Abstract: In wireless sensor network, sensor node transmits the
sensed data to the sink node in multi-hop communication
periodically. This high traffic induces congestion at the node which is
present one-hop distance to the sink node. The packet transmission
and reception rate of these nodes should be very high, when
compared to other sensor nodes in the network. Therefore, the energy
consumption of that node is very high and this effect is known as the
“funneling effect”. The tree based-data aggregation technique
(TBDA) is used to reduce the energy consumption of the node. The
throughput of the overall performance shows a considerable decrease
in the number of packet transmissions to the sink node. The proposed
scheme, TBDA, avoids the funneling effect and extends the lifetime
of the wireless sensor network. The average case time complexity for
inserting the node in the tree is O(n log n) and for the worst case time
complexity is O(n2).
Abstract: This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.