Software Engineering Commons^™

Vkse-Mo: Verifiable Keyword Search Over Encrypted Data In Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Junwei Zhang, Zhiquan Liu

Research Collection School Of Computing and Information Systems

Searchable encryption (SE) techniques allow cloud clients to easily store data and search encrypted data in a privacy-preserving manner, where most of SE schemes treat the cloud server as honest-but-curious. However, in practice, the cloud server is a semi-honest-but-curious third-party, which only executes a fraction of search operations and returns a fraction of false search results to save its computational and bandwidth resources. Thus, it is important to provide a results verification method to guarantee the correctness of the search results. Existing SE schemes allow multiple data owners to upload different records to the cloud server, but these schemes have …

Enabling Phased Array Signal Processing For Mobile Wifi Devices, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu

Research Collection School Of Computing and Information Systems

Modern mobile devices are equipped with multiple antennas, which brings various wireless sensing applications such as accurate localization, contactless human detection, and wireless human-device interaction. A key enabler for these applications is phased array signal processing, especially Angle of Arrival (AoA) estimation. However, accurate AoA estimation on commodity devices is non-trivial due to limited number of antennas and uncertain phase offsets. Previous works either rely on elaborate calibration or involve contrived human interactions. In this paper, we aim to enable practical AoA measurements on commodity off-the-shelf (COTS) mobile devices. The key insight is to involve users’ natural rotation to formulate …

Spatio-Temporal Analysis And Prediction Of Cellular Traffic In Metropolis, Xu Wang, Zimu Zhou, Zheng Yang, Yunhao Liu, Chunyi Peng

Research Collection School Of Computing and Information Systems

Understanding and predicting cellular traffic at large-scale and fine-granularity is beneficial and valuable to mobile users, wireless carriers and city authorities. Predicting cellular traffic in modern metropolis is particularly challenging because of the tremendous temporal and spatial dynamics introduced by diverse user Internet behaviours and frequent user mobility citywide. In this paper, we characterize and investigate the root causes of such dynamics in cellular traffic through a big cellular usage dataset covering 1.5 million users and 5,929 cell towers in a major city of China. We reveal intensive spatio-temporal dependency even among distant cell towers, which is largely overlooked in …

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

Toward Accurate Network Delay Measurement On Android Phones, Weichao Li, Daoyuan Wu, Rocky K. C. Chang, Ricky K. P. Mok

Research Collection School Of Computing and Information Systems

Measuring and understanding the performance of mobile networks is becoming very important for end users and operators. Despite the availability of many measurement apps, their measurement accuracy has not received sufficient scrutiny. In this paper, we appraise the accuracy of smartphone-based network performance measurement using the Android platform and the network round-trip time (RTT) as the metric. We show that two of the most popular measurement apps-Ookla Speedtest and MobiPerf-have their RTT measurements inflated. We build three test apps that cover three common measurement methods and evaluate them in a testbed. We overcome the main challenge of obtaining a complete …

Recommending Personalized Schedules In Urban Environments, Cen Chen

Dissertations and Theses Collection

In this thesis, we are broadly interested in solving real world problems that involve decision support for coordinating agent movements in dynamic urban environments, where people are agents exhibiting different human behavior patterns and preferences. The rapid development of mobile technologies makes it easier to capture agent behavioral and preference information. Such rich agent specific information, coupled with the explosive growth of computational power, opens many opportunities that we could potentially leverage, to better guide/influence the agents in urban environments. The purpose of this thesis is to investigate how we can effectively and efficiently guide and coordinate the agents with …

Inferring Motion Direction Using Commodity Wi-Fi For Interactive Exergames, Kun Qian, Chenshu Wu, Zimu Zhou, Yue Zheng, Yang Zheng, Yunhao Liu

Research Collection School Of Computing and Information Systems

In-air interaction acts as a key enabler for ambient intelligence and augmented reality. As an increasing popular example, exergames, and the alike gesture recognition applications, have attracted extensive research in designing accurate, pervasive and low-cost user interfaces. Recent advances in wireless sensing show promise for a ubiquitous gesture-based interaction interface with Wi-Fi. In this work, we extract complete information of motion-induced Doppler shifts with only commodity Wi-Fi. The key insight is to harness antenna diversity to carefully eliminate random phase shifts while retaining relevant Doppler shifts. We further correlate Doppler shifts with motion directions, and propose a light-weight pipeline to …

