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Articles 1561 - 1590 of 2211
Full-Text Articles in Software Engineering
Summarizing And Measuring Development Activity, Christoph Treude, Fernando Figueira Filho, Uirá Kulesza
Summarizing And Measuring Development Activity, Christoph Treude, Fernando Figueira Filho, Uirá Kulesza
Research Collection School Of Computing and Information Systems
Software developers pursue a wide range of activities as part of their work, and making sense of what they did in a given time frame is far from trivial as evidenced by the large number of awareness and coordination tools that have been developed in recent years. To inform tool design for making sense of the information available about a developer’s activity, we conducted an empirical study with 156 GitHub users to investigate what information they would expect in a summary of development activity, how they would measure development activity, and what factors influence how such activity can be condensed …
Uedashboard: Awareness Of Unusual Events In Commit Histories, Larissa Leite, Christoph Treude, Fernando Figueira Filho
Uedashboard: Awareness Of Unusual Events In Commit Histories, Larissa Leite, Christoph Treude, Fernando Figueira Filho
Research Collection School Of Computing and Information Systems
To be able to respond to source code modifications with large impact or commits that necessitate further examination, developers and managers in a software development team need to be aware of anything unusual happening in their software projects. To address this need, we introduce UEDashboard, a tool which automatically detects unusual events in a commit history based on metrics and smells, and surfaces them in an event feed. Our preliminary evaluation with a team of professional software developers showed that our conceptualization of unusual correlates with developers' perceptions of task difficulty, and that UEDashboard could be useful in supporting development …
Tonetrack: Leveraging Frequency-Agile Radios For Time-Based Indoor Wireless, Jie Xiong, Karthikeyan Sundaresan, Kyle Jamieson
Tonetrack: Leveraging Frequency-Agile Radios For Time-Based Indoor Wireless, Jie Xiong, Karthikeyan Sundaresan, Kyle Jamieson
Research Collection School Of Computing and Information Systems
Indoor localization of mobile devices and tags has received much attention recently, with encouraging fine-grained localization results available with enough line-of-sight coverage and hardware infrastructure. Some of the most promising techniques analyze the time-of-arrival of incoming signals, but the limited bandwidth available to most wireless transmissions fundamentally constrains their resolution. Frequency-agile wireless networks utilize bandwidths of varying sizes and locations in a wireless band to effi- ciently share the wireless medium between users. ToneTrack is an indoor location system that achieves sub-meter accuracy with minimal hardware and antennas, by leveraging frequency-agile wireless networks to increase the effective bandwidth. Our novel …
Need Accurate User Behaviour?: Pay Attention To Groups!, Kasthuri Jayarajah, Youngki Lee, Archan Misra, Rajesh Krishna Balan
Need Accurate User Behaviour?: Pay Attention To Groups!, Kasthuri Jayarajah, Youngki Lee, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we show that characterizing user behaviour from location or smartphone usage traces, without accounting for the interaction of individuals in physical-world groups, can lead to erroneous results. We conducted one of the largest studies in the UbiComp domain thus far, involving indoor location traces of more than 6,000 users, collected over a 4-month period at our university campus, and further studied fine-grained App usage of a subset of 156 Android users. We apply a state-of-the-art group detection algorithm to annotate such location traces with group vs. individual context, and then show that individuals vs. groups exhibit significant …
Sandra Helps You Learn: The More You Walk, The More Battery Your Phone Drains, Chulhong Min, Chungkuk Yoo, Inseok Hwang, Seungwoo Kang, Youngki Lee, Seungchul Lee, Pillsoon Park, Changhun Lee, Seungpyo Choi Choi
Sandra Helps You Learn: The More You Walk, The More Battery Your Phone Drains, Chulhong Min, Chungkuk Yoo, Inseok Hwang, Seungwoo Kang, Youngki Lee, Seungchul Lee, Pillsoon Park, Changhun Lee, Seungpyo Choi Choi
Research Collection School Of Computing and Information Systems
Emerging continuous sensing apps introduce new major factors governing phones’ overall battery consumption behaviors: (1) added nontrivial persistent battery drain, and more importantly (2) different battery drain rate depending on the user’s different mobility condition. In this paper, we address the new battery impacting factors significant enough to outdate users’ existing battery model in real life. We explore an initial approach to help users understand the cause and effect between their physical activity and phones’ battery life. To this end, we present Sandra, a novel mobility-aware smartphone battery information advisor, and study its potential to help users redevelop their battery …
