Dealing Data From Sensors Network PPT Presentation OverView:

A sensor network can communicate and collect the data string continuously to the database. The term real life application means monitoring the physical phenomena like concentration of contaminants, climate, structures of building earthquake responses and others. It functions like black boxes that can record the data,  its diagnostic and performance as well as history. For example: computers, cell phone and vehicles.

The technique of data gathering use the network primitives techniques of cleaning the data like querying about noise data, cleaning of noisy data, discovering the outlines and handling data that are incomplete due the erroneous sensors and missing values.

There are certain limitations like:

Low battery life

The capabilities of processing and storing enforce the handling of special data algorithms and architectures for streams of sensor data that incorporate explicitly these constraint resources. Sensors can construct and maintain a local consistent, view of its neighborhood. There are two approaches for in-network aggregation: TAG or tiny aggregation service for sensor network ad hoc. It includes aggregation for monitoring the wireless network sensors.

Query network

Distribution phase. To each and every node in the network the query is distributed and a tree that is rooted at the base parents. In the collection phase the parents gather data from their children at specific period of time intervals.

The process of routing enables to deliver the requests of query to every individual node. It provides from every node, one or two routes to the base root. Specifically it uses a based tree for the rating where only one route is not the root. TAG reduces dramatically and in turn lead to decreases in the communication process and also yields reduction in the order of magnitude from the aspect of the cost of communication in comparison to the centralized approach. There are many common networks in the sensors like link asymmetry and heavy packet loss.

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