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Research Collection School Of Computing and Information Systems

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Full-Text Articles in Computer Sciences

Revisiting Risk-Sensitive Mdps: New Algorithms And Results, Ping Hou, William Yeoh, Pradeep Reddy Varakantham Jun 2014

Revisiting Risk-Sensitive Mdps: New Algorithms And Results, Ping Hou, William Yeoh, Pradeep Reddy Varakantham

Research Collection School Of Computing and Information Systems

While Markov Decision Processes (MDPs) have been shown to be effective models for planning under uncertainty, theobjective to minimize the expected cumulative cost is inappropriate for high-stake planning problems. As such, Yu, Lin, and Yan (1998) introduced the Risk-Sensitive MDP (RSMDP) model, where the objective is to find a policy that maximizes the probability that the cumulative cost is within some user-defined cost threshold. In this paper, we revisit this problem and introduce new algorithms that are based on classical techniques, such as depth-first search and dynamic programming, and a recently introduced technique called Topological Value Iteration (TVI). We demonstrate …


Boat: An Experimental Platform For Researchers To Comparatively And Reproducibly Evaluate Bug Localization Techniques, Xinyu Wang, David Lo, Xin Xia, Xingen Wang, Pavneet Singh Kochhar, Yuan Tian, Xiaohu Yang, Shanping Li, Jianling Sun, Bo Zhou Jun 2014

Boat: An Experimental Platform For Researchers To Comparatively And Reproducibly Evaluate Bug Localization Techniques, Xinyu Wang, David Lo, Xin Xia, Xingen Wang, Pavneet Singh Kochhar, Yuan Tian, Xiaohu Yang, Shanping Li, Jianling Sun, Bo Zhou

Research Collection School Of Computing and Information Systems

Bug localization refers to the process of identifying source code files that contain defects from descriptions of these defects which are typically contained in bug reports. There have been many bug localization techniques proposed in the literature. However, often it is hard to compare these techniques since different evaluation datasets are used. At times the datasets are not made publicly available and thus it is difficult to reproduce reported results. Furthermore, some techniques are only evaluated on small datasets and thus it is not clear whether the results are generalizable. Thus, there is a need for a platform that allows …


Sewordsim: Software-Specific Word Similarity Database, Yuan Tian, David Lo, Julia Lawall Jun 2014

Sewordsim: Software-Specific Word Similarity Database, Yuan Tian, David Lo, Julia Lawall

Research Collection School Of Computing and Information Systems

Measuring the similarity of words is important in accurately representing and comparing documents, and thus improves the results of many natural language processing (NLP) tasks. The NLP community has proposed various measurements based on WordNet, a lexical database that contains relationships between many pairs of words. Recently, a number of techniques have been proposed to address software engineering issues such as code search and fault localization that require understanding natural language documents, and a measure of word similarity could improve their results. However, WordNet only contains information about words senses in general-purpose conversation, which often differ from word senses in …


Global Immutable Region Computation, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang Jun 2014

Global Immutable Region Computation, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

A top-k query shortlists the k records in a dataset that best match the user's preferences. To indicate her preferences, the user typically determines a numeric weight for each data dimension (i.e., attribute). We refer to these weights collectively as the query vector. Based on this vector, each data record is implicitly mapped to a score value (via a weighted sum function). The records with the k largest scores are reported as the result. In this paper we propose an auxiliary feature to standard top-k query processing. Specifically, we compute the maximal locus within which the query vector incurs no …


Evolving An Information Systems Capstone Course To Align With The Fast Changing Singapore Marketplace, Chris Boesch, Benjamin Kok Siew Gan Jun 2014

Evolving An Information Systems Capstone Course To Align With The Fast Changing Singapore Marketplace, Chris Boesch, Benjamin Kok Siew Gan

Research Collection School Of Computing and Information Systems

Every year, around fifty-five undergraduate teams of four to six students are required to complete a capstone course for the School of Information Systems at Singapore Management University. Each team spends approximately five months working with an industry sponsor using the latest tools and techniques. Students actively learn by implementing the system to solve a real world problem. In addition to delivering value to the local sponsor, our students learn specialized skills currently needed in the marketplace, which might not yet be incorporated into electives and core courses. In this paper, we discuss the tradeoffs of providing students and project …