Candy Crushing Your Sleep, Kasthuri Jeyarajah, Meeralakshi Radhakrishnan, Steven C. H. Hoi, Archan Misra
Candy Crushing Your Sleep, Kasthuri Jeyarajah, Meeralakshi Radhakrishnan, Steven C. H. Hoi, Archan Misra
Research Collection School Of Computing and Information Systems
Growing interest in quantified self has led to the popularity of lifelogging applications. In particular, health and wellness related applications have seen an upsurge with the advent of wearables such as the Fitbit. In this paper, we focus on the quality of sleep that directly impacts the overall wellness of individuals. In particular, in this work, we present a first of its kind study that (1) unobtrusively quantifies the quality of sleep and (2) seeks to identify attributing aspects of our daily lives such as an individual's usage of apps throughout the day and his/her physical environment that may affect …
Deep Learning For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Yun Zhang, Jianling Sun
Deep Learning For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Yun Zhang, Jianling Sun
Research Collection School Of Computing and Information Systems
Defect prediction is a very meaningful topic, particularly at change-level. Change-level defect prediction, which is also referred as just-in-time defect prediction, could not only ensure software quality in the development process, but also make the developers check and fix the defects in time. Nowadays, deep learning is a hot topic in the machine learning literature. Whether deep learning can be used to improve the performance of just-in-time defect prediction is still uninvestigated. In this paper, to bridge this research gap, we propose an approach Deeper which leverages deep learning techniques to predict defect-prone changes. We first build a set of …
Enabling Real Time In-Situ Context Based Experimentation To Observe User Behaviour, Kartik Muralidaran
Enabling Real Time In-Situ Context Based Experimentation To Observe User Behaviour, Kartik Muralidaran
Dissertations and Theses Collection (Open Access)
Today’s mobile phones represent a rich and powerful computing platform, given their sensing, processing and communication capabilities. These devices are also part of the everyday life of millions of people, and coupled with the unprecedented access to personal context, make them the ideal tool for conducting behavioural experiments in an unobtrusive way. Transforming the mobile device from a mere observer of human context to an enabler of behavioural experiments however, requires not only providing experimenters access to the deep, near-real time human context (e.g., location, activity, group dynamics) but also exposing a disciplined scientific experimentation service that frees them from …
A Study On The Geographical Distribution Of Brazil’S Prestigious Software Developers, Fernando Figueira Filho, Marcelo Gattermann Perin, Christoph Treude, Sabrina Marczak, Leandro De Almeida Melo, Igor Marques Da Silva, Lucas Bibiano Dos Santos
A Study On The Geographical Distribution Of Brazil’S Prestigious Software Developers, Fernando Figueira Filho, Marcelo Gattermann Perin, Christoph Treude, Sabrina Marczak, Leandro De Almeida Melo, Igor Marques Da Silva, Lucas Bibiano Dos Santos
Research Collection School Of Computing and Information Systems
Brazil is an emerging economy with many IT initiatives from public and private sectors. To evaluate the progress of such initiatives, we study the geographical distribution of software developers in Brazil, in particular which of the Brazilian states succeed the most in attracting and nurturing them. We compare the prestige of developers with socio-economic data and find that (i) prestigious developers tend to be located in the most economically developed regions of Brazil, (ii) they are likely to follow others in the same state they are located in, (iii) they are likely to follow other prestigious developers, and (iv) they …
Memes As Building Blocks: A Case Study On Evolutionary Optimization + Transfer Learning For Routing Problems, Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Ivor W. Tsang
Memes As Building Blocks: A Case Study On Evolutionary Optimization + Transfer Learning For Routing Problems, Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Ivor W. Tsang
Research Collection School Of Computing and Information Systems
