(20 pts) Consider the study of replica voting algorithm you had done as part of the first warm-up project. For an extended analysis, Figure 4 shows the key performance results of the voting algorithms. The performance parameters are the time to deliver a data to the end-user (TTC). the number of distinct data proposals before effecting a data delivery, and the control message overhead expended to deliver a data. One of the influential parameters is the fault severity of a mis-behaving voter: denoted as a parameter r, where r is the probability that a faulty device does in fact behave incorrectly. For e.g., r=0.1 means that a faulty device X behaves incorrectly only for 10% of the times X participates in the algorithm operations - which means that X behaves correctly for 90% of the times. The results are shown for a case of r=0.5. Empirically plot the results for two other cases: r=0.2 and r=0.75. Show the plots on top of the results given for r=0.5. \# 10; data size =30 kbytes fm : \# of faulty devices \# of YES votes needed =6; (Tc)=50mec;(Tc)=50msec; control message: 50 bytes Tc : voter computation time Figure 4: Experimental performance results of replica voting algorithm