Graph-Based Semi-Supervised Learning: Realizing Pointwise Smoothness Probabilistically, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw Jun 2014

Graph-Based Semi-Supervised Learning: Realizing Pointwise Smoothness Probabilistically, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw

Research Collection School Of Computing and Information Systems

As the central notion in semi-supervised learning, smoothness is often realized on a graph representation of the data. In this paper, we study two complementary dimensions of smoothness: its pointwise nature and probabilistic modeling. While no existing graph-based work exploits them in conjunction, we encompass both in a novel framework of Probabilistic Graph-based Pointwise Smoothness (PGP), building upon two foundational models of data closeness and label coupling. This new form of smoothness axiomatizes a set of probability constraints, which ultimately enables class prediction. Theoretically, we provide an error and robustness analysis of PGP. Empirically, we conduct extensive experiments to show …


Ar-Miner: Mining Informative Reviews For Developers From Mobile App Marketplace, Ning Chen, Jialiu Lin, Steven C. H. Hoi, Xiaokui Xiao, Boshen Zhang Jun 2014

Ar-Miner: Mining Informative Reviews For Developers From Mobile App Marketplace, Ning Chen, Jialiu Lin, Steven C. H. Hoi, Xiaokui Xiao, Boshen Zhang

Research Collection School Of Computing and Information Systems

With the popularity of smartphones and mobile devices, mobile application (a.k.a. “app”) markets have been growing exponentially in terms of number of users and downloads. App developers spend considerable effort on collecting and exploiting user feedback to improve user satisfaction, but suffer from the absence of effective user review analytics tools. To facilitate mobile app developers discover the most “informative” user reviews from a large and rapidly increasing pool of user reviews, we present “AR-Miner” — a novel computational framework for App Review Mining, which performs comprehensive analytics from raw user reviews by (i) first extracting informative user reviews by …


Version History, Similar Report, And Structure: Putting Them Together For Improved Bug Localization, Shaowei Wang, David Lo Jun 2014

Version History, Similar Report, And Structure: Putting Them Together For Improved Bug Localization, Shaowei Wang, David Lo

Research Collection School Of Computing and Information Systems

During the evolution of a software system, a large number of bug reports are submitted. Locating the source code files that need to be fixed to resolve the bugs is a challenging problem. Thus, there is a need for a technique that can automatically figure out these buggy files. A number of bug localization solutions that take in a bug report and output a ranked list of files sorted based on their likelihood to be buggy have been proposed in the literature. However, the accuracy of these tools still need to be improved. In this paper, to address this need, …


Towards More Accurate Content Categorization Of Api Discussions, Bo Zhou, Xin Xia, David Lo, Cong Tian, Xinyu Wang Jun 2014

Towards More Accurate Content Categorization Of Api Discussions, Bo Zhou, Xin Xia, David Lo, Cong Tian, Xinyu Wang

Research Collection School Of Computing and Information Systems

Nowadays, software developers often discuss the usage of various APIs in online forums. Automatically assigning pre-defined semantic categorizes to API discussions in these forums could help manage the data in online forums, and assist developers to search for useful information. We refer to this process as content categorization of API discussions. To solve this problem, Hou and Mo proposed the usage of naive Bayes multinomial, which is an effective classification algorithm. In this paper, we propose a Cache-bAsed compoSitE algorithm, short formed as CASE, to automatically categorize API discussions. Considering that the content of an API discussion contains both textual …


Condensing Class Diagrams By Analyzing Design And Network Metrics Using Optimistic Classification, Ferdian Thung, David Lo, Mohd Hafeez Osman, Michel R.V. Chaudron Jun 2014

Condensing Class Diagrams By Analyzing Design And Network Metrics Using Optimistic Classification, Ferdian Thung, David Lo, Mohd Hafeez Osman, Michel R.V. Chaudron

Research Collection School Of Computing and Information Systems

A class diagram of a software system enhances our ability to understand software design. However, this diagram is often unavailable. Developers usually reconstruct the diagram by reverse engineering it from source code. Unfortunately, the resultant diagram is often very cluttered; making it difficult to learn anything valuable from it. Thus, it would be very beneficial if we are able to condense the reverse- engineered class diagram to contain only the important classes depicting the overall design of a software system. Such diagram would make program understanding much easier. A class can be important, for example, if its removal would break …


