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Articles 5311 - 5340 of 8479
Full-Text Articles in Computer Sciences
Modelling Cascades Over Time In Microblogs, Xie Wei, Feida Zhu, Siyuan Liu, Ke Wang
Modelling Cascades Over Time In Microblogs, Xie Wei, Feida Zhu, Siyuan Liu, Ke Wang
Research Collection School Of Computing and Information Systems
One of the most important features of microblogging services such as Twitter is how easy it is to re-share a piece of information across the network through various user connections, forming what we call a "cascade". Business applications such as viral marketing have driven a tremendous amount of research effort predicting whether a certain cascade will go viral. Yet the rarity of viral cascades in real data poses a challenge to all existing prediction methods. One solution is to simulate cascades that well fit the real viral ones, which requires our ability to tell how a certain cascade grows over …
Analysis Of Aspects And Star Ratings In Consumer Reviews, Maruthi Prithivirajan, Vivian Lai, Kyong Jin Shim
Analysis Of Aspects And Star Ratings In Consumer Reviews, Maruthi Prithivirajan, Vivian Lai, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
This paper presents an analysis of star ratings in consumer reviews in Yelp, an online social platform for sharing consumer reviews about local businesses. In particular, we analyze consumer reviews about food businesses. We analyze how well or poorly the star ratings (on a scale of one star to five stars) associated with these reviews tally with the sentiment derived from the textual portion of the consumer review.
Security And Privacy Of Electronic Health Information Systems: Editorial, Elisa Bertino, Robert H. Deng, Xinyi Huang, Jianying Zhou
Security And Privacy Of Electronic Health Information Systems: Editorial, Elisa Bertino, Robert H. Deng, Xinyi Huang, Jianying Zhou
Research Collection School Of Computing and Information Systems
Digital technologies have dramatically transformed our daily lives by bringing countless conveniences and benefits. As an evolving concept, electronic health information has become the focus of attention in both academia and industry. By leveraging modern digital technologies like the internet and the cloud, electronic health information systems will be a key enabling technology in improving the quality and convenience of patient care, encouraging patient participation in their care, reducing medical errors, improving practice efficiencies, and saving time and cost. The complexity of electronic health information systems, however, raises several new security and privacy issues. It is thus critical to investigate …
Dictionary Pair Learning On Grassmann Manifolds For Image Denoising, Xianhua Zeng, Wei Bian, Wei Liu, Jialie Shen, Dacheng Tao
Dictionary Pair Learning On Grassmann Manifolds For Image Denoising, Xianhua Zeng, Wei Bian, Wei Liu, Jialie Shen, Dacheng Tao
Research Collection School Of Computing and Information Systems
Image denoising is a fundamental problem in computer vision and image processing that holds considerable practical importance for real-world applications. The traditional patch-based and sparse coding-driven image denoising methods convert 2D image patches into 1D vectors for further processing. Thus, these methods inevitably break down the inherent 2D geometric structure of natural images. To overcome this limitation pertaining to the previous image denoising methods, we propose a 2D image denoising model, namely, the dictionary pair learning (DPL) model, and we design a corresponding algorithm called the DPL on the Grassmann-manifold (DPLG) algorithm. The DPLG algorithm first learns an initial dictionary …
Where Are The Passengers? A Grid-Based Gaussian Mixture Model For Taxi Bookings, Meng-Fen Chiang, Tuan Anh Hoang, Ee-Peng Lim
Where Are The Passengers? A Grid-Based Gaussian Mixture Model For Taxi Bookings, Meng-Fen Chiang, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Taxi bookings are events where requests for taxis are made by passengers either over voice calls or mobile apps. As the demand for taxis changes with space and time, it is important to model both the space and temporal dimensions in dynamic booking data. Several applications can benefit from a good taxi booking model. These include the prediction of number of bookings at certain location and time of the day, and the detection of anomalous booking events. In this paper, we propose a Grid-based Gaussian Mixture Model (GGMM) with spatio-temporal dimensions that groups booking data into a number of spatio-temporal …
Intelligshop: Enabling Intelligent Shopping In Malls Through Location-Based Augmented Reality, Aditi Adhikari, Vincent W. Zheng, Hong Cao, Miao Lin, Yuan Fang, Kevin Chen-Chuan Chang