A significantly under-explored area of evolutionary optimization in the literature is the study of optimization methodologies that can evolve along with the problems solved. Particularly, present evolutionary optimization approaches generally start their search from scratch or the ground-zero state of knowledge, independent of how similar the given new problem of interest is to those optimized previously. There has thus been the apparent lack of automated knowledge transfers and reuse across problems. Taking this cue, this paper presents a Memetic Computational Paradigm based on Evolutionary Optimization + Transfer Learning for search, one that models how human solves problems, and embarks on …
Towards A Robust Sparse Data Representation In Wireless Sensor Networks, Abu Alsheik Mohammad, Shaowei Lin, Hwee-Pink Tan, Dusit Niyato
Towards A Robust Sparse Data Representation In Wireless Sensor Networks, Abu Alsheik Mohammad, Shaowei Lin, Hwee-Pink Tan, Dusit Niyato
Research Collection School Of Computing and Information Systems
Compressive sensing has been successfully used for optimized operations in wireless sensor networks. However, raw data collected by sensors may be neither originally sparse nor easily transformed into a sparse data representation. This paper addresses the problem of transforming source data collected by sensor nodes into sparse representation with a few nonzero elements. Our contributions that address three major issues include: 1) an effective method that extracts population sparsity of the data, 2) a sparsity ratio guarantee scheme, and 3) a customized leaerning algorithm of the sparsifying dictionary. We introduce an unsupervised neural network to extract an intrinsic sparse coding …
Apparatus And Method For Determining The Location Of A Mobile Device Using Multiple Wireless Access Points, Kyle Jamieson, Jie Xiong
Apparatus And Method For Determining The Location Of A Mobile Device Using Multiple Wireless Access Points, Kyle Jamieson, Jie Xiong
Research Collection School Of Computing and Information Systems
A method and apparatus are provided for determining the location of a mobile device using multiple wireless access points, each wireless access point comprising multiple antennas. The method comprises receiving a communication signal from the mobile device at said multiple antennas of said multiple wireless access points. For each wireless access point, angle-of-arrival information of the received communication signal at the wireless access point is determined, based on a difference in phase of the received signal between different antennas. The determined angle-of-arrival information for the received communication signal from the mobile device is then collected from each of the multiple …
Cooperation In Delay-Tolerant Networks With Wireless Energy Transfer: Performance Analysis And Optimization, Dusit Niyato, Ping Wang, Hwee-Pink Tan, Walid Saad, Dong In Kim
Cooperation In Delay-Tolerant Networks With Wireless Energy Transfer: Performance Analysis And Optimization, Dusit Niyato, Ping Wang, Hwee-Pink Tan, Walid Saad, Dong In Kim
Research Collection School Of Computing and Information Systems
We consider a delay-tolerant network (DTN) whose mobile nodes are assigned to collect packets from data sources and deliver them to a sink (i.e., a gateway). Each mobile node operates by using energy transferred wirelessly from the gateway. For such a network, two main issues are studied. First, when a mobile node is at the data source, this node must decide on whether to accept the packet received from the data source or not. In contrast, whenever a mobile node is at the gateway, it has to decide on whether to transmit the packets collected from the data sources or …
Detection And Classification Of Malicious Javascript Via Attack Behavior Modelling, Yinxing Xue, Junjie Wang, Yang Liu, Hao Xiao, Jun Sun, Mahinthan Chandramohan
Detection And Classification Of Malicious Javascript Via Attack Behavior Modelling, Yinxing Xue, Junjie Wang, Yang Liu, Hao Xiao, Jun Sun, Mahinthan Chandramohan
Research Collection School Of Computing and Information Systems
Existing malicious JavaScript (JS) detection tools and commercial anti-virus tools mostly use feature-based or signature-based approaches to detect JS malware. These tools are weak in resistance to obfuscation and JS malware variants, not mentioning about providing detailed information of attack behaviors. Such limitations root in the incapability of capturing attack behaviors in these approches. In this paper, we propose to use Deterministic Finite Automaton (DFA) to abstract and summarize common behaviors of malicious JS of the same attack type. We propose an automatic behavior learning framework, named JS∗ , to learn DFA from dynamic execution traces of JS malware, where …
On Multipath Link Characterization And Adaptation For Device-Free Human Detection, Zimu Zhou, Zheng Yang, Chenshu Wu, Yunhao Liu, Lionel M. Ni
On Multipath Link Characterization And Adaptation For Device-Free Human Detection, Zimu Zhou, Zheng Yang, Chenshu Wu, Yunhao Liu, Lionel M. Ni
Research Collection School Of Computing and Information Systems
No abstract provided.