Cross-Language Bug Localization, Xin Xia, David Lo, Xingen Wang, Chenyi Zhang, Xinyu Wang Jun 2014

Cross-Language Bug Localization, Xin Xia, David Lo, Xingen Wang, Chenyi Zhang, Xinyu Wang

Research Collection School Of Computing and Information Systems

Bug localization refers to the process of identifying source code files that contain defects from textual descriptions in bug reports. Existing bug localization techniques work on the assumption that bug reports, and identifiers and comments in source code files, are written in the same language (i.e., English). However, software users from non-English speaking countries (e.g., China) often use their native languages (e.g., Chinese) to write bug reports. For this setting, existing studies on bug localization would not work as the terms that appear in the bug reports do not appear in the source code. We refer to this problem as …


Socio-Physical Analytics: Challenges & Opportunities, Archan Misra, Kasthuri Jayarajah, Shriguru Nayak, Philips Kokoh Prasetyo, Ee-Peng Lim Jun 2014

Socio-Physical Analytics: Challenges & Opportunities, Archan Misra, Kasthuri Jayarajah, Shriguru Nayak, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we argue for expanded research into an area called Socio-Physical Analytics, that focuses on combining the behavioral insight gained from mobile-sensing based monitoring of physical behavior with the inter-personal relationships and preferences deduced from online social networks. We highlight some of the research challenges in combining these heterogeneous data sources and then describe some examples of our ongoing work (based on real-world data being collected at SMU) that illustrate two aspects of socio-physical analytics: (a) how additional demographic and online analytics based attributes can potentially provide better insights into the preferences and behaviors of individuals or groups …


Paths Of Influence For Innovations In Financial Is And Technology Ecosystems, Jun Liu, Robert John Kauffman, Dan Ma Jun 2014

Paths Of Influence For Innovations In Financial Is And Technology Ecosystems, Jun Liu, Robert John Kauffman, Dan Ma

Research Collection School Of Computing and Information Systems

Predicting technological innovations in financial information systems (IS) and technology ecosystems has been challenging for technology forecasters and industry analysts due to their underlying complexity. Technology-based financial innovations over the past four decades, such as programmed trading in the 1980s, risk-adjusted return on capital-based financial risk management systems in the 1990s, high-frequency trading and Internet banking in 2000s, and now mobile payments in the 2010s, have all led to transformations in the financial services industry. What basis can be identified to predict such new innovations? And what areas of financial services will they affect? This study applies the technology ecosystem …


Technology Investment Decision-Making Under Uncertainty In Mobile Payment Systems, Robert J. Kauffman, Jun Liu, Dan Ma Jun 2014

Technology Investment Decision-Making Under Uncertainty In Mobile Payment Systems, Robert J. Kauffman, Jun Liu, Dan Ma

Research Collection School Of Computing and Information Systems

Innovations in the mobile payments industry provide potentially profitable investment opportunities for banks. Nonetheless, significant uncertainties are associated with decision-making for this IT investment context, regarding future market conditions, technology standards, and consumer and merchant responses, especially their willingness to adopt. As a result, traditional capital budgeting approach and experienced intuition have not been effective. We develop a model to support a bank’s mobile payment systems adoption decision-making at the firm level when it faces endogenous technological risks and exogenous market conditions. This study applies theory and modeling from financial economics for decision-making under uncertainty to investments in m-payment systems …


Permission Based Android Security: Issues And Countermeasures, Zheran Fang, Weili Han, Yingjiu Li Jun 2014

Permission Based Android Security: Issues And Countermeasures, Zheran Fang, Weili Han, Yingjiu Li

Research Collection School Of Computing and Information Systems

Android security has been a hot spot recently in both academic research and public concerns due to numerous instances of security attacks and privacy leakage on Android platform. Android security has been built upon a permission based mechanism which restricts accesses of third-party Android applications to critical resources on an Android device. Such permission based mechanism is widely criticized for its coarse-grained control of application permissions and difficult management of permissions by developers, marketers, and end-users. In this paper, we investigate the arising issues in Android security, including coarse granularity of permissions, incompetent permission administration, insufficient permission documentation, over-claim of …


Fully Secure Key-Policy Attribute-Based Encryption With Constant-Size Ciphertexts And Fast Decryption, Junzuo Lai, Robert H. Deng, Yingjiu Li, Jian Weng Jun 2014