Intelligshop: Enabling Intelligent Shopping In Malls Through Location-Based Augmented Reality, Aditi Adhikari, Vincent W. Zheng, Hong Cao, Miao Lin, Yuan Fang, Kevin Chen-Chuan Chang
Research Collection School Of Computing and Information Systems
Shopping experience is important for both citizens and tourists. We present IntelligShop, a novel location-based augmented reality application that supports intelligent shopping experience in malls. As the key functionality, IntelligShop provides an augmented reality interface-people can simply use ubiquitous smartphones to face mall retailers, then IntelligShop will automatically recognize the retailers and fetch their online reviews from various sources (including blogs, forums and publicly accessible social media) to display on the phones. Technically, IntelligShop addresses two challenging data mining problems, including robust feature learning to support heterogeneous smartphones in localization and learning to query for automatically gathering the retailer content …
Codehow: Effective Code Search Based On Api Understanding And Extended Boolean Model (E), Fei Lv, Jian-Guang Lou, Shaowei Wang, Dongmei Zhang, Jainjun Zhao
Codehow: Effective Code Search Based On Api Understanding And Extended Boolean Model (E), Fei Lv, Jian-Guang Lou, Shaowei Wang, Dongmei Zhang, Jainjun Zhao
Research Collection School Of Computing and Information Systems
Over the years of software development, a vast amount of source code has been accumulated. Many code search tools were proposed to help programmers reuse previously-written code by performing free-text queries over a large-scale codebase. Our experience shows that the accuracy of these code search tools are often unsatisfactory. One major reason is that existing tools lack of query understanding ability. In this paper, we propose CodeHow, a code search technique that can recognize potential APIs a user query refers to. Having understood the potentially relevant APIs, CodeHow expands the query with the APIs and performs code retrieval by applying …
Automating The Performance Deviation Analysis For Multiple System Releases: An Evolutionary Study, Felipe Pinto, Uirá Kulesza, Christoph Treude
Automating The Performance Deviation Analysis For Multiple System Releases: An Evolutionary Study, Felipe Pinto, Uirá Kulesza, Christoph Treude
Research Collection School Of Computing and Information Systems
This paper presents a scenario-based approach for the evaluation of the quality attribute of performance, measured in terms of execution time (response time). The approach is implemented by a framework that uses dynamic analysis and repository mining techniques to provide an automated way for revealing potential sources of performance degradation of scenarios between releases of a software system. The approach defines four phases: (i) preparation – choosing the scenarios and preparing the target releases; (ii) dynamic analysis – determining the performance of scenarios and methods by calculating their execution time; (iii) degradation analysis – processing and comparing the results of …
Challenges In Analyzing Software Documentation In Portuguese, Christoph Treude, Carlos A. Prolo, Fernando Figueira Filho
Challenges In Analyzing Software Documentation In Portuguese, Christoph Treude, Carlos A. Prolo, Fernando Figueira Filho
Research Collection School Of Computing and Information Systems
Many tools that automatically analyze, summarize, or transform software artifacts rely on natural language processing tooling for the interpretation of natural language text produced by software developers, such as documentation, code comments, commit messages, or bug reports. Processing natural language text produced by software developers is challenging because of unique characteristics not found in other texts, such as the presence of code terms and the systematic use of incomplete sentences. In addition, texts produced by Portuguese-speaking developers mix languages since many keywords and programming concepts are referred to by their English name. In this paper, we provide empirical insights into …
A Method And System For Sentiment Classification And Emotion Classification [Us Patent 20170308523a1], Zhaoxia Wang, Rick Siow Mong Goh, Yinping Yang
A Method And System For Sentiment Classification And Emotion Classification [Us Patent 20170308523a1], Zhaoxia Wang, Rick Siow Mong Goh, Yinping Yang
Research Collection School Of Computing and Information Systems
A system and a method for classifying text messages, such as social media messages into sentiment valence categories are provided. The system comprising a module for decomposing text messages, a module for cleaning text messages, a module for producing feature data of text messages, and a module for classifying text messages into sentiment valence categories. The module for decomposing text messages is configured to: receive a text message, parse the text message into separate portions in response to parsing criteria based on sentence delimiters, wherein the separate portions are sentences, phrases and words, and rejoin at least some of the …
