Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network

Algorithm 4

On-demand mobile sink traversal [ODMST].

Step 1. Obtain Cluster heads by executing Algorithm 3 (RLBCA).

Step 2. Initially mobile sink placed randomly. Mobile sink advertise his position to all cluster heads.

Step 3. Interested cluster heads sends their request to visit message packet to mobile sink.

Step 4. Mobile sink stores these received messages in routing table to calculate distance (as per equation (4)) and visit

cluster head to collect the data.

Step 5. If multiple request messages are received by mobile sink then

Step 5.1. Mobile sink calculates distance of SNs as per the equation (4) and store them in routing Table 1.

Step 5.2. Mobile sink creates the traversal path as per shortest distance and execute it.

Step 5.3. During this execution of mobile sink traversal, if again any cluster heads send their request

message then mobile sink used to calculate the shortest distance, update the traversal path and execute it.

Step 6. Go to step 3.