Abstract-An interplay between mobile devices and static sensor nodes is envisioned in the near future. This will enable a heterogeneous design space that can offset the stringent resource and power constraints encountered in traditional static sensor networks by taking advantage of the more powerful mobile devices. We present a systematic framework for end-to-end query processing, using a two-layer architecture that consists of mobile devices at the upper layer and static sensor nodes at the bottom layer. The framework employs a "PULL" query model that contains staged operations including query generation, query routing, query injection, and query result routing. Each of these stages of query processing is discussed with an emphasis on techniques for energyefficient query injection and query result routing with location-ignorant sensor nodes. The techniques leverage the mobility and transmission flexibility of mobile objects at the upper layer. Numeric and simulation results are provided to support the proposed methods.Index Terms-mobile objects, opportunistic query processing, sensor networks. INTRODUCTIONStringent power constraints and limited computation and communication capabilities are key issues in the development of sensor networks. For example, a Berkeley Mote powered by two AA batteries can operate for about one year in the idle state, but only one week when fully loaded. In addition, large-scale sensor network applications impose a demand for cheap, small, lowpower sensor nodes, making it impractical to equip sensor nodes with GPS-receivers. While various localization techniques are evolving [1], localization for very large-scale sensor networks is still in the research stage, especially when there is the need to obtain accurate location information under restrained energy conditions. Thus, we focus on location-ignorant sensor networks, which impose challenges on various aspects for query processing in the network, including both query routing and results gathering.In contrast to sensor networks, mobile wireless networks have much relaxed power constraints. Various communication technologies, including Cellular, Wi-Fi, WiMAX, and Bluetooth, have been developed for connecting billions of electronic products, such as PDAs, cell phones, laptops, and cars. Moreover, GPS-receivers are reasonably affordable on such mobile devices. We observe that a heterogeneous design space consisting of both static sensor nodes and mobile devices can successfully offset the stringent resource and power constraints in traditional sensor networks. Such an interplay between mobile (ad hoc) networks and sensor networks also links the mobile devices as query requesters and data consumers directly to sensor networks that are responsible for sensing the physical world. We propose a framework for query processing that is based on the "PULL" query model [2] [3] in a two-layer network structure, including a mobile network at the upper layer and a wireless sensor network at the bottom layer. Hereafter, the term "mobile objects" refe...
To facilitate flexible data discovery, sensor networks can be supported by query processing, where a query is injected into the sensor network from some base station. In his paper we consider the problem of query injection by base stations that are mobile (mobile objects) and individual sensors are "location-ignorant." The idea is to have mobile objects take advantage of each other's independent motion plans to do a form of opportunistic query injection. We discuss methods to optimize query injection in terms of optimal injection points and transmission ranges. Numerical simulations on coverage rate metrics are provided to support the proposed methods. Index Terms: mobile object, query injection, sensor networks.
Abstract-an interplay between mobile devices and static sensor nodes is envisioned in the near future. This will enable a heterogeneous design space that can offset the stringent resource and power constraints encountered in traditional static sensor networks by taking advantage of the more powerful mobile devices. As such, we present a systematic framework for end-to-end query processing, using a two-layer architecture that consists of mobile devices at the upper layer and static sensor nodes at the bottom layer. One of our key goals is to achieve energy-efficient query injection and data collection by leveraging the mobility and transmission flexibility of objects at the upper layer. We propose a pull query model that contains staged operations including query generation, query routing, query injection, and query result routing. In the context of this model, we investigate a suite of techniques for the scenario with location-ignorant sensor nodes.Index Terms-mobile objects, query processing, sensor networks.
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