Tum: Towards Ubiquitous Multi-Device Localization For Cross-Device Interaction, Han Xu, Zheng Yang, Zimu Zhou, Ke Yi, Chunyi Peng

Research Collection School Of Computing and Information Systems

Cross-device interaction is becoming an increasingly hot topic as we often have multiple devices at our immediate disposal in this era of mobile computing. Various cross-device applications such as file sharing, multi-screen display, and crossdevice authentication have been proposed and investigated. However, one of the most fundamental enablers remains unsolved: How to achieve ubiquitous multi-device localization? Though pioneer efforts have resorted to gesture-assisted or sensing-assisted localization, they either require extensive user participation or impose some strong assumptions on device sensing abilities. This introduces extra costs and constraints, and thus degrades their practicality. To overcome these limitations, we propose TUM, an …

Rapid Deployment Indoor Localization Without Prior Human Participation, Han Xu, Zimu Zhou, Longfei Shangguan

Research Collection School Of Computing and Information Systems

In this work, we propose RAD, a RApid Deployment localization framework without human sampling. The basic idea of RAD is to automatically generate a fingerprint database through space partition, of which each cell is fingerprinted by its maximum influence APs. Based on this robust location indicator, fine-grained localization can be achieved by a discretized particle filter utilizing sensor data fusion. We devise techniques for CIVD-based field division, graph-based particle filter, EM-based individual character learning, and build a prototype that runs on commodity devices. Extensive experiments show that RAD provides a comparable performance to the state-of-the-art RSSbased methods while relieving it …

Passively Testing Routing Protocols In Wireless Sensor Networks, Xiaoping Che, Stephane Maag, Hwee-Xian Tan, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Smart systems are today increasingly developed with the number of wireless sensor devices that drastically increases. They are implemented within several contexts through our environment. Thus, sensed data transported in ubiquitous systems are important and the way to carry them must be efficient and reliable. For that purpose, several routing protocols have been proposed to wireless sensor networks (WSN). However, one stage that is often neglected before their deployment, is the conformance testing process, a crucial and challenging step. Active testing techniques commonly used in wired networks are not suitable to WSN and passive approaches are needed. While some works …

Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Software engineering practitioners often spend significant amount of time and effort to debug. To help practitioners perform this crucial task, hundreds of papers have proposed various fault localization techniques. Fault localization helps practitioners to find the location of a defect given its symptoms (e.g., program failures). These localization techniques have pinpointed the locations of bugs of various systems of diverse sizes, with varying degrees of success, and for various usage scenarios. Unfortunately, it is unclear whether practitioners appreciate this line of research. To fill this gap, we performed an empirical study by surveying 386 practitioners from more than 30 countries …

Stpp: Spatial-Temporal Phase Profiling Based Method For Relative Rfid Tag Localization, 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 interrogating …

Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra

Research Collection School Of Computing and Information Systems

We design and develop TA$Ker, a real-world mobile crowd- sourcing platform to empirically study the worker responses to various task recommendation and selection strategies.

Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra

Research Collection School Of Computing and Information Systems

To model the overall personal inhalation of hazardous gases through the air (both indoor and outdoor) by an individual, provide air quality friendly route recommendations, thus raising the overall quality of urban movement and living healthy life.

Smokey: Ubiquitous Smoking Detection With Commercial Wifi Infrastructures, Xiaolong Zheng, Jiliang Wang, Longfei Shangguan, Zimu Zhou, Yunhao Liu

Research Collection School Of Computing and Information Systems

Even though indoor smoking ban is being put into practice in civilized countries, existing vision or sensor-based smoking detection methods cannot provide ubiquitous smoking detection. In this paper, we take the first attempt to build a ubiquitous passive smoking detection system, which leverages the patterns smoking leaves on WiFi signals to identify the smoking activity even in the non-line-of-sight and through-wall environments. We study the behaviors of smokers and leverage the common features to recognize the series of motions during smoking, avoiding the target-dependent training set to achieve the high accuracy. We design a foreground detection based motion acquisition method …

Tuning By Turning: Enabling Phased Array Signal Processing For Wifi With Inertial Sensors, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu

