made, we find a lack of fully context-aware smart cars. This study presents a general architecture of smart cars from the viewpoint of context- awareness. A hierarchical context model is proposed for description of the complex driving environment. A smart car prototype including software platform and hardware infrastructures is built to provide the running environment for the context model and applications. Two performance metrics were evaluated: accuracy of the context situation recognition and efficiency of the smart car. The whole response time of context situation recognition is nearly 1.4 s for one person, which is acceptable for non-time critical applications in a smart car.
基金Supported by the National Natural Science Foundation of China(71662014 and 61602219)the Natural Science Foundation of Jiangxi Province of China(20132BAB201050)the Science and Technology Project of Jiangxi Province Educational Department(GJJ151601)
文摘The service recommendation mechanism as a key enabling technology that provides users with more proactive and personalized service is one of the important research topics in mobile social network （MSN）. Meanwhile, MSN is susceptible to various types of anonymous information or hacker actions. Trust can reduce the risk of interaction with unknown entities and prevent malicious attacks. In our paper, we present a trust-based service recommendation algorithm in MSN that considers users＇ similarity and friends＇ familiarity when computing trustworthy neighbors of target users. Firstly, we use the context information and the number of co-rated items to define users＇ similarity. Then, motivated by the theory of six degrees of space, the friend familiarity is derived by graph-based method. Thus the proposed methods are further enhanced by considering users＇ context in the recommendation phase. Finally, a set of simulations are conducted to evaluate the accuracy of the algorithm. The results show that the friend familiarity and user similarity can effectively improve the recommendation performance, and the friend familiarity contributes more than the user similarity.
基金This work was supported in part by the project of the National Natural Science Foundation of China(51875030).
文摘The rapid development of information and communication technologies(ICTs)and cyber-physical systems(CPSs)has paved the way for the increasing popularity of smart products.Context-awareness is an important facet of product smartness.Unlike artifacts,various bio-systems are naturally characterized by their extraordinary context-awareness.Biologically inspired design(BID)is one of the most commonly employed design strategies.However,few studies have examined the BID of context-aware smart products to date.This paper presents a structured design framework to support the BID of context-aware smart products.The meaning of context-awareness is defined from the perspective of product design.The framework is developed based on the theoretical foundations of the situated function-behavior-structure ontology.A structured design process is prescribed to leverage various biological inspirations in order to support different conceptual design activities,such as problem formulation,structure reformulation,behavior reformulation,and function reformulation.Some existing design methods and emerging design tools are incorporated into the framework.A case study is presented to showcase how this framework can be followed to redesign a robot vacuum cleaner and make it more context-aware.
基金the National Key Basic Research Program of China，the National Natural Science Foundation of China，the Ministry of Education of the People's Republic of China，the Fundamental Research Funds for the Central Universities of China
文摘This paper discussed the differences of context-aware service between the cloud computing environment and the traditional service system.Given the above differences,the paper subsequently analyzed the changes of context-aware service during preparation,organization and delivery,as well as the resulting changes in service acceptance of consumers.Because of these changes,the context-aware service modes in the cloud computing environment change are intelligent,immersive,highly interactive,and real-time.According to active and responded service,and authorization and non-authorized service,the paper drew a case diagram of context-aware service in Unified Modeling Language(UML) and established four categories of context-aware service modes.
基金Supported by the National Grand Fundamental Research 973 Program of China under Grant No. 2009CB320504the National High Technology Development 863 Program of China under Grant No.2007AA01Z206 and No.2009AA01Z210the EU FP7 Project EFIPSANS (INFSO-ICT-215549)
文摘Autonomic networking is one of the hot research topics in the research area of future network architectures.In this paper, we introduce context-aware and autonomic attributes into DiffServ QoS framework, and propose a novel autonomic packet marking(APM) algorithm.In the proposed autonomic QoS framework, APM is capable of collecting various QoS related contexts, and adaptively adjusting its behavior to provide better QoS guarantee according to users' requirements and network conditions.Simulation results show that APM provides better performance than traditional packet marker, and significantly improves user's quality of experience.
