NEW APPLICATIONS ENABLED BY HETEROGENEOUS WSNs in VS .NET

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Figure 2.14. Sensor management ow chart.
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analytical techniques may reinforce each other. A standard format is developed to facilitate the interoperability of diverse sensors. Management of the WSN may also help network scalability. In reference 38, G rgen et al. propose a hybrid approach offering scalable solutions that combine u the advantages of both centralized and distributed data stream management. Their main concern is the querying and system management of large sets of sensors. In the heterogeneous WSN considered, diverse types of sensor nodes are used, each with a different data delivery rate. A three-stage architecture is proposed for distributed evaluation of queries on the network: sensor nodes, gateway, and control site. In the architecture, the load of query evaluation is distributed between stages. A mediatorwrapper [39] is applied at the gateway stage to serve as local query translator and optimizer. The wrapper proposed is an approach for heterogeneous sensor data management and provides an integrated global view of the different types of sensor. With the help of this three-stage management scheme, the query load is distributed; also, the burden at each stage is decreased. Hence, the scalability of the network is improved by manipulating the query in the heterogeneous WSN.
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2.6 NEW APPLICATIONS ENABLED BY HETEROGENEOUS WSNs Using a homogeneous WSN may not satisfy the requirements of an application [40]. The following two applications are examples requiring a heterogeneous WSN.
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HETEROGENEOUS WIRELESS SENSOR NETWORKS
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The ability to reliably deliver a large volume of data has opened a new range of applications for heterogeneous WSNs. This includes audio/video surveillance and the monitoring of telemetry data. Yuan et al. [40] consider a new live virtual reality application. The idea is to provide a user with live real-time video of a monitored sensor eld together with the ability for the user to navigate virtually within the eld. One example is that of a heterogeneous WSN deployed for securing a building, where a console operator can survey a building using a joystick for navigation. Gnawali and Yarvis [41] propose a do not disturb application requiring a heterogeneous WSN. The purpose of this application is to alert people to keep the noise down in an of ce environment when there are people working in a nearby area. A do not disturb WSN consists of nodes with motion and sound sensors. Motion detectors determine the occupancy status of a cubicle. Sound sensors in cubicles measure the loudness of the sound heard in each cubicle. Sound sensors in the hallways pick up the noise of impromptu hallway meetings. The do not disturb application determines the source of the noise by data fusion; this requires CPU and memory resources typically not available in sensor nodes. Figure 2.15a shows two types of sensor node deployed in an of ce environment, as well as actuators to alert people when it is too noisy; the network topology that corresponds to the deployment is shown in Figure 2.15b. The use of heterogeneous nodes allows a distributed architecture using ad hoc deployment that is resilient to failure and has lower cost. In addition to the motion and sound sensors, a sensor with more powerful processing ability is required. This is where the motion and sound data are sent for processing and analysis, to determine whether an actuator signal is needed. As a result, the successful transmission rate increases, and delay decreases signi cantly. Moreover, as the network grows and computational demand increases, more high-end sensor nodes can be added in the network. 2.7 SUMMARY OF PROJECTS AND SYSTEMS INFRASTRUCTURE 2.7.1 Summary of Heterogeneous WSN Projects A summary of heterogeneous WSN projects is given in Table 2.1. 2.7.2 Systems Infrastructure for Heterogeneous WSNs A summary of systems infrastructure for heterogeneous WSNs is given in Table 2.2. 2.8 OPEN PROBLEMS Research in heterogeneous WSNs is in its infancy and is therefore rich in open problems. Some of them include: Inadequate Theory of Heterogeneous WSNs. Most of the models assume that a heterogeneous WSN provides data that are clock-driven (or periodic).
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