 and the resources available on MEC servers. Task priority can be considered by adding a violation penalty that corresponds to the priority of the task. Therefore, assignments that cause high priority violations will have a higher cost and will be eliminated. 7.5.2 MOBILITY CHALLENGE Indoor health monitoring sensors are one example of low mobility healthcare applications. A 5G connected ambulance is an example of high mobility healthcare applications. Like older mobile network generations, 5G should effectively associate an end-user with the most appropriate access point and handle handovers. An extra parameter to consider in MEC is how will resource allocation algorithms handle Integrated Blockchain and MEC Systems handovers. The higher the mobility, the more challenging it is to allocate resources that fulfill the QoS requirements of each request. To solve the network association problem, Zhu et al. [27] propose a network selec- tion scheme using decision theory and fuzzy logic theory. They base their decision on the QoS required by the user, the cost of associating with the network, and the network load. For mobility aware resource allocation, two methods were mentioned in [28]. One method is to provide the orchestrator with real-time user information to predict the user location and consider it to decide the allocation. The other method is to reserve resources on each server to improve the scheduling of tasks that migrate from one edge node to another. The main concern with the task migration method is that it induces unnecessary communication overhead in a false handover alarm. The interesting idea is to build two different protocols for dealing with network associ- ation and resource allocation. Low mobility applications will follow one protocol, whereas the other protocol focuses on solving serious mobility application problems. Network slicing can be used to categorize the request and determine the protocol that should be used. 7.5.3 PROBLEMS AND CHALLENGES IN INTEGRATION 7.5.3.1 Scalability In blockchain