Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks by Sagayam K. Martin

Author:Sagayam K. Martin
Language: eng
Format: epub
Publisher: Information Science Reference

In information gathering phase, when the portable sink reaches every RP/SRP each time, chooses whether to request for tree-rebuilt based on the remaining power proportion of its single-bounce closest hub. If it meets the constraints, the intended RP/SRP make the request to the portable sink after it comes. At last, the sink determines about tree rebuilt according to the based on the quantity of requests to the number of RPs and SRPs.

Figure 3. Flowchart of SCBDCA scheme

The flowchart of SCBDCA algorithm is shown in figure 3. Initially consider a homogeneous network with 50 nodes. The nodes are clustered depending upon the geographic location of the nodes. Once the nodes are clustered, CH is selected based on the remaining power and the utilization of the node to its nearby hubs. To balance the data gathering latency, a mobile sink is introduced in each zone to see all CH of that zone for data collection. The new algorithm introduced in this paper is the speed control mechanism which is mainly used to control the speed of the portable sink. The remoteness among the portable sink and CHs are calculated and the average distance is taken as the threshold. If the distance is found to be exceeding the fixed limit, increase the speed of the mobile sink else the speed is decreased or adjusted accordingly depending upon the distance.

Algorithm of SCBDCA Scheme:

For the mobile sink (MS)

if distance > threshold

increase speed

else

decrease speed

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