基金supported in partby the National Natural Science Foundation of China under Grants No. 70972048,No. 71071140,No. 71272076,No. 71201011,No. 51108209,No. 60903014Shanghai Philosophy,Social Science Funds for Youth under Grant No. 2008EZH002
文摘With the development of communication and ubiquitous computing technologies, context-aware services, which acquire contextual information of users and environment, have become critical applications providing customization in mobile commerce. Meanwhile, tourism has attracted increasing attention as a high value-added service and a hot academic topic. However, the research on how to provide tour services based on context-aware services is in fact still at an early stage, limited to concept elaboration, service framework discussion, prototype system development etc. In this paper, we summarized the previous researches on context-aware services to establish the research foundation, put forward a way of analyzing a tour planning problem with a modified model of Traveling Salesman Problem （TSP） and Vehicle Routing Problem （VRP）, and we applied an innovated Resource Constrain Project Scheduling Problem （RCPSP） mathematical model to solve the tour planning problem based on context information. The simulation under branch and bound algoritban evaluated the validity of our solution.
基金supported by the The Ministry of Knowledge Economy,Korea,the ITRC(Information Technology Research Center)support program(ⅡTA-2009-(C1090-0902-0007))
文摘In recent years, several researchers have applied workflow technologies for service automation on ubiquitous compating environments. However, most context-aware workflows do not offer a method to compose several workflows in order to get mare large-scale or complicated workflow. They only provide a simple workflow model, not a composite workflow model. In this paper, the autorhs propose a context-aware workflow model to support composite workflows by expanding the patterns of the existing context-aware wrY：flows, which support the basic woddlow patterns. The suggested workflow model of. fers composite workflow patterns for a context-aware workflow, which consists of various flow patterns, such as simple, split, parallel flows, and subflow. With the suggested model, the model can easily reuse few of existing workflows to make a new workflow. As a result, it can save the development efforts and time of context-aware workflows and increase the workflow reusability. Therefore, the suggested model is expected to make it easy to develop applications related to context-aware workflow services on ubiquitous computing environments.
文摘Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the continual exchange of vehicle motion-state information, such as position, speed, and heading, which enables each vehicle to track its neighboring vehicles in real time. This work presents a context-aware adaptive beaconing scheme that dynamically adapts the beaconing repetition rate based on an estimated channel load and the danger severity of the interactions among vehicles. The safety, efficiency, and scalability of the new scheme is evaluated by simulating vehicle collisions caused by inattentive drivers under various road traffic densities. Simulation results show that the new scheme is more efficient and scalable, and is able to improve safety better than the existing non-adaptive and adaptive rate schemes.
文摘The digital technologies that run based on users’content provide a platform for users to help air their opinions on various aspects of a particular subject or product.The recommendation agents play a crucial role in personalizing the needs of individual users.Therefore,it is essential to improve the user experience.The recommender system focuses on recommending a set of items to a user to help the decision-making process and is prevalent across e-commerce and media websites.In Context-Aware Recommender Systems(CARS),several influential and contextual variables are identified to provide an effective recommendation.A substantial trade-off is applied in context to achieve the proper accuracy and coverage required for a collaborative recommendation.The CARS will generate more recommendations utilizing adapting them to a certain contextual situation of users.However,the key issue is how contextual information is used to create good and intelligent recommender systems.This paper proposes an Artificial Neural Network(ANN)to achieve contextual recommendations based on usergenerated reviews.The ability of ANNs to learn events and make decisions based on similar events makes it effective for personalized recommendations in CARS.Thus,the most appropriate contexts in which a user should choose an item or service are achieved.This work converts every label set into a Multi-Label Classification(MLC)problem to enhance recommendations.Experimental results show that the proposed ANN performs better in the Binary Relevance(BR)Instance-Based Classifier,the BR Decision Tree,and the Multi-label SVM for Trip Advisor and LDOS-CoMoDa Dataset.Furthermore,the accuracy of the proposed ANN achieves better results by 1.1%to 6.1%compared to other existing methods.