Optimizing Selection Of Competing Features Via Feedback-Directed Evolutionary Algorithms, Tian Huat Tan, Yinxing Xue, Manman Chen, Jun Sun, Yang Liu, Jin Song Dong Dong
Optimizing Selection Of Competing Features Via Feedback-Directed Evolutionary Algorithms, Tian Huat Tan, Yinxing Xue, Manman Chen, Jun Sun, Yang Liu, Jin Song Dong Dong
Research Collection School Of Computing and Information Systems
Software that support various groups of customers usually require complicated configurations to attain different functionalities. To model the configuration options, feature model is proposed to capture the commonalities and competing variabilities of the product variants in software family or Software Product Line (SPL). A key challenge for deriving a new product is to find a set of features that do not have inconsistencies or conflicts, yet optimize multiple objectives (e.g., minimizing cost and maximizing number of features), which are often competing with each other. Existing works have attempted to make use of evolutionary algorithms (EAs) to address this problem. In …
Reliability Assessment For Distributed Systems Via Communication Abstraction And Refinement, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong
Reliability Assessment For Distributed Systems Via Communication Abstraction And Refinement, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Distributed systems like cloud-based services are ever more popular. Assessing the reliability of distributed systems is highly non-trivial. Particularly, the order of executions among distributed components adds a dimension of non-determinism, which invalidates existing reliability assessment methods based on Markov chains. Probabilistic model checking based on models like Markov decision processes is designed to deal with scenarios involving both probabilistic behavior (e.g., reliabilities of system components) and non-determinism. However, its application is currently limited by state space explosion, which makes reliability assessment of distributed system particularly difficult. In this work, we improve the probabilistic model checking through a method of …
An Automatic Approach To Detect Unusual Events In Software Repositories, Larissa Leite, Christoph Treude, Fernando Figueira Filho
An Automatic Approach To Detect Unusual Events In Software Repositories, Larissa Leite, Christoph Treude, Fernando Figueira Filho
Research Collection School Of Computing and Information Systems
This work presents an automatic approach to detect unusual events in software repositories. The approach collects data from source code repositories and analyzes new commits based on historical data in order to detect unusual events that are displayed to developers and managers in an awareness tool.
S-Looper: Automatic Summarization For Multipath String Loops, Xiaofei Xie, Yang Liu, Wei Le, Xiaohong Li, Hongxu Chen
S-Looper: Automatic Summarization For Multipath String Loops, Xiaofei Xie, Yang Liu, Wei Le, Xiaohong Li, Hongxu Chen
Research Collection School Of Computing and Information Systems
Loops are important yet most challenging program constructs to analyze for various program analysis tasks. Existing loop analysis techniques mainly handle well loops that contain only integer variables with a single path in the loop body. The key challenge in summarizing a multiple-path loop is that a loop traversal can yield a large number of possibilities due to the different execution orders of these paths located in the loop; when a loop contains a conditional branch related to string content, we potentially need to track every character in the string for loop summarization, which is expensive. In this paper, we …
Active Semi-Supervised Approach For Checking App Behavior Against Its Description, Ma Siqi, Shaowei Wang, David Lo, Deng, Robert H., Cong Sun
Active Semi-Supervised Approach For Checking App Behavior Against Its Description, Ma Siqi, Shaowei Wang, David Lo, Deng, Robert H., Cong Sun
Research Collection School Of Computing and Information Systems
Mobile applications are popular in recent years. They are often allowed to access and modify users' sensitive data. However, many mobile applications are malwares that inappropriately use these sensitive data. To detect these malwares, Gorla et al. Propose CHABADA which compares app behaviors against its descriptions. Data about known malwares are not used in their work, which limits its effectiveness. In this work, we extend the work by Gorla et al. By proposing an active and semi-supervised approach for detecting malwares. Different from CHABADA, our approach will make use of both known benign and malicious apps to predict other malicious …
An Empirical Study Of Classifier Combination On Cross-Project Defect Prediction, Yun Zhang, David Lo, Xin Xia, Jianling Sun
An Empirical Study Of Classifier Combination On Cross-Project Defect Prediction, Yun Zhang, David Lo, Xin Xia, Jianling Sun
Research Collection School Of Computing and Information Systems
