## 6 Comparison and Discussion  
Simulation experiments have been performed to compare the proposed DT based method with SPRT [4, 5] (centralized) and XED [30] (distributed). The effectiveness of the existing clone detection approaches, e.g., SPRT and XED depend upon fast detection and simple remember and challenge response (i.e., based on random number), respectively. Therefore, it motivates this research to compare the proposed DT approach with SPRT and XED in order to show the efficiency (i.e., clone detection improvement) to secure the MWSN from malicious activities. The fair comparison is performed by using the same estimation, simulation parameters and network settings. Previous research [31] has compared SPRT (i.e., centralized method) and XED (i.e., distributed method) by using specific simulation parameters. Therefore, this paper has used the same consideration and estimation to perform a fair comparison between SPRT (i.e., centralized method), XED (i.e., distributed method) and hybrid (i.e., DT) approaches. The comparison is made consuming several execution factors, namely, replica detection ratio, completion time for clone identification, energy consumption, false negative and false positive for replication threats. The details of the parameters can be described as follows:  
1. **Energy Consumption for DT (\(E_{d}\)):** This is the total consumption cost in support to communication and computation overhead for clone detection. 2. **Clone detection ratio (\(P_{d}\)):** This is the ratio of successful clone identification interval over the whole experiments' execution. 3. **Completion time for detecting a clone (\(T_{d}\)):** This is the interval that is consumed when the first clone detection happens. 4. **Errors for False Positive:** This indicates the wrongly detected replicas in MWSN (a normal node is detected as a replica). 5. **Error for False Negative:** This reflects that clone mobile node is not identified as a clone, which may collapse and affect the capability and performance of clone detection due to wrong identification. These parameters will briefly reflect how centralized and distributed methods for clone identification is effective and more efficient in network. The single point of failure is the main concern in the centralized approach as mentioned in [32] that affects the tasks in MWSN. Moreover, the mobile nodes deployed  
Figure 14: Delay effect of DT approach on detection performance. close to the base station could suffer from the huge load which would eventually lead to congestion (i.e., load balancing issue). That could be in favor of an advisory. Therefore, for clone identification, a balanced and distributed technique is obligatory to overcome the drawback of the single point of failure. For clone identification with distributed method, as observed in [30], it mostly has issues with memory, for example XED if mobile node memory is fully occupied, for localization and detection time completion. On the other hand, it has less load and output shows that it has least errors in terms of false negative and positive. In order to decrease the matter of memory, hybrid method (i.e., centralized and distributed) is used for clone identification and mitigation. By mean of fair comparison, we utilized the same simulation parameters approximation as mentioned in [31]. Accordingly, the performance evaluation involves 200 mobile nodes, network size of 500 m \(\times\) 500 m, transmission range of 100 m, detection time of 1000 seconds and average simulation results of 100 simulation experiments. Figures 15 and 16 illustrate the false detection errors of the clone detection methods in terms of false negative and false positive, respectively. It could be seen that the multi-level DT based clone identification approach offers efficient outcome compared to XED and SPRT methods.