Using Gamification As A Collaboration Motivator For Software Development Teams: A Preliminary Framework, Flavio Steffens, Sabrina Marczak, Fernando Figueira Filho, Christoph Treude, Leif Singer, David Redmiles, Ban Al-Ani
Using Gamification As A Collaboration Motivator For Software Development Teams: A Preliminary Framework, Flavio Steffens, Sabrina Marczak, Fernando Figueira Filho, Christoph Treude, Leif Singer, David Redmiles, Ban Al-Ani
Research Collection School Of Computing and Information Systems
Gamification is the use of game elements in non-game context to engage and to motivate people to achieve goals. Its use is becoming very popular in software development organizations due to work being based upon human-centric and brain-intensive activity. This paper presents the topics of collaboration and gamification in the context of software engineering, and proposes a framework that identifies the most common collaboration issues that affect software development teams, and how to apply game elements to motivate a change on their behaviors.
Lesinn: Detecting Anomalies By Identifying Least Similar Nearest Neighbours, Guansong Pang, Kai Ming Ting, David Albrecht
Lesinn: Detecting Anomalies By Identifying Least Similar Nearest Neighbours, Guansong Pang, Kai Ming Ting, David Albrecht
Research Collection School Of Computing and Information Systems
We introduce the concept of Least Similar Nearest Neighbours (LeSiNN) and use LeSiNN to detect anomalies directly. Although there is an existing method which is a special case of LeSiNN, this paper is the first to clearly articulate the underlying concept, as far as we know. LeSiNN is the first ensemble method which works well with models trained using samples of one instance. LeSiNN has linear time complexity with respect to data size and the number of dimensions, and it is one of the few anomaly detectors which can apply directly to both numeric and categorical data sets. Our extensive …
Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik
Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik
Research Collection School Of Computing and Information Systems
Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact …
The Importance Of Being Isolated: An Empirical Study On Chromium Reviews, Subhajit Datta, Devarshi Bhatt, Manish Jain, Proshanta Sarkar, Santonu Sarkar
The Importance Of Being Isolated: An Empirical Study On Chromium Reviews, Subhajit Datta, Devarshi Bhatt, Manish Jain, Proshanta Sarkar, Santonu Sarkar
Research Collection School Of Computing and Information Systems
As large scale software development has become more collaborative, and software teams more globally distributed, several studies have explored how developer interaction influences software development outcomes. The emphasis so far has been largely on outcomes like defect count, the time to close modification requests etc. In the paper, we examine data from the Chromium project to understand how different aspects of developer discussion relate to the closure time of reviews. On the basis of analyzing reviews discussed by 2000+ developers, our results indicate that quicker closure of reviews owned by a developer relates to higher reception of information and insights …
Towards Automatic Generation Of Security-Centric Descriptions For Android Apps, Mu Zhang, Yue Duan, Qian Feng, Heng Yin
Towards Automatic Generation Of Security-Centric Descriptions For Android Apps, Mu Zhang, Yue Duan, Qian Feng, Heng Yin
Research Collection School Of Computing and Information Systems
To improve the security awareness of end users, Android markets directly present two classes of literal app information: 1) permission requests and 2) textual descriptions. Unfortunately, neither can serve the needs. A permission list is not only hard to understand but also inadequate; textual descriptions provided by developers are not security-centric and are significantly deviated from the permissions. To fill in this gap, we propose a novel technique to automatically generate security-centric app descriptions, based on program analysis. We implement a prototype system, DESCRIBEME, and evaluate our system using both DroidBench and real-world Android apps. Experimental results demonstrate that DESCRIBEME …
Inferring Door Locations From A Teammate's Trajectory In Stealth Human-Robot Team Operations, Jean Oh, Arne Suppe, Arne Suppe, Anthony Stentz, Martial Hebert
Inferring Door Locations From A Teammate's Trajectory In Stealth Human-Robot Team Operations, Jean Oh, Arne Suppe, Arne Suppe, Anthony Stentz, Martial Hebert
