Projects @ SMU

Understanding Uncertainty in Event Driven Experimentation

The wide spread use of smart phones has ushered in a wave of context-based advertising services that operate on predefined user events. A prime example is Location Based Advertising. What is missing though, is the ability to experiment with these services under varying event conditions with real users using their regular phones in real-world environments. Such experiments provide greater insight into user needs and behaviour towards context-based advertising applications. However, these event-driven experiments rely on data that arrive from sources such as mobile sen sors which have inherent uncertainties associated with them. This effects the interpretation of the outcome of an experiment. In this paper we introduce Jarvis, a behavioural experimentation platform that supports running in-situ real-time experiments of mobile advertising services, targeting real participants on their smart phones based on multiple context-specific events. We highlight the challenges of handling uncertainty on such a platform as well as how we deal with ambiguity in the location attribute

Barometric Phone Sensors – More Hype Than Hope!

The inclusion of the barometer sensor in smartphones signaled an opportunity for aiding indoor localization efforts. In this paper, we therefore investigate a possible use of the barometer sensor for detecting vertically oriented activities. We start by showing the accuracies of various commodity measurement devices and the challenges they bring forth. We then show how to use the barometer values to build a predictor that can detect floor changes and the mode (elevator, escalator, or stairs) used to change floors with nearly 100% accuracy. We validate these properties with data collected using 3 different measurement devices from 7 different buildings. Our investigation reveals that while the barometer sensor has potential, there is still a lot left to be desired.

Where Am I?: Studying Users’ Indoor Navigation Location Needs

Location has emerged as the single-most important context whilst building pervasive mobile applications. Several mobile applications have appeared that use location to provide a host of services such as location-specific advertising as well as navigation. As a result, the key challenge of positioning techniques has been to provide the most precise location of the user (device) and much effort has been put in  computing this fine grained location in indoor environments. This is under the assumption that highly accurate location is crucial for all  indoor services. To understand the location accuracy, that should prove sufficient, for users to navigate to a specific store in a mall, we conducted a user study that mimicked the mall-like setting in two university buildings. Our results suggest that for navigating indoors in mall-like settings, users do not require highly accurate location awareness.

myDeal: The Context-Aware Urban Shopping Assistant

A common problem in large urban cities is the huge number of retail options available. In response, a number of shopping assistance applications have been created for mobile phones. However, these applications mostly allow users to know where stores are or find promotions on specific items. What is missing is a system that factors in a user’s shopping preferences and automatically tells them which stores are of their interest. The key challenge in this system is twofold; 1) building a matching algorithm that can combine user preferences with fairly unstructured deals and store information to generate a final rank ordered list, and 2) designing a mobile application that can capture user preferences and display deal information to the user in an intuitive way. In this paper, we present myDeal, a system that automatically ranks deals according to user preferences and presents them to the user on their mobile device.

Keystroke Biometrics: the User Perspective

Usability is an important aspect of security, because poor usability motivates users to find shortcuts that bypass the system. Existing studies on keystroke biometrics evaluate the usability issue in terms of the average false rejection rate (FRR). We show in this paper that such an approach underestimates the user impact in two ways. First, the FRR of keystroke biometrics changes for the worse under a range of common conditions such as background music, exercise and even game playing. In a user study involving 111 participants, the average penalties (increases) in FRR are 0.0360 and 0.0498, respectively, for two different classifiers. Second, presenting the FRR as an average obscures the fact that not everyone is suitable for keystroke biometrics deployment. For example, using a Monte Carlo simulation, we found that 30% of users would encounter an account lockout before their 50th authentication session (given a lockout policy of 3 attempts) if they are affected by external influences 50% of the time when authenticating.

Projects @ NUS

SpyderMesh: An Unplanned Dual-Radio Wireless Mesh Network (Link) - Last accessed 2016

NUS wireless mesh network is an experimental outdoor testbed deployed in Prince George Park Residences (PGPR) in Kent Ridge campus of NUS. PGPR is a typical urban environment in Singapore, with many high-rise buildings (more than 10 storeys),that are not friendly to the transmission of wireless signals. There are currently 20 mesh nodes in our mesh network, occupying 20 residential blocks in PGPR. Each node has two Wi-Fi adapters (11abg) with antennas fixed onto the building wall. About half of these nodes reside at floor 7 and others at floor 3 and floor 10. Thus the network topology is a 3-dimensional one.