基金Supported by the National Natural Science Foundation of China(61373040,61173137)the Ph.D.Programs Foundation of Ministry of Education of China(20120141110002)the Key Project of Natural Science Foundation of Hubei Province(2010CDA004)
文摘Opportunistic networking-forwarding messages in a disconnected mobile ad hoc network via any encountered nodes offers a new mechanism for exploiting the mobile devices that many users already carry. However, forwarding messages in such a network is trapped by many particular challenges, and some protocols have contributed to solve them partly. In this paper, we propose a Context-Aware Adaptive opportunistic Routing algorithm（CAAR）. The algorithm firstly predicts the approximate location and orientation of the destination node by using its movement key positions and historical communication records, and then calculates the best neighbor for the next hop by using location and velocity of neighbors. In the unpredictable cases, forwarding messages will be delivered to the more capable forwarding nodes or wait for another transmission while the capable node does not exist in the neighborhood. The proposed algorithm takes the movement pattern into consideration and can adapt different network topologies and movements. The experiment results show that the proposed routing algorithm outperforms the epidemic forwarding（EF） and the prophet forwarding（PF） in packet delivery ratio while ensuring low bandwidth overhead.
基金supported by the National Natural Science Foundation of China (Nos.61373015,61300052, 41301047)the Priority Academic Program Development of Jiangsu Higher Education Institutionsthe Important National Science and Technology Specific Project(No. BA2013049)
文摘In many wireless sensor networks(WSNs)applications,the preservation of source-location privacy plays a critical role in concealing context information,otherwise the monitored entities or subjects may be put in danger.Many traditional solutions have been proposed based on the creation of random routes,such as random walk and fake sources approach,which will lead to serious packet delay and high energy consumption.Instead of applying the routing in a blind way,this article proposes a novel solution for source location privacy in WSNs by utilizing sensor ability of perceiving the presence a mobile attacker nearby,for patient attackers in particular to increase the safety period and decrease the data delivery delay.The proposed strategy forms an intelligent silent zone(ISZ)by sacrificing only a minority of sensor nodes to entice patient attackers away from real packet routing path.The analysis and simulation results show that the proposed scheme,besides providing source location privacy energy efficiently,can significantly reduce real event reporting latency compared with the existing approaches.
基金Supported by the National Key Research and Development Plan(2016YFB1001200)the National Natural Science Foundation of China(U1435220,61232013)
文摘In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to analyze and describe the relationships between animation data.Second,a novel context model which is able to keep the context-awareness was proposed to facilitate data organization and storage.In our context model,all the main animation elements in a scene are operated as a whole.Then sketch is utilized as the main interactive method to describe the relationships between animation data,edit the context model and make some other user operations.Finally,a context-aware computer animation data description system based on sketch is generated and it also works well in animation generation process.
文摘Recent years have witnessed the expeditious evolution of intelligentsmart devices and autonomous software technologies with the expandeddomains of computing from workplaces to smart computing in everydayroutine life activities. This trend has been rapidly advancing towards the newgeneration of systems where smart devices play vital roles in acting intelligently on behalf of the users. Context-awareness has emerged from the pervasive computing paradigm. Context-aware systems have the ability to acquirecontextual information from the surrounding environment autonomously,perform reasoning on it, and then adapt their behaviors accordingly. With theproliferation of context-aware systems and smart sensors, real-time monitoring of environmental situations (context) has become quite trivial. However,it is often challenging because the imperfect nature of context can cause theinconsistent behavior of the system. In this paper, we propose a contextaware intelligent decision support formalism to assist cognitively impairedpeople in managing their routine life activities. For this, we present a semanticknowledge-based framework to contextualize the information from the environment using the protégé ontology editor and Semantic Web Rule Language(SWRL) rules. The set of contextualized information and the set of rulesacquired from the ontology can be used to model Context-aware Multi-AgentSystems (CMAS) in order to autonomously plan all activities of the users andnotify users to act accordingly. To illustrate the use of the proposed formalism,we model a case study of Mild Cognitive Impaired (MCI) patients usingColored Petri Nets (CPN) to show the reasoning process on how the contextaware agents collaboratively plan activities on the user’s behalf and validatethe correctness properties of the system.
