Jabed Faruque

RUGGED: routing on fingerprint gradients in sensor networks

Every physical event produces a fingerprint in the environment which results a natural information gradient in the proximity of the phenomenon. Moreover, many physical phenomena follow diffusion laws. In this paper, we propose a novel scheme to effectively exploit the natural information gradient to route a query in a sensor network. Our scheme uses multiple path exploration, and controls the instantiation of paths by simulated annealing. Unlike other information-driven protocols, our scheme eliminates the overhead of preparing and maintaining the gradient information repository. We apply our scheme to study three different problems: (1) single-value query, (2) global maxima search, and (3) multiple events detection. Simulation results have demonstrated that the routing protocol, based on our proposed scheme, is highly energy efficient and achieves over 98% success rate to route around sensor holes, even in the presence of environmental noise and malfunctioning sensor nodes. We also illustrate that our scheme is well suited for a broad-range of applications; e.g., time gradient based target tracking.

Analysis of gradient-based routing protocols in sensor networks

Every physical event results in a natural information gradient in the proximity of the phenomenon. Moreover, many physical phenomena follow the diffusion laws. This natural information gradient can be used to design efficient information-driven routing protocols for sensor networks. Information-driven routing protocols based on the natural information gradient, may be categorized into two major approaches: (i) the single-path approach and (ii) the multiple-path approach. In this paper, using a regular grid topology, we develop analytical models for the query success rate and the overhead of both approaches for ideal and lossy wireless link conditions. We validate our analytical models using simulations. Also, both the analytical and the simulation models are used to characterize each approach in terms of overhead, query success rate and increase in path length.

Gradient-based routing in sensor networks

A distributed sensor network (DSN) consists of sensor nodes with limited energy source, sensor devices, short-range radio and on-board processing capability. Sensing capability of the attached sensing devices and their small size, make these sensor nodes highly suitable for environmental monitoring. But characteristics of sensor nodes, e.g., expensive wireless communication, high probability of failure or malfunction and the unstructured nature of DSN, make routing in DSN a challenging problem. Traditional routing protocols in DSN are based mostly on flooding (Directed Diffusion[1]) or random-walk (Rumor routing [1], ACQUIRE [3], etc.). Flooding causes huge communication overhead due to frequent route discovery, especially for one-shot query and for large-scale networks. Though asymptotically, random-walk shows good performance, in practice it causes high latency and without directionality and proper TTL, sometimes fails to find resource. We note that many physical phenomena follow decay law. For example, if some location’s temperature is 100C, then nearby locations temperature should be correlated with that based on distance. So, routing protocols can use this natural gradient as an important attribute to forward the query towards source. A proactive informative driven protocol is proposed in [4] for querying and routing in sensor net. It uses proactive information utility measurement to select optimal node and guide query routing, which creates extra overhead at low query rate due to exchange of information between neighbors and leader. Also that protocol does not handle scenarios with local maxima or minima or multiple sources. To overcome these limitations, in this paper we propose a novel energy efficient, fully distributed and reactive routing protocol based on gradient of event’s effect for environmental monitoring sensor networks. Our protocol handles local and isolated maxima or hole of information using simulated annealing concepts.

Feature Matrices: A Model for Efficient and Anonymous Web Usage Mining

Recent growth of startup companies in the area of Web Usage Mining is a strong indication of the effectiveness of this data in understanding user behaviors. However, the approach taken by industry towards Web Usage Mining is off-line and hence intrusive, static, and cannot differentiate between various roles a single user might play. Towards this end, several researchers studied probabilistic and distance-based models to summarize the collected data and maintain only the important features for analysis. The proposed models are either not flexible to trade-off accuracy for performance per application requirements, or not adaptable in real-time due to high complexity of updating the model. In this paper, we propose a new model, the FM model, which is flexible, tunable, adaptable, and can be used for both anonymous and on-line analysis. Also, we introduce a novel similarity measure for accurate comparison among FM models of navigation paths or cluster of paths. We conducted several experiments to evaluate and verify the FM model.

TABS: Link Loss Tolerant Data Routing Protocol for Multi-hop Wireless Sensor Networks

Routing techniques of multi-hop wireless sensor networks try to mask low-power radio properties such as link asymmetry, unidirectionality and unreliability using different techniques like blacklisting, link reliability metrics etc. In addition to associated overhead, these approaches limit routing options. In this paper, we design a novel link loss tolerant data routing protocol, called TABS (Try-Ancestors-Before-Spreading), for multi-hop wireless sensor networks. TABS effectively combines the benefits of wireless broadcast advantages with traditional retransmission based routing while evades route explosion. Also, this protocol instantaneously adapts to network dynamics without periodic link quality maintenance. We evaluate the performance of TABS implementation using TinyOS on a 56-node 802.15.4 radio based test-bed. We analyze TABS performance on dense and sparse networks, and static and dynamic network topologies. TABS shows over 98% success rate to deliver packet between all pair of nodes. In addition, we compare the performance of TABS with that of hop-by-hop retransmission based routing, periodic link quality estimation based routing and the routing that exploits wireless broadcast advantages.

PBS: A virtual grid architecture for gradient-based active querying in sensor networks

Every physical event diffuses its effect geographically, which results in perceivable information gradient within the proximity of the phenomenon. In this paper, we propose a novel framework for on-demand query processing that exploits this diffusion property to form a virtual grid-based querying architecture, probe-before-spray (PBS), for wireless sensor networks. PBS effectively divides the sensor field on-demand based on the query type and parameters in addition to the gradient spread. Also, it combines gradient routing and in-network processing for efficient and scalable querying in sensor networks. Based on PBS, we design new algorithms to process basic aggregate queries - count, sum, average, max and min, and combined queries. Through analysis, we analyze the worst-case overhead to process these queries using PBS. Also, using extensive simulations, we demonstrate that PBS helps to reduce search overhead significantly (over 30%) to process such queries while attaining accuracy over 99%.