Research Collection School Of Computing and Information Systems
Robot perception is generally viewed as the interpretation of data from various types of sensors such as cameras. In this paper, we study indirect perception where a robot can perceive new information by making inferences from non-visual observations of human teammates. As a proof-of-concept study, we specifically focus on a door detection problem in a stealth mission setting where a team operation must not be exposed to the visibility of the team's opponents. We use a special type of the Noisy-OR model known as BN2O model of Bayesian inference network to represent the inter-visibility and to infer the locations of …
Face Recognition On Large-Scale Video In The Wild With Hybrid Euclidean-And-Riemannian Metric Learning, Zhiwu Huang, R. Wang, S. Shan, X Chen
Face Recognition On Large-Scale Video In The Wild With Hybrid Euclidean-And-Riemannian Metric Learning, Zhiwu Huang, R. Wang, S. Shan, X Chen
Research Collection School Of Computing and Information Systems
Face recognition on large-scale video in the wild is becoming increasingly important due to the ubiquity of video data captured by surveillance cameras, handheld devices, Internet uploads, and other sources. By treating each video as one image set, set-based methods recently have made great success in the field of video-based face recognition. In the wild world, videos often contain extremely complex data variations and thus pose a big challenge of set modeling for set-based methods. In this paper, we propose a novel Hybrid Euclidean-and-Riemannian Metric Learning (HERML) method to fuse multiple statistics of image set. Specifically, we represent each image …
Contract-Based General-Purpose Gpu Programming, Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer
Contract-Based General-Purpose Gpu Programming, Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer
Research Collection School Of Computing and Information Systems
Using GPUs as general-purpose processors has revolutionized parallel computing by offering, for a large and growing set of algorithms, massive data-parallelization on desktop machines. An obstacle to widespread adoption, however, is the difficulty of programming them and the low-level control of the hardware required to achieve good performance. This paper suggests a programming library, SafeGPU, that aims at striking a balance between programmer productivity and performance, by making GPU data-parallel operations accessible from within a classical object-oriented programming language. The solution is integrated with the design-by-contract approach, which increases confidence in functional program correctness by embedding executable program specifications into …
A Note On The Security Of Khl Scheme, Jian Weng, Yunlei Zhao, Deng, Robert H., Shengli Liu, Yanjiang Yang, Kouichi Sakurai
A Note On The Security Of Khl Scheme, Jian Weng, Yunlei Zhao, Deng, Robert H., Shengli Liu, Yanjiang Yang, Kouichi Sakurai
Research Collection School Of Computing and Information Systems
A public key trace and revoke scheme combines the functionality of broadcast encryption with the capability of traitor tracing. In Asiacrypt 2003, Kim, Hwang and Lee proposed a public key trace and revoke scheme (referred to as KHL scheme), and gave the security proof to support that their scheme is z-resilient against adaptive chosen-ciphertext attacks, in which the adversary is allowed to adaptively issue decryption queries as well as adaptively corrupt up to z users. In the passed ten years, KHL scheme has been believed as one of the most efficient public key trace and revoke schemes with z-resilience against …
Seeing Your Face Is Not Enough: An Inertial Sensor-Based Liveness Detection For Face Authentication, Yan Li, Yingjiu Li, Qiang Yan, Hancong Kong, Robert H. Deng
Seeing Your Face Is Not Enough: An Inertial Sensor-Based Liveness Detection For Face Authentication, Yan Li, Yingjiu Li, Qiang Yan, Hancong Kong, Robert H. Deng
Research Collection School Of Computing and Information Systems
Leveraging built-in cameras on smartphones and tablets, face authentication provides an attractive alternative of legacy passwords due to its memory-less authentication process. However, it has an intrinsic vulnerability against the media-based facial forgery (MFF) where adversaries use photos/videos containing victims' faces to circumvent face authentication systems. In this paper, we propose FaceLive, a practical and robust liveness detection mechanism to strengthen the face authentication on mobile devices in fighting the MFF-based attacks. FaceLive detects the MFF-based attacks by measuring the consistency between device movement data from the inertial sensors and the head pose changes from the facial video captured by …