To help developers better allocate testing and debugging efforts, many software defect prediction techniques have been proposed in the literature. These techniques can be used to predict classes that are more likely to be buggy based on past history of buggy classes. These techniques work well as long as a sufficient amount of data is available to train a prediction model. However, there is rarely enough training data for new software projects. To deal with this problem, cross-project defect prediction, which transfers a prediction model trained using data from one project to another, has been proposed and is regarded as …
Adaptive Resource Provisioning Mechanism In Vees For Improving Performance Of Hla-Based Simulations, Zengxiang Li, Wentong Cai, Stephen John Turner, Xiaorong Li, Nguyen Binh Duong Ta
Adaptive Resource Provisioning Mechanism In Vees For Improving Performance Of Hla-Based Simulations, Zengxiang Li, Wentong Cai, Stephen John Turner, Xiaorong Li, Nguyen Binh Duong Ta
Research Collection School Of Computing and Information Systems
Parallel and distributed simulations (or High-Level Architecture (HLA)-based simulations) employing optimistic synchronization allow federates to advance simulation time freely at the risk of overoptimistic executions and execution rollbacks. As a result, the simulation performance may degrade significantly due to the simulation workload imbalance among federates. In this article, we investigate the execution of parallel and distributed simulations on Cloud and data centers with Virtual Execution Environments (VEEs). In order to speed up simulation execution, an Adaptive Resource Provisioning Mechanism in Virtual Execution Environments (ArmVee) is proposed. It is composed of a performance monitor and a resource manager. The former measures …
Aarpa: Combining Mobile And Power-Line Sensing For Fine-Grained Appliance Usage And Energy Monitoring, Nirmalya Roy, Nilavra Pathak, Archan Misra
Aarpa: Combining Mobile And Power-Line Sensing For Fine-Grained Appliance Usage And Energy Monitoring, Nirmalya Roy, Nilavra Pathak, Archan Misra
Research Collection School Of Computing and Information Systems
To promote energy-efficient operations in residential and office buildings, non-intrusive load monitoring (NILM) techniques have been proposed to infer the fine-grained power consumption and usage patterns of appliances from power-line measurement data. Fine-grained monitoring of everyday appliances (such as toasters and coffee makers) can not only promote energy-efficient building operations, but also provide unique insights into the context and activities of individuals. Current building-level NILM techniques are unable to identify the consumption characteristics of relatively low-load appliances, whereas smart-plug based solutions incur significant deployment and maintenance costs. In this paper, we investigate an intermediate architecture, where smart circuit breakers provide …
Wifi-Based Indoor Line-Of-Sight Identification, Zimu Zhou, Zheng Yang, Chenshu Wu, Longfei Shangguan, Haibin Cai, Yunhao Liu, Lionel M. Ni
Wifi-Based Indoor Line-Of-Sight Identification, Zimu Zhou, Zheng Yang, Chenshu Wu, Longfei Shangguan, Haibin Cai, Yunhao Liu, Lionel M. Ni
Research Collection School Of Computing and Information Systems
Wireless LANs, particularly WiFi, have been pervasively deployed and have fostered myriad wireless communication services and ubiquitous computing applications. A primary concern in designing these applications is to combat harsh indoor propagation environments, particularly Non-Line-Of-Sight (NLOS) propagation. The ability to identify the existence of the Line-Of-Sight (LOS) path acts as a key enabler for adaptive communication, cognitive radios, and robust localization. Enabling such capability on commodity WiFi infrastructure, however, is prohibitive due to the coarse multipath resolution with MAC-layer received signal strength. In this paper, we propose two PHY-layer channel-statistics-based features from both the time and frequency domains. To further …
Extracting Development Tasks To Navigate Software Documentation, Christoph Treude, Martin P. Robillard, Barthélémy Dagenais
Extracting Development Tasks To Navigate Software Documentation, Christoph Treude, Martin P. Robillard, Barthélémy Dagenais
Research Collection School Of Computing and Information Systems
Knowledge management plays a central role in many software development organizations. While much of the important technical knowledge can be captured in documentation, there often exists a gap between the information needs of software developers and the documentation structure. To help developers navigate documentation, we developed a technique for automatically extracting tasks from software documentation by conceptualizing tasks as specific programming actions that have been described in the documentation. More than 70 percent of the tasks we extracted from the documentation of two projects were judged meaningful by at least one of two developers. We present TaskNavigator, a user interface …
