Research

My main research interests are in the areas of databases and networks. In particular, my focus has been on data management in wired/wireless sensing networks that often become basis for streaming databases. Features selection from high dimensional data, classification, localization, tracking, and access control are some of the important problems that I deal with in my research. These problems are inherently different in nature, yet related to each other due to sustainability and reliability issues. Consider e.g., wireless sensor networks that irrespective of any particular applications require sepcialized techniques to operate in an energy constrained and inheretnly unreliable wireless network for sustaining longer network lifetime. In some sensing networks that are more robust, e.g., Automatic Identification System (AIS) used by maritime vessels, sustainability may take a biform that is different than just being energy efficient. Multiple AIS devices (installed on various vessels) can be connected in a network system that can provide operational and analytical services through the Internet. However, such a system will need access control policies, without which it may jeopardize navigation safety and privacy concerns, and hence the system may become unsustainable. Following are the brief summaries of the research projects that deal the issues described above.

Data Management in Sensing Networks

  • Biased Shortest Path Trees in Wireless Networks.[IEEE IPCCC 2011] pdf

    Broadcasting is an elementary problem in wireless networks. Energy-efficient broadcasting is important, e.g., to coordinate the distributed computing operations by sending periodic messages in a network of Automatic Identification System installed on energy constrained maritime lighthouses. To that end logical tree topologies that are based on Connected Dominating Sets have been proposed vigorously in the literature. In this work, we present Biased Shortest Path Tree (BISPT), a new logical tree topology for efficient broadcasting in wireless networks. In simulations we find that BISPT outperforms state-of-the-art solutions.

  • ASSIST: Access Controlled Ship Identification Streams.[ACM GIS 2011] pdf

    The International Maritime Organization (IMO) requires a majority of cargo and passenger ships to use the Automatic Identification System (AIS) for navigation safety and traffic control. Distributing live AIS data on the Internet can offer a global view based on ships' status for both operational and analytical purposes to port authorities, shipping and insurance companies, cargo owners and ship captains and other stakeholders. Yet, uncontrolled, this distribution can seriously undermine navigation safety and security and the privacy of the various stakeholders. In this paper we present ASSIST, a system prototype based on our recently proposed access control framework, to protect data streams from unauthorized access. We demonstrate the effectiveness of the system in a real scenario with real AIS data streams.

  • Exact Top-K Queries in Wireless Sensor Networks.[IEEE TKDE 2011] pdf

    In this work we considered the exact top-k query problem in wireless sensor networks, i.e., where one seeks to find the k highest reported values as well as the complete set of nodes that reported them. Our primary contribution in this context is EXTOK, a provably correct and topology-independent filtering-based algorithm for processing exact top-k queries. We examine EXTOK's performance with respect to a number of parameters and different logical tree topologies while using both synthetic and real data sets. Our simulation reveal that EXTOK consistently outperforms the current state-of-the-art algorithm by a very significant margin and regardless of the underlying logical tree topology.

  • Aggregation Convergecast Scheduling in Wireless Sensor Networks.[WINET 2011] pdf

    In this work, we considered the problem of scheduling in wireless sensor networks for the purposes of aggregation convergecast. We observe that existing schemes adopt essentially a two phase approach, consisting of, first, a tree construction and, second, a scheduling phase. Following a similar approach, we propose two new improvements, one to each of the two phases. Starting with a new lower bound on the schedule length, we make use of it in the tree construction phase. The tree construction phase consists of solutions to instances of bipartite graph semi-matchings. The scheduling phase is a weight-based priority scheme that obeys dependency (tree) and interference constraints. Our extensive experiments show that, overall, our proposed solution not only outperforms all previously proposed solutions in terms of schedule length, but it also significantly extends the network's lifetime.

  • Distributed classification of Acoustic Targets in Wireless Audio-Sensor Networks.[COMNET 2008] pdf

    Target tracking is an important application for wireless sensor networks. One important aspect of tracking is target classification. Classification helps in selecting particular target(s) of interest. In this project, we addressed the problem of classification of moving ground vehicles. The basis of classification are the audible signals produced by the vehicles. We present a distributed framework to classify vehicles based on features extracted from acoustic signals of vehicles. The main features used in our study are based on FFT (fast Fourier transform) and PSD (power spectral density). We propose three distributed algorithms for classification that are based on the k-nearest neighbor (k-NN) classification method. An experimental study has been conducted using real acoustic signals of different vehicles recorded in the city of Edmonton. We compare our proposed algorithms with a naive distributed implementation of the k-NN algorithm. Performance results reveal that our proposed algorithms are energy efficient, and thus suitable for sensor network deployment.

  • Path-Adaptive On-Site Tracking in Wireless Sensor Networks.[IEICE 2006] pdf

    In this work we characterized the on-site tracking in which a mobile sink is eventually required to be present in the vicinity of the target, possibly to perform further actions. We propose two efficient on-site tracking algorithms. We derive theoretical upper bounds for the tracking time and the number of messages generated by the sensors during the tracking. We conducted a simulation study to evaluate the performance of our algorithms. The results show that our algorithms are efficient as compared to the existing methods that can solve the on-site tracking problem. In particular, the path adaptive nature of the sink in our algorithms allows the network to conserve the energy and the sink to reduce the tracking time.