The research work focused on the following aspects of wireless mesh networks:

• Characterization of wireless signal transmission in dense urban environment.

• Dual-radio routing algorithms

• TCP fairness in wireless mesh networks.

• Adjustable Wi-Fi antenna orientation.

• Power control and topology control.

Photo Credit: Eugene Chow

Projects @ Infosys

As part of the pervasive computing research initiative at SETLabs, I was focusing on two research areas. The first was in the enterprise mobility domain where the focus was on developing smart mobile applications, applications that are aware of their operating environment (power, connectivity, memory and so on) and are capable of adapting to the same. The second was pervasive and wireless computing where the focus was on seamless migration of user/task context from one computing environment to another as well as leveraging computing capabilities in a smart environment. I was also doing interesting work in peer-to-peer communication in 802.11 networks in seeing how information exchanged between the peers can assist in some form of proactive guidance. Below are some of the research projects I was leading and part of

Nimbus: A context aware computing paradigm

The system is designed to automatically detect and manage an end user’s computing tasks in a seamless way as the user moves from one computing device to another. Embodying the concepts of a context carrier (a mobile device like a mobile phone or a PDA) as well as virtual identities, the system gives the user the flexibility to not only continue working on a given task irrespective of the computing device (of course within the constraints of the computing device and the nature of the task), but to also remotely manage certain tasks using a mobile device. The system is context aware and resumes old tasks by taking advantage of available resources.

Smart Environments

Smart environments of tomorrow will be populated by different kinds of computing devices with varying processing capabilities, energy resources, memory capacity and different ways of interacting with users. Handheld devices such as mobile phones or PDA's, RFID enabled consumer products and wall sized displays are likely to play a role in future smart environments. One core challenge on smart environments is therefore to exploit their heterogeneity by building applications that make use of and combine the specific capabilities provided by different types of computing devices.

IRIS

Resource discovery in networks pertains to the ability to discover and extract services available directly from the network. Traditional resource discovery is a static process. One cannot even begin to imagine doing fancier things, like delegate document to "least loaded printer", or "closest color printer" etc. Resource discovery is usually housed in the network layer, wherein application specific metrics simply cannot be captured. We propose IRIS: Intentional Resource Indicator Service, which springs from the concept that end users should not be bogged down with network names when looking for a resource. They should be able to express more with natural languages what they want rather than where to go get it.

mConnect

Enterprises are aggressively eyeing mobile ubiquitous solutions. But ubiquitous mobility comes with numerous functional as well as technical challenges. One faces a wide range of devices with differences in underlying platforms, platform capabilities, application/browser support, available screen real estate, input mechanisms, connectivity, and deployment issues. Typically, application content has to be adapted according to the form factor and size of the devices in use. As the heterogeneity of target mobile devices increases, adapting the content to support all the devices is a daunting task. Also the content has to be adapted to the appropriate format (for example html, wml etc.) supported by the device.  mConnect is a mobile middleware platform aimed to manage this mobile device diversity in an efficient manner. It handles the multiplicity of form factors and access mechanisms on multiple devices to provide a context agnostic view to the 'Transaction (back end)' server. This middleware provides a unique user interface on each hand held by properly identifying the device capabilities to access the services offered by the transaction server.

TruMobile

Tackles several key mobile technology issues like intermittent network connectivity, constrained device resources (memory, processing power, battery power), diversified device capabilities (form factor, display size, etc.), content adaptation, etc. Our vision is to eventually merge these different research outcomes to develop a comprehensive mobile application framework and middleware.

Location Based Services

Location Based Service is the capability to find the geographical location of the mobile device and then provide services based on this location information. Enterprises are finding that it is easier to realize value by exploiting LBS with their employees than selling LBS enabled services to consumers. This research project aims at how LBS solutions can be incorporated within the enterprise where information is availed to the user via broadcast mechanism.

BOWL (Broadcast over Wireless LAN)

BOWL is a wireless broadcast technology that enables devices with a simple software upgrade to wirelessly communicate without the need for an inherent connected communication system. We take advantage of the wireless media to piggyback fragmented messages over standard beacon frames, thereby creating a low data rate truly connectionless broadcast stream. The scheme supports multiple logical channels over this broadcast channel, without compromising the reliability or robustness of the system. In essence, our system leverages the broadcast nature of the control channel thereby providing for parallel short connectionless data transfer streams.