Wifi-Based Indoor Line-Of-Sight Identification, Zimu Zhou, Zheng Yang, Chenshu Wu, Longfei Shangguan, Haibin Cai, Yunhao Liu, Lionel M. Ni
Wifi-Based Indoor Line-Of-Sight Identification, Zimu Zhou, Zheng Yang, Chenshu Wu, Longfei Shangguan, Haibin Cai, Yunhao Liu, Lionel M. Ni
Research Collection School Of Computing and Information Systems
Wireless LANs, particularly WiFi, have been pervasively deployed and have fostered myriad wireless communication services and ubiquitous computing applications. A primary concern in designing these applications is to combat harsh indoor propagation environments, particularly Non-Line-Of-Sight (NLOS) propagation. The ability to identify the existence of the Line-Of-Sight (LOS) path acts as a key enabler for adaptive communication, cognitive radios, and robust localization. Enabling such capability on commodity WiFi infrastructure, however, is prohibitive due to the coarse multipath resolution with MAC-layer received signal strength. In this paper, we propose two PHY-layer channel-statistics-based features from both the time and frequency domains. To further …
Verifying Parameterized Timed Security Protocols, Li Li, Jun Sun, Yang Liu, Jin Song Dong
Verifying Parameterized Timed Security Protocols, Li Li, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Quantitative timing is often explicitly used in systems for better security, e.g., the credentials for automatic website logon often has limited lifetime. Verifying timing relevant security protocols in these systems is very challenging as timing adds another dimension of complexity compared with the untimed protocol verification. In our previous work, we proposed an approach to check the correctness of the timed authentication in security protocols with fixed timing constraints. However, a more difficult question persists, i.e., given a particular protocol design, whether the protocol has security flaws in its design or it can be configured secure with proper parameter values? …
Heuristic Collective Learning For Efficient And Robust Emergence Of Social Norms, Jianye Hao, Jun Sun, Dongping Huang, Yi Cai, Chao Yu
Heuristic Collective Learning For Efficient And Robust Emergence Of Social Norms, Jianye Hao, Jun Sun, Dongping Huang, Yi Cai, Chao Yu
Research Collection School Of Computing and Information Systems
In multiagent systems, social norms is a useful technique in regulating agents’ behaviors to achieve coordination or cooperation among agents. One important research question is to investigate how a desirable social norm can be evolved in a bottom-up manner through local interactions. In this paper, we propose two novel learning strategies under the collective learning framework: collective learning EV-l and collective learning EV-g, to efficiently facilitate the emergence of social norms. Experimental results show that both learning strategies can support the emergence of desirable social norms more efficiently in a much broader range of multiagent interaction scenarios than previous work, …
Non-Invasive Detection Of Moving And Stationary Human With Wifi, Chenshu Wu, Zheng Yang, Zimu Zhou, Xuefeng Liu, Yunhao Liu, Jiannong Cao
Non-Invasive Detection Of Moving And Stationary Human With Wifi, Chenshu Wu, Zheng Yang, Zimu Zhou, Xuefeng Liu, Yunhao Liu, Jiannong Cao
Research Collection School Of Computing and Information Systems
Non-invasive human sensing based on radio signals has attracted a great deal of research interest and fostered a broad range of innovative applications of localization, gesture recognition, smart health-care, etc., for which a primary primitive is to detect human presence. Previous works have studied the detection of moving humans via signal variations caused by human movements. For stationary people, however, existing approaches often employ a prerequisite scenario-tailored calibration of channel profile in human-free environments. Based on in-depth understanding of human motion induced signal attenuation reflected by PHY layer channel state information (CSI), we propose DeMan, a unified scheme for non-invasive …
Relative Localization Of Rfid Tags Using Spatial-Temporal Phase Profiling, Longfei Shangguan, Zheng Yang, Alex X. Liu, Zimu Zhou, Yunhao Liu
Relative Localization Of Rfid Tags Using Spatial-Temporal Phase Profiling, Longfei Shangguan, Zheng Yang, Alex X. Liu, Zimu Zhou, Yunhao Liu
Research Collection School Of Computing and Information Systems
Many object localization applications need the relative locations of a set of objects as oppose to their absolute locations. Although many schemes for object localization using Radio Frequency Identification (RFID) tags have been proposed, they mostly focus on absolute object localization and are not suitable for relative object localization because of large error margins and the special hardware that they require. In this paper, we propose an approach called Spatial-Temporal Phase Profiling (STPP) to RFID based relative object localization. The basic idea of STPP is that by moving a reader over a set of tags during which the reader continuously …