Fully Secure Key-Policy Attribute-Based Encryption With Constant-Size Ciphertexts And Fast Decryption, Junzuo Lai, Robert H. Deng, Yingjiu Li, Jian Weng

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE), introduced by Sahai and Waters, is a promising cryptographic primitive, which has been widely applied to implement fine-grained access control system for encrypted data. In its key-policy flavor, attribute sets are used to annotate ciphertexts and secret keys are associated with access structures that specify which ciphertexts a user is entitled to decrypt. In most existing key-policy attribute-based encryption (KP-ABE) constructions, the size of the ciphertext is proportional to the number of attributes associated with it and the decryption cost is proportional to the number of attributes used during decryption. In this paper, we present a new …


It's Not A Bug, It's A Feature: Does Misclassification Affect Bug Localization?, Pavneet Singh Kocchar, Tien-Duy B. Le, David Lo Jun 2014

It's Not A Bug, It's A Feature: Does Misclassification Affect Bug Localization?, Pavneet Singh Kocchar, Tien-Duy B. Le, David Lo

Research Collection School Of Computing and Information Systems

Bug localization refers to the task of automatically processing bug reports to locate source code files that are responsible for the bugs. Many bug localization techniques have been proposed in the literature. These techniques are often evaluated on issue reports that are marked as bugs by their reporters in issue tracking systems. However, recent findings by Herzig et al. find that a substantial number of issue reports marked as bugs, are not bugs but other kinds of issues like refactorings, request for enhancement, documentation changes, test case creation, and so on. Herzig et al. report that these misclassifications affect bug …


On Modeling Brand Preferences In Item Adoptions, Minh Duc Luu, Ee Peng Lim, Freddy Chong-Tat Chua Jun 2014

On Modeling Brand Preferences In Item Adoptions, Minh Duc Luu, Ee Peng Lim, Freddy Chong-Tat Chua

Research Collection School Of Computing and Information Systems

In marketing and advertising, developing and managingbrands value represent the core activities performedby companies. Successful brands attract buyers andadopters, which in turn increase the companies’ value.Given a set of user-item adoption data, can we inferbrand effects from users adopting items? To answerthis question, we develop the Brand Item Topic Model(BITM) that incorporates users’ brand preferences inthe process of item adoption by the users. We evaluateour model using synthetic and two real world datasetsagainst baseline models which do not consider brand effects.The results show that BITM can determine userswho demonstrate brand preferences and predict itemadoptions more accurately.


Hydra: Large-Scale Social Identity Linkage Via Heterogeneous Behavior Modeling, Siyuan Liu, Shuhui Wang, Feida Zhu, Jinbo Zhang, Ramayya Krishnan Jun 2014

Hydra: Large-Scale Social Identity Linkage Via Heterogeneous Behavior Modeling, Siyuan Liu, Shuhui Wang, Feida Zhu, Jinbo Zhang, Ramayya Krishnan

Research Collection School Of Computing and Information Systems

We study the problem of large-scale social identity linkage across different social media platforms, which is of critical importance to business intelligence by gaining from social data a deeper understanding and more accurate profiling of users. This paper proposes HYDRA, a solution framework which consists of three key steps: (I) modeling heterogeneous behavior by long-term behavior distribution analysis and multi-resolution temporal information matching; (II) constructing structural consistency graph to measure the high-order structure consistency on users' core social structures across different platforms; and (III) learning the mapping function by multi-objective optimization composed of both the supervised learning on pair-wise ID …


The Case For Human-Centric Personal Analytics, Youngki Lee, Rajesh Krishna Balan Jun 2014

The Case For Human-Centric Personal Analytics, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

The rich context provided by smartphones has enabled many new context-aware applications. However, these applications still need to provide their own mechanisms to interpret low-level sensing data and generate high-level user states. In this paper, we propose the idea of building a personal analytics (PA) layer that will use inputs from multiple lower layer sources, such as sensor data (accelerometers, gyroscopes, etc.), phone data (call logs, application activity, etc.), and online sources (Twitter, Facebook posts, etc.) to generate high-level user contextual states (such as emotions, preferences, and engagements). Developers can then use the PA layer to easily build a new …


Optimal Performance Trade-Offs In Mac For Wireless Sensor Networks Powered By Heterogeneous Ambient Energy Harvesting, Jin Yunye, Hwee-Pink Tan Jun 2014

