In the era of smart devices and connected neighborhoods, the ubiquitous monitoring and care of patients are possible with the Internet of Medical Things (IoMT). Smart healthcare devices may serve their purpose well when they are able to share patient's data with each other. However, data formats vary widely across vendors, rendering these devices not interoperable. Recent solutions mostly rely on cloud services where a source device uploads the data, and the sink devices download it conforming to their own native formats. However, the quality of service is expected to deteriorate in a cloud processing regime with inherent network delays and traffic congestion, and the real-time data acquisition and manipulation is, therefore, not possible. This article presents MeDIC, a framework of Medical Data Interoperability through Collaboration of healthcare devices. MeDIC improves over a cloud-based IoMT by utilizing translation resources at the network edge, with its probing and translating agents. The probing agents maintain a capability list of MeDIC devices within a local network and enable one MeDIC device to request data conversion from another device when the former is not capable of this conversion by itself. The translating agent of the later then converts the data into the required format and returns it to the former. These novel agents allow IoMT devices to share their redundant computing resources for data translations in order to minimize cloud accesses. Legacy devices are supported through MeDIC-enabled, fog resource managers. We evaluate MeDIC in four use cases with rigorous simulations, which prove that this collaborative framework not only reduces the uplink traffic but also improves the response time, which is critical in real-time medical applications.
Due to exponential growth in the daily usage of vehicles, the traffic congestion and roadside accidents are increasing day by day. The communication among vehicles is critical to avoid the emergencies and to address the issue of congestion of vehicles. Internet of vehicles provides the communication channel between the vehicles, but existing solutions require a centralized communication system to distribute the message and to authenticate the source. This centralized infrastructure is subject to disturb the vehicular communication in case of server breakdown or due to any natural disaster where hardware stops working. Also, the centralized system proves to be costly as the communication of each vehicle necessitates access to the central server resulting in the more resource requirement. A secure distributed system is required to avoid the emergencies and reduce the traffic rate. To address the issues, we proposed a secure distributed messagepassing framework that does not require a centralized server, and it rates the credibility of message source using blockchain technology. The messages in the proposed system are forwarded through dedicated short-range communication protocol. To validate the proposed system, we have performed different simulations using SUMO, OMNET, and VEINS. The results demonstrated an increase in the average speed of vehicles that showed a reduced congestion rate. Moreover, our system identified the malicious vehicles with 77.1% accuracy.
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