Research Collection School Of Computing and Information Systems

Modern mobile devices are equipped with multiple antennas, which brings various wireless sensing applications such as accurate localization, contactless human detection and wireless human-device interaction. A key enabler for these applications is phased array signal processing, especially Angle of Arrival (AoA) estimation. However, accurate AoA estimation on commodity devices is non-trivial due to limited number of antennas and uncertain phase offsets. Previous works either rely on elaborate calibration or involve contrived human interactions. In this paper, we aim to enable practical AoA measurements on commodity off-the-shelf (COTS) mobile devices. The key insight is to involve users’ natural rotation to formulate …

Improving The Sensitivity Of Unobtrusive Inactivity Detection In Sensor-Enabled Homes For The Elderly, Alvin C. Valera, Hwee-Pink Tan, Liming Bai

Research Collection School Of Computing and Information Systems

Unobtrusive in-home monitoring systems are gaining acceptability and are being deployed to enable relatives and caregivers to remotely monitor and provide timely care to their elderly loved ones or senior clients, respectively, who are living independently. Such systems can provide information about nonmovement or inactivity of the elderly resident. As prolonged inactivity could mean potential danger, several algorithms have been proposed to automatically detect unusually long durations of inactivity. Such schemes, however, suffer from low sensitivity due to their high detection latency. In this paper, we propose Dwell Time-enhanced Dynamic Threshold (DTDT), a scheme for computing adaptive alert thresholds that …

Ambient And Smartphone Sensor Assisted Adl Recognition In Multi-Inhabitant Smart Environments, Nirmalya Roy, Archan Misra, Diane Cook

Research Collection School Of Computing and Information Systems

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users’ spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user …

We Can Hear You With Wi-Fi!, Guanhua Wang, Yongpan Zou, Zimu Zhou, Kaishun Wu, Lionel M. Ni

Research Collection School Of Computing and Information Systems

Recent literature advances Wi-Fi signals to “see” people’s motions and locations. This paper asks the following question: Can Wi-Fi “hear” our talks? We present WiHear, which enables Wi-Fi signals to “hear” our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micro-movement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can “hear” people talks within the radio range. Further, WiHear can simultaneously “hear” multiple people’s talks leveraging MIMO technology. We …

Social Signal Processing For Real-Time Situational Understanding: A Vision And Approach, Kasthuri Jeyarajah, Shuchao Yao, Raghava Muthuraju, Archan Misra, Geeth De Mel, Julie Skipper, Tarek Abdelzaher, Michael Kolodny

Research Collection School Of Computing and Information Systems

The US Army Research Laboratory (ARL) and the Air Force Research Laboratory (AFRL) have established a collaborative research enterprise referred to as the Situational Understanding Research Institute (SURI). The goal is to develop an information processing framework to help the military obtain real-time situational awareness of physical events by harnessing the combined power of multiple sensing sources to obtain insights about events and their evolution. It is envisioned that one could use such information to predict behaviors of groups, be they local transient groups (e.g., protests) or widespread, networked groups, and thus enable proactive prevention of nefarious activities. This paper …

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 …

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 …

Design, Programming, And User-Experience, Kaila G. Manca

Honors Scholar Theses

This thesis is a culmination of my individualized major in Human-Computer Interaction. As such, it showcases my knowledge of design, computer engineering, user-experience research, and puts into practice my background in psychology, com- munications, and neuroscience.

I provided full-service design and development for a web application to be used by the Digital Media and Design Department and their students.This process involved several iterations of user-experience research, testing, concepting, branding and strategy, ideation, and design. It lead to two products.

