# Resilience in the Internet of Medical Things: A Review and Case Study
## 5 Analysis of Resilience in Existing Works
### Diagnose and Recovery  
Diagnosis is the process which is required to restore the IoMT network operation during and just after the occurrence of faults. Finding the root cause of the faults can be performed through anomaly detection by the use of ML [87]. [PERSON] et al. [44] used the dynamic Bayesian network along with blockchain to provide resilience in the IoMT networks from the damage caused by the distortion of various components in the IoMT subsystem. However, how this model can predict the failure rate in advance has not been discussed. Most of the works [68; 69; 70; 71; 72] provide the solution as a proactive approach. The methodologies are designed in such a way that they can avoid problems or attacks.  
To avoid a single point of failure in the IoMT networks, distributed functionality is a worthwhile feature. Refs. [80; 81; 82; 83; 84] explored distributed functionality by providing the access control by using the microservices architecture with SDN technologies as an integration. However, no contingency plan is available for single-point-of-fault or failures in the existing works.  
During the recovery, the basic tasks required for data transfer should be distributed in the IoMT networks so that the communication between the active nodes can still be possible. These tasks involve the following:  
* The real-time tracking or capturing of the data with their performance metrics.
* Topology information that maps out all the connected nodes during the failure.
* Dynamic flow control capability among the active nodes.  
Based on the requirements provided by the ITU, the seven key capabilities discussed in Section 4 are as follows: anomaly detection, authorization and accessibility, scalability, distributed functionality, traffic classification, route optimization, and global view. These can be considered as essential capabilities of the four critical requirements, monitoring (M), control (C), diagnosis (D), and recovery (R), that are required for realizing resilience in the IoMT networks, as shown in Figure 3. The global view and traffic management capabilitiescan be associated with the monitoring from the perspective of the IoMT infrastructure. Access control and route optimization with scalability are other essential capabilities that can be correlated to control.  
Furthermore, real-time fault detection and traffic classification features are required for route optimization and can be viewed as diagnosis during the failure time in the IoMT networks. Overall, these distributed functionalities provided by the microservices architecture can be integrated into the IoMT infrastructure for the recovery process.  
Furthermore, each of these capabilities has its own functionalities, such as global view having the functionality of tracking the network events and their performance in real-time. In traffic management operations like resource allocation, load balancing and QoS maintenance need to be performed. Real-time detection of faults and failures can be conducted through anomaly detection. The key operations of distributed functionality are redundancy management and data backup scheduling.  
This analysis found that three key technologies can bring all these functionalities into the IoMT networks. SDN can capture the network events in real-time with its performance. SDN can also provide resource allocation and load balancing to maintain the QoS into the IoMT networks. Microservices architecture can provide redundancy management and data backup scheduling. It also provides access control through authorization protocols. Machine learning can provide the real-time prediction of anomalies in the IoMT networks.  
In the next subsection, an analysis of using the SDN or MSA individually in the existing works has been conducted, to check whether or not they can individually meet the requirement of resilience in the IoMT networks.