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Bypassing Holes in Sensor Networks: Load-Balance vs. Latency

This work addresses the problem of geographic routing in the presence of holes or voids in wireless sensor networks. We postulate that, once the boundary of the hole has been established, relying on the existing algorithms for bypassing it may cause severe depletion of the energy reserves among the nodes at (or near) that boundary. This, in turn, may soon render some of those nodes useless for any routing (and/or sensing) purposes, thereby effectively enlarging the size of the pre-existing hole. To extend the lifetime of the nodes along the boundary of a given hole, we propose two heuristic approaches which aim at relieving some of the routing load of the boundary nodes. Towards that, our approaches propose that some of the routes that would otherwise need to bypass the hole along the boundary, should instead start to deviate from their original path further from the hole. Our experiments demonstrate that the proposed approaches not only increase the lifetime of the nodes along the boundary of a given hole, but also yield a more uniform depletion of the energy reserves in its vicinity.

Managing evolving shapes in sensor networks

This work addresses the problem of efficient distributed detection and tracking of mobile and evolving/deformable spatial shapes in Wireless Sensor Networks (WSN). The shapes correspond to contiguous regions bounding the locations of sensors in which the readings of the sensors satisfy a particular threshold-based criterion related to the values of a physical phenomenon that they measure. We formalize the predicates representing the shapes in such settings and present detection algorithms. In addition, we provide a light-weight protocol and aggregation methods for energy-efficient distributed execution of those algorithms. Another contribution of this work is that we developed efficient techniques for detecting a co-occurrence of shapes within a given proximity from each other. Our experiments demonstrate that, when compared to the centralized techniques -- which is, predicates being detected in a dedicated sink -- as well as distributed periodic contours construction, our methodologies yield significant energy/communication savings.

Efficient detection of motion-trend predicates in wireless sensor networks

This work addresses the problem of efficient distributed detection of predicates capturing the motion trends of mobile objects evaluated with respect to a (boundary of a) polygonal region, in the settings in which the (location, time) data is obtained via tracking in Wireless Sensor Networks (WSN). Specifically, we discuss in-network distributed algorithms for detecting two motion-trend predicates: Continuously Moving Towards and Persistently Moving Towards: first for a single object, and then the corresponding variants for multiple objects. We also present methodologies which consider the energy vs. latency trade-offs when multiple tracked objects are being considered for validating the monitored predicates. Our experiments demonstrate that our proposed technique yield substantial energy savings when compared to the nave centralized and cluster-based approaches in which the raw (location, time) data is transmitted to a dedicated sink where the predicates are being evaluated.

Privacy-Preserving Detection of Anomalous Phenomena in Crowdsourced Environmental Sensing

Crowdsourced environmental sensing is made possible by the wide-spread availability of powerful mobile devices with a broad array of features, such as temperature, location, velocity, and acceleration sensors. Mobile users can contribute measured data for a variety of purposes, such as environmental monitoring, traffic analysis, or emergency response. One important application scenario is that of detecting anomalous phenomena, where sensed data is crucial to quickly acquire data about forest fires, environmental accidents or dangerous weather events. Such cases typically require the construction of a heatmap that captures the distribution of a certain parameter over a geospatial domain (e.g., temperature, \({\text {CO}}_{2}\) concentration, water polluting agents, etc.).

Motion Trends Detection in Wireless Sensor Networks

We address the problem of efficient detection of destination-related motion trends in Wireless Sensor Networks (WSN) where tracking is done in collaborative manner among the sensor nodes participating in location detection. In addition to determining a single location, applications may need to detect whether certain properties are true for the (portion of the) entire trajectories. Transmitting the sequence of (location, time) values to a dedicated sink and relying on the sink to detect the validity of the desired properties is a brute-force approach that generates a lot of communication overhead. We present an in-network distributed algorithm for efficient detecting of the Continuously Moving Towards predicate with respect to a given destination that is either a point or a region with polygonal boundary. Our experiments demonstrate that the proposed approaches yield substantial savings when compared to the brute-force one.