基金supported by the NationalBasic Research Program of China(973 Program)under Grants No.2011CB302506,No.2011CB302704,No.2012CB315802the National Key Technologies Research and Development Program of China"Research on theMobile Community Cultural Service Aggregation Supporting Technology"under Grant No.2012BAH94F02+5 种基金the Novel Mobile ServiceControl Network Architecture and Key Technologies under Grant No.2010ZX03004001-01the National High Technical Researchand Development Program of China(863 Program)under Grant No.2013AA102301the National Natural Science Foundation of Chinaunder Grants No.61003067,No.61171102,No.61001118,No.61132001Program for NewCentury Excellent Talents in University underGrant No.NCET-11-0592the Project of NewGeneration Broadband Wireless Network under Grant No.2011ZX03002-002-01the Beijing Nova Program under Grant No.2008B50
文摘Service-Oriented Communication(SOC)is a key research issue to enable media communications using the Service-Oriented Architecture(SOA).Motivated by the necessity to guarantee the service quality of our webbased multimedia conferencing system,we present a Comprehensively Context-Aware(CoCA)approach in this paper.One major problem in the existing end-to-end Quality of Service(QoS)management solutions is that they analyse and exploit the relationships between the QoS metrics and corresponding contexts in an isolated manner.In this paper,we propose a novel approach to leveraging such relationships in a comprehensive manner based on Bayesian networks and the fuzzy set theory.This approach includes three phases:1)information feedback and training,2)QoS-to-context mapping,and3)optimal context adaption.We implement the proposed CoCA in the real multimedia conferencing system and compare its performance with the existing bandwidth aware and playback buffer aware schemes.Experimental results show that the proposed CoCA outperforms the competing approaches in improving the average video Peak Signal-to-Noise Ratio(PSNR).It also exhibits good performance in preventing the playback buffer starvation.
基金Supported by the School-Enterprise Project of Nokia Research Center(Beijing)
文摘The recommendation system can efficiently solve the information overload in mobile Internet. Thus, how to effectively utilize context information to improve the accuracy of recommendation becomes the research focus in the field. This article puts forward a novel approach to realize the context-aware recommendation in mobile environments. It first gets users’ interest resonance with a hash-based interest resonance mining algorithm. Then, it calculates the association degree between the user and the item and then predicts the user’s rating on the item. Finally, it comprehensively figures out the recommending index. Moreover, this article also designs a personal recommendation model for the users and provides relevant decision-making coefficients. Experiments have demonstrated that our approach is superior to the traditional ones （RMP, RSTE, MD and BBBs） in both performance and efficiency.
基金the National High Technology Research and Development Program(863)of China(No.2012AA02A601)the National Science and Technology Major Project of China(No.2013ZX03005012)
文摘Communication or the lack of it has been complained to be a major contributor to medical errors in healthcare.To enhance communication in hospital,diverse communication mechanisms are proposed.However,human directed communication in a complex clinical setting in which many people play diverse roles and need to collaborate in many parallel tasks is always in chaos and inefficient.Context-aware communication which can help target who should be communicated and what information should be provided for different scenarios has the potential to improve the communication in hospital.This paper proposes a flexible,automated and asynchronous context-aware medical instant message(IM)middleware which support dispatch,forward and routing different message to the right person in the right time based on the context information.A prototype of this IM communication middleware was implemented in real clinical setting for evaluation.The preliminary results demonstrate its novel features and clinical feasibility.