Optimal Performance Trade-Offs In Mac For Wireless Sensor Networks Powered By Heterogeneous Ambient Energy Harvesting, Jin Yunye, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

In wireless sensor networks powered by ambient energy harvesting (WSNs-HEAP), sensor nodes' energy harvesting rates are spatially heterogeneous and temporally variant, which impose difficulties for medium access control (MAC). In this paper, we first derive the necessary conditions under which channel utilization and fairness are optimal in a WSN-HEAP, respectively. Based on the analysis, we propose an earliest deadline first (EDF) polling MAC protocol, which regulates transmission sequence of the sensor nodes based on the spatially heterogeneous energy harvesting rates. It also mitigates temporal variations in energy harvesting rates by a prediction and update mechanism. Simulation results verify the performance …


Bootstrapping Simulation-Based Algorithms With A Suboptimal Policy, Nguyen T., Silander T., Lee W., Tze-Yun Leong Jun 2014

Bootstrapping Simulation-Based Algorithms With A Suboptimal Policy, Nguyen T., Silander T., Lee W., Tze-Yun Leong

Research Collection School Of Computing and Information Systems

Finding optimal policies for Markov Decision Processes with large state spaces is in general intractable. Nonetheless, simulation-based algorithms inspired by Sparse Sampling (SS) such as Upper Confidence Bound applied in Trees (UCT) and Forward Search Sparse Sampling (FSSS) have been shown to perform reasonably well in both theory and practice, despite the high computational demand. To improve the efficiency of these algorithms, we adopt a simple enhancement technique with a heuristic policy to speed up the selection of optimal actions. The general method, called Aux, augments the look-ahead tree with auxiliary arms that are evaluated by the heuristic policy. In …


Online Community Transition Detection, Biying Tan, Feida Zhu, Qiang Qu, Siyuan Liu Jun 2014

Online Community Transition Detection, Biying Tan, Feida Zhu, Qiang Qu, Siyuan Liu

Research Collection School Of Computing and Information Systems

Mining user behavior patterns in social networks is of great importance in user behavior analysis, targeted marketing, churn prediction and other applications. However, less effort has been made to study the evolution of user behavior in social communities. In particular, users join and leave communities over time. How to automatically detect the online community transitions of individual users is a research problem of immense practical value yet with great technical challenges. In this paper, we propose an algorithm based on the Minimum Description Length (MDL) principle to trace the evolution of community transition of individual users, adaptive to the noisy …


Flow In Gaming: Literature Synthesis And Framework Development, Fiona Fui-Hoon Nah, B. Eschenbrenner, Q. Zeng, V. Telaprolu, S. Sepehr Jun 2014

Flow In Gaming: Literature Synthesis And Framework Development, Fiona Fui-Hoon Nah, B. Eschenbrenner, Q. Zeng, V. Telaprolu, S. Sepehr

Research Collection School Of Computing and Information Systems

Flow, a state of optimal experience where one is completely absorbed and immersed in an activity, is an important phenomenon for studying and designing games. In this article, we synthesise the literature on flow in gaming to discern existing research streams, and identify the antecedents, dimensions, and outcomes of flow which are then integrated into a framework. Based on the findings, we provide suggestions for game design elements that practitioners, such as game designers, may find useful for creating or inducing flow in gaming. We also discuss implications for research and practice as well as provide suggestions for future research.


Information Systems User Competency: A Conceptual Foundation, B. Eschenbrenner, Fiona Fui-Hoon Nah Jun 2014

Information Systems User Competency: A Conceptual Foundation, B. Eschenbrenner, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Research has identified a variety of factors that influence people’s intentions to use IS and their degree of IS use. However, what has not been well understood are the characteristics of competent IS users who are proficient in using IS and are able to achieve quality IS usage. Considering that improving IS users’ abilities to more efficiently and effectively use IS has always been and remains a challenge, research that provides a comprehensive view of the characteristics associated with competent IS users is warranted. This paper addresses this research question by proposing a conceptual foundation for IS user competency. Based …


Institutional Boundaries And Trust Of Virtual Teams In Collaborative Design: An Experimental Study In A Virtual World Environment, Shu Z. Schiller, Brian Mennecke, Fiona Fui-Hoon Nah, Andy Luse Jun 2014