Tracking Coverage throughout Epochs with Bounded Uncertainty

This work addresses the problem of managing the sensor-coverage and organizing the epochs in a manner that balances the trades-offs between the accuracy and energy consumptions during target tracking in Wireless Sensor Networks (WSN). While the typical target tracking approaches are based on movement prediction, we only assume a knowledge of some maximal speed of the target during certain time-intervals. This, in turn, restricts its whereabouts to a disk-bound area throughout such intervals. In such settings, we seek to determine a sensor cover, a subset of all the nodes that need to be awake, which ensures that the target can be detected during the given epoch. Towards this, we propose sensor-cover selection methodologies, Greedy Uncertain Moving Object coverage sensor set selection (GUMO) and PAttern Based coverage sensor set selection (PAB). GUMO is a heuristic maximizing the coverage gain at each step, while PAB is an approach based on optimal deployment pattern of sensor nodes achieving coverage of the disk area bounding the targets whereabouts. We conduct extensive simulations to evaluate the performance of the algorithms, and the results reveal that GUMO and PAB not only provide substantial energy saving due to reduction in the communications involved in selecting tracking participant-nodes and principal(s), while assuring a bounded error on the targets location.

Bypassing holes in sensor networks

This work addresses problems that arise when geographic routing is used in the presence of holes in wireless sensor networks. We postulate that relying on the existing algorithms for bypassing a coverage hole may cause more severe depletion of the energy reserves among the nodes at (or near) that holes boundary. This, in turn, will render some of those nodes useless for any routing (and/or sensing) purposes, thereby effectively enlarging the size of existing hole and inducing longer communication delays for certain (source, sink) pairs. We propose heuristics that address these complementary problems: (1) relieving some of the routing-load for the nodes around the boundary of a given hole, for the purpose of extending their lifetime; and (2) reducing the latency of the packets-delivery by using routes that are within certain bounds from the route based on the shortest-path. Our approaches are based on the idea that some of the packets that would (otherwise) need to be routed along the boundary of a given hole, should instead start to deviate from their original path further away from that hole. To investigate the potential benefits, we introduce approximations of the holes boundary with a rectangle, a circle and an ellipse, respectively. We derive the bounds on reducing the routing latency for these three approximations. Our experiments demonstrate that the proposed approaches not only increase the lifetime of the nodes along the boundary of a given hole and yield a more uniform depletion of the energy reserves in its vicinity, but also reduce the communication latency, compared to the traditional face routing.

Semantics-Aware Warehousing of Symbolic Trajectories

We address the problem of extending the querying capabilities of Trajectories Data Warehouses (TDW) for symbolic trajectories, by introducing Semantic Relatedness (SR) as part of the formal model. This enables capturing the similarity between different annotations describing Points of Interest (POI), locations and activities. We formally define the inclusion of the relationship between different terms used as descriptors in symbolic trajectories and present the Semantic Relatedness in Trajectories Data Warehouse (SR-TDW) model. We introduce newly enabled queries in the SR-TDW model and illustrate the impacts of the added functionality. Our experiments demonstrate the benefits of the proposed approaches in terms of enriching the answer-sets for the common OLAP-based queries, and the sensitivity in terms of the various measures of semantic similarity.

Evolving shapes in wireless sensor networks

We present an implementation of a system for managing evolving shapes in Wireless Sensor Networks (WSN). A shape is a contiguous region in which the measurements of the sensors detect values above a given threshold. Our system, in its current version, solves two important problems: (1) Detecting and tracking the changes of boundaries; (2) Detecting an occurrence of within distance predicate for two (or more) shapes. A centralized approach (transmitting raw measurements to a dedicated sink) incurs communication overhead, so we developed distributed algorithms for managing the predicates related to evolving shapes. This demo will present the implementation of our solutions in a heterogeneous WSN consisting of TelosB and SunSPOT motes. It will also illustrate the end-user tools: interface for specifying the parameters of the predicates, along with real-time visualization of their evaluation.

Distributed data management for large-scale wireless sensor networks simulations

We tackle two important problems that arise in simulation-based studies of various data-related properties in the context of Wireless Sensor Networks (WSNs): (1) reducing the turnaround time for completing the simulations in a large-scale parameter space; (2) providing database functionalities for a more detailed insight into the simulations evolution. Towards these goals, we have developed the DiSSIDnet (<u>Di</u>stributed <u>S</u>ystem for <u>S</u>imulation and <u>I</u>ntegrated <u>D</u>evelopment for Wireless Sensor <u>Net</u>works). Leveraging upon our earlier works on the SIDnet-SWANS tool [3], DiSSIDnet not only provides the ability of a synchronized execution of the simulations in a distributed environment, but also maintains the simulation data over the parameter-space in a relational database. In addition to post-simulation queries that can be posed to the database, we also provide the feature of specifying triggers that can generate notifications upon detecting certain events of interest during the simulation process.