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Top1. Introduction
Wireless sensor networks (WSN) is a network of spatially distributed physical sensors which sense the data like temperature, moisture, pressure etc. This ability of sensors is used in wide range of applications like forest fire detection, medical monitoring pollution monitoring and agriculture surveillance (Bruckner, Picus, Velik et al., 2012). There is a long history of using sensors in medicine and public health. Due the recent evolutions in electronics, it is highly economical to get the low cost, lightweight multipurpose sensors which can be integrated to use in different applications. Wireless sensors have limitations such as Non rechargeable battery power, Low computation ability, Limited memory storage and No standard platform (El Emary, & Al-Gamdi, 2014; Hamid, Harouna, Salele et al., 2013).
WSN consists of battery powered small devices which are capable of acquiring physical information from environment, processing of information and forwarding the collected information to the required destination. Application which involve multimedia data often act as sensor-actor network in which scalar sensors collects the environmental information and depending upon the environmental parameters the multimedia nodes are switched On or OFF. The multimedia nodes can be operated in sleep/awake mode as per requirement. This way is efficient way in terms of energy saving and lifetime improvement of the network (Ekleitis, Meger, Dudek, 2006).
Figure 1. Wireless Camera Sensor Network (WCSN)
Figure 1 shows architecture of Wireless Camera Sensor Network (WCSN). WCSN is constructed by a set of small and low cost sensor nodes which can produce images or videos from the sensing area. The images are then processed and transmitted to other sensors or to a central base station. The base station and the sink node in the architecture shown are static and the nodes in sensor field can be static or mobile as per application.
WCSN are widely used in various fields such as battlefield visual monitoring, environment monitoring, safety monitoring, person locator services, traffic monitoring, intelligent home, and medical treatment and public healthcare.
Pure static networks face problems due to dynamic changes of events and unpredictable environmental change in the network. Some of the challenges for static network are (Rezazadeh, 2012):
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Initial deployment of the network would not give full coverage and connectivity of the network. The randomly deployed networks may get divided into small non-connected networks. This may degrade the performance of the application.
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As sensor node are battery operated those may deplete their energy after some time and energy holes may be created in the network which will result in unconnected sensor field.
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More no of node are required in case of object tracking kind of applications. No. of nodes can be reduced if some nodes are capable of relocating themselves as per network and application requirement.
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Addition and movement of some specialized node will increase the scope of the application. For some applications it is feasible to add or remove nodes as per time schedules and tracking requirements from the network.
In military applications the scenario can be developed in which the mobile nodes act as sink node or data collector node, which collects the information from other nodes which are stationary nodes. In such cases sparsely deployed node will also be able to communicate. In smart city applications not only sink node but the sensor nodes will also be moving. In target tracking scenario combination of static and mobile nodes can be used effectively. Applications explain above consist of the movement of node which is unpredictable. The traditional algorithms for deployment, duty cycle scheduling and routing needs improvement.
Following are type of mobility which can be applied to the applications described previously.