The first product is full-scale development and optimization of the web appli- cation.The web application adheres to best practices. It was …

Matchmaking Game Players On Public Transport, Nairan Zhang, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

This paper extends our recent work, called GameOn, which presented a system for allowing public transport commuters to engage in multiplayer games with fellow commuters traveling on the same bus or train. An important challenge for GameOn is to group players with reliable connections into the same game. In this case, the meaning of reliability has two dimensions. First, the network connectivity (TCP, UDP etc.) should be robust. Second, the players should be collocated with each other for a sufficiently long duration so that a game session will not be terminated by players leaving the public transport modality such as …

Ambient Rendezvous: Energy Efficient Neighbor Discovery Via Acoustic Sensing, Keyu Wang, Zheng Yang, Zimu Zhou, Yunhao Liu, Lionel M. Ni

Research Collection School Of Computing and Information Systems

The continual proliferation of mobile devices has stimulated the development of opportunistic encounter-based networking and has spurred a myriad of proximity-based mobile applications. A primary cornerstone of such applications is to discover neighboring devices effectively and efficiently. Despite extensive protocol optimization, current neighbor discovery modalities mainly rely on radio interfaces, whose energy and wake up delay required to initiate, configure and operate these protocols hamper practical applicability. Unlike conventional schemes that actively emit radio tones, we exploit ubiquitous audio events to discover neighbors passively. The rationale is that spatially adjacent neighbors tend to share similar ambient acoustic environments. We propose …

Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Context data, collected either from mobile devices or from user-generated social media content, can help identify abnormal behavioural patterns in public spaces (e.g., shopping malls, college campuses or downtown city areas). Spatiotemporal analysis of such data streams provides a compelling new approach towards automatically creating real-time urban situational awareness, especially about events that are unanticipated or that evolve very rapidly. In this work, we use real-life datasets collected via SMU's LiveLabs testbed or via SMU's Palanteer software, to explore various discriminative features (both spatial and temporal - e.g., occupancy volumes, rate of change in topic{specific tweets or probabilistic distribution of …

First Step Mental Health App, Joshua Martin, James Faraday, Mackenzie Lopez

Undergraduate Research Symposium

The goal of this project is to create a tool that provides students at Minnesota State University, Mankato with mental health information through a freely available smartphone application (App). Our approach uses a software engineering design process that focuses on who our customers are, what resources are available, and how we can best connect the two to improve student lives. We identified the stakeholders involved and worked with campus mental health professionals to help shape our App. While there is a broad range of mental health topics, we have focused on materials related to depression. The first process gives the …

Securearray: Improving Wifi Security With Fine-Grained Physical-Layer, Jie Xiong, Kyle Jamieson

Research Collection School Of Computing and Information Systems

Despite the important role that WiFi networks play in home and enterprise networks they are relatively weak from a security standpoint. With easily available directional antennas, attackers can be physically located off-site, yet compromise WiFi security protocols such as WEP, WPA, and even to some extent WPA2 through a range of exploits specific to those protocols, or simply by running dictionary and human-factors attacks on users' poorly-chosen passwords. This presents a security risk to the entire home or enterprise network. To mitigate this ongoing problem, we propose SecureArray, a system designed to operate alongside existing wireless security protocols, adding defense …

Arraytrack: A Fine-Grained Indoor Location System, Jie Xiong, Kyle Jamieson

Research Collection School Of Computing and Information Systems

With myriad augmented reality, social networking, and retail shopping applications all on the horizon for the mobile handheld, a fast and accurate location technology will become key to a rich user experience. When roaming outdoors, users can usually count on a clear GPS signal for accurate location, but indoors, GPS often fades, and so up until recently, mobiles have had to rely mainly on rather coarse-grained signal strength readings. What has changed this status quo is the recent trend of dramatically increasing numbers of antennas at the indoor access point, mainly to bolster capacity and coverage with multiple-input, multiple-output (MIMO) …

Energy-Efficient Continuous Activity Recognition On Mobile Phones: An Activity-Adaptive Approach, Zhixian Yan, Vigneshwaran Subbaraju, Dipanjan Chakraborty, Archan Misra, Karl Aberer

Research Collection School Of Computing and Information Systems

Power consumption on mobile phones is a painful obstacle towards adoption of continuous sensing driven applications, e.g., continuously inferring individual’s locomotive activities (such as ‘sit’, ‘stand’ or ‘walk’) using the embedded accelerometer sensor. To reduce the energy overhead of such continuous activity sensing, we first investigate how the choice of accelerometer sampling frequency & classification features affects, separately for each activity, the “energy overhead” vs. “classification accuracy” tradeoff. We find that such tradeoff is activity specific. Based on this finding, we introduce an activity-sensitive strategy (dubbed “A3R” – Adaptive Accelerometer-based Activity Recognition) for continuous activity recognition, where the choice of …