Analyzing Educational Comments For Topics And Sentiments: A Text Analytics Approach, Gokran Ila Nitin, Swapna Gottipati, Venky Shankararaman
Analyzing Educational Comments For Topics And Sentiments: A Text Analytics Approach, Gokran Ila Nitin, Swapna Gottipati, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Universities collect qualitative and quantitative feedback from students upon course completion in order to improve course quality and students’ learning experience. Combining program-wide and module-specific questions, universities collect feedback from students on three main aspects of a course namely, teaching style, content, and learning experience. The feedback is collected through both qualitative comments and quantitative scores. Current methods for analyzing the student course evaluations are manual and majorly focus on quantitative feedback and fall short of an in-depth exploration of qualitative feedback. In this paper, we develop student feedback mining system (SFMS) which applies text analytics and opinion mining approach …
Structural Constraints For Multipartite Entity Resolution With Markov Logic Network, Tengyuan Ye, Hady W. Lauw
Structural Constraints For Multipartite Entity Resolution With Markov Logic Network, Tengyuan Ye, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Multipartite entity resolution seeks to match entity mentions across several collections. An entity mention is presumed unique within a collection, and thus could match at most one entity mention in each of the other collections. In addition to domain-specific features considered in entity resolution, there are a number of domain-invariant structural contraints that apply in this scenario, including one-to-one assignment as well as cross-collection transitivity. We propose a principled solution to the multipartite entity resolution problem, building on the foundation of Markov Logic Network (MLN) that combines probabilistic graphical model and first-order logic. We describe how the domain-invariant structural constraints …
Targeted Blended Learning Through Competency Assessment In An Undergraduate Information Systems Program, Joelle Elmaleh, Shankararaman, Venky
Targeted Blended Learning Through Competency Assessment In An Undergraduate Information Systems Program, Joelle Elmaleh, Shankararaman, Venky
Research Collection School Of Computing and Information Systems
In this paper we report our study on the problem of competency acquisition when students progress from one course to another and more generally, from one term to the next. We observed that some students moved on to a second programming course without acquiring some of the competencies in the first programming course. This leads to problem in the second course, especially when these competencies are pre-requisites for this course. We applied blended learning, which allows a student to learn at least in part through delivery of content and instruction via online media, to overcome this problem. Our approach is …
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Research Collection School Of Computing and Information Systems
Relative similarity learning, as an important learning scheme for information retrieval, aims to learn a bi-linear similarity function from a collection of labeled instance-pairs, and the learned function would assign a high similarity value for a similar instance-pair and a low value for a dissimilar pair. Existing algorithms usually assume the labels of all the pairs in data streams are always made available for learning. However, this is not always realistic in practice since the number of possible pairs is quadratic to the number of instances in the database, and manually labeling the pairs could be very costly and time …
Density Peaks Clustering Approach For Discovering Demand Hot Spots In City-Scale Taxi Fleet Dataset, Dongchang Liu, Shih-Fen Cheng, Yiping Yang
Density Peaks Clustering Approach For Discovering Demand Hot Spots In City-Scale Taxi Fleet Dataset, Dongchang Liu, Shih-Fen Cheng, Yiping Yang
Research Collection School Of Computing and Information Systems
In this paper, we introduce a variant of the density peaks clustering (DPC) approach for discovering demand hot spots from a low-frequency, low-quality taxi fleet operational dataset. From the literature, the DPC approach mainly uses density peaks as features to discover potential cluster centers, and this requires distances between all pairs of data points to be calculated. This implies that the DPC approach can only be applied to cases with relatively small numbers of data points. For the domain of urban taxi operations that we are interested in, we could have millions of demand points per day, and calculating all-pair …