Institutional Boundaries And Trust Of Virtual Teams In Collaborative Design: An Experimental Study In A Virtual World Environment, Shu Z. Schiller, Brian Mennecke, Fiona Fui-Hoon Nah, Andy Luse

Research Collection School Of Computing and Information Systems

Members of virtual teams often collaborate within and across institutional boundaries. This research investigates the effects of boundary spanning conditions on the development of team trust and team satisfaction. Two hundred and eighty-two participants carried out a collaborative design task over several weeks in a virtual world, Second Life. Multigroup structural equation modeling was used to examine our research model, which compares individual level measurement between two boundary spanning team conditions. The results indicate that trusting beliefs have a positive impact on team trust, which in turn, influences team satisfaction. Further, we found that, compared to cross-boundary teams, within-boundary teams …


Gamification Of Education: A Review Of Literature, Fiona Fui-Hoon Nah, Qing Zeng, Venkata R. Telaprolu, Abhishek Padmanabhuni Ayyappa, Brenda Eschenbrenner Jun 2014

Gamification Of Education: A Review Of Literature, Fiona Fui-Hoon Nah, Qing Zeng, Venkata R. Telaprolu, Abhishek Padmanabhuni Ayyappa, Brenda Eschenbrenner

Research Collection School Of Computing and Information Systems

We synthesized the literature on gamification of education by conducting a review of the literature on gamification in the educational and learning context. Based on our review, we identified several game design elements that are used in education. These game design elements include points, levels/stages, badges, leaderboards, prizes, progress bars, storyline, and feedback. We provided examples from the literature to illustrate the application of gamification in the educational context.


Joint Virtual Machine And Bandwidth Allocation In Software Defined Network (Sdn) And Cloud Computing Environments, Jonathan David Chase, Rakpong Kaewpuang, Wen Yonggang, Dusit Niyato Jun 2014

Joint Virtual Machine And Bandwidth Allocation In Software Defined Network (Sdn) And Cloud Computing Environments, Jonathan David Chase, Rakpong Kaewpuang, Wen Yonggang, Dusit Niyato

Research Collection School Of Computing and Information Systems

Cloud computing provides users with great flexibility when provisioning resources, with cloud providers offering a choice of reservation and on-demand purchasing options. Reservation plans offer cheaper prices, but must be chosen in advance, and therefore must be appropriate to users' requirements. If demand is uncertain, the reservation plan may not be sufficient and on-demand resources have to be provisioned. Previous work focused on optimally placing virtual machines with cloud providers to minimize total cost. However, many applications require large amounts of network bandwidth. Therefore, considering only virtual machines offers an incomplete view of the system. Exploiting recent developments in software …


An Air Index For Spatial Query Processing In Road Networks, Weiwei Sun, Chunan Chen, Baihua Zheng, Chong Chen, Peng Liu Jun 2014

An Air Index For Spatial Query Processing In Road Networks, Weiwei Sun, Chunan Chen, Baihua Zheng, Chong Chen, Peng Liu

Research Collection School Of Computing and Information Systems

Spatial queries such as range query and kNN query in road networks have received a growing number of attention in real life. Considering the large population of the users and the high overhead of network distance computation, it is extremely important to guarantee the efficiency and scalability of query processing. Motivated by the scalable and secure properties of wireless broadcast model, this paper presents an air index called Network Partition Index (NPI) to support efficient spatial query processing in road networks via wireless broadcast. The main idea is to partition the road network into a number of regions and then …


A Hybrid Model Of Connectors In Cyber-Physical Systems, Xiaohong Chen, Jun Sun, Meng Sun Sun May 2014

A Hybrid Model Of Connectors In Cyber-Physical Systems, Xiaohong Chen, Jun Sun, Meng Sun Sun

Research Collection School Of Computing and Information Systems

Compositional coordination models and languages play an important role in cyber-physical systems (CPSs). In this paper, we introduce a formal model for describing hybrid behaviors of connectors in CPSs. We extend the constraint automata model, which is used as the semantic model for the exogenous channel-based coordination language Reo, to capture the dynamic behavior of connectors in CPSs where the discrete and continuous dynamics co-exist and interact with each other. In addition to the formalism, we also provide a theoretical compositional approach for constructing the product automata for a Reo circuit, which is typically obtained by composing several primitive connectors …