Shineseniors: Personalized Services For Active Ageing-In-Place, Liming Bai, Alex I. Gavino, Wei Qi Lee, Jungyoon Kim, Na Liu, Hwee-Pink Tan, Hwee Xian Tan, Lee Buay Tan, Xiaoping Toh, Alvin Cerdena Valera, Elina Jia Yu, Alfred Wu, Mark S. Fox
Shineseniors: Personalized Services For Active Ageing-In-Place, Liming Bai, Alex I. Gavino, Wei Qi Lee, Jungyoon Kim, Na Liu, Hwee-Pink Tan, Hwee Xian Tan, Lee Buay Tan, Xiaoping Toh, Alvin Cerdena Valera, Elina Jia Yu, Alfred Wu, Mark S. Fox
Research Collection School Of Computing and Information Systems
Singapore faces a major challenge in providing care and support for senior citizens due to its rapidlyageing population and declining old-age support ratio. The concept of Ageing-in-Place was introduced by the Singapore government [1] to allow older people to live independently in their own homes and communities so that the need for institutionalised care will only be utilised when necessary. We have three fundamental questions that this project will answer: 1. How to make community care serviceseffective through innovations in care delivery? How to lower the cost of service delivery and improve 2. productivity of caregivers, by leveraging information and …
What Are The Characteristics Of High-Rated Apps? A Case Study On Free Android Applications, Tian Yuan, Meiyappan Nagappan, David Lo, Ahmed E. Hassan
What Are The Characteristics Of High-Rated Apps? A Case Study On Free Android Applications, Tian Yuan, Meiyappan Nagappan, David Lo, Ahmed E. Hassan
Research Collection School Of Computing and Information Systems
The tremendous rate of growth in the mobile app market over the past few years has attracted many developers to build mobile apps. However, while there is no shortage of stories of how lone developers have made great fortunes from their apps, the majority of developers are struggling to break even. For those struggling developers, knowing the “DNA” (i.e., characteristics) of high-rated apps is the first step towards successful development and evolution of their apps. In this paper, we investigate 28 factors along eight dimensions to understand how high-rated apps are different from low-rated apps. We also investigate what are …
Constrained Feature Selection For Localizing Faults, Tien-Duy B. Le, David Lo, Ming Li
Constrained Feature Selection For Localizing Faults, Tien-Duy B. Le, David Lo, Ming Li
Research Collection School Of Computing and Information Systems
Developers often take much time and effort to find buggy program elements. To help developers debug, many past studies have proposed spectrum-based fault localization techniques. These techniques compare and contrast correct and faulty execution traces and highlight suspicious program elements. In this work, we propose constrained feature selection algorithms that we use to localize faults. Feature selection algorithms are commonly used to identify important features that are helpful for a classification task. By mapping an execution trace to a classification instance and a program element to a feature, we can transform fault localization to the feature selection problem. Unfortunately, existing …
What's Hot In Software Engineering Twitter Space?, Abhishek Sharma, Tian Yuan, David Lo
What's Hot In Software Engineering Twitter Space?, Abhishek Sharma, Tian Yuan, David Lo
Research Collection School Of Computing and Information Systems
Twitter is a popular means to disseminate information and currently more than 300 million people are using it actively. Software engineers are no exception; Singer et al. have shown that many developers use Twitter to stay current with recent technological trends. At various time points, many users are posting microblogs (i.e., tweets) about the same topic in Twitter. We refer to this reasonably large set of topically-coherent microblogs in the Twitter space made at a particular point in time as an event. In this work, we perform an exploratory study on software engineering related events in Twitter. We collect a …
Smartphones And Ble Services: Empirical Insights, Meera Radhakrishnan, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Smartphones And Ble Services: Empirical Insights, Meera Radhakrishnan, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Driven by the rapid market growth of sensors and beacons that offer Bluetooth Low Energy (BLE) based connectivity, this paper empirically investigates the performance characteristics of the BLE interface on multiple Android smartphones, and the consequent impact on a proposed BLE-based service: continuous indoor location. We first use extensive measurement studies with multiple Android devices to establish that the BLE interface on current smartphones is not as "low-energy" as nominally expected, and establish that continuous use of such a BLE interface is not feasible unless we choose a moderately large scan interval and a low duty cycle. We then explore …