# Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks
## 2 Related Work
### IoT Protocols for IoT in VANET  
In the following we will briefly describe the most frequently used protocols for Machine-to-Machine (M2M) communication. The Message Queue Telemetry Transport (MQTT) is a Client Server that publishes or subscribes messaging transport protocol. It is light weight, open, simple and designed so as to be easy to implement. The protocol runs over Transmission Control Protocol/ Internet protocol (TCP/IP) or over other network protocols that provide ordered, lossless, bi-directional connections. The MQTT features include the usage of the publish/subscribe message pattern which provides one-to-many message distribution, a messaging transport that is agnostic to the content of the payload. Furthermore, the MQTT protocol has minimized transport overhead and protocol exchange to reduce network traffic and has an extraordinary mechanism to notify interested parties when an abnormal disconnection occurs as well [21].  
The Constraint Application Protocol (CoAP) is a specialized Web transfer protocol for use with constrained nodes and constrained networks. The nodes often have 8-bit microcontroller with small amounts of Read Only Memory (ROM) and Random Access Memory (RAM), while constrained network often have high packet error rate and typical throughput is 10 kbps. This protocol designed for M2M application such as smart city and building automation. The CoAP provides a request and response interaction model between application end points, support build-in discovery services and resources, and includes key concepts of the Web, such as Universal Resources Locator (URIs) and Internet media types. CoAP is designed to have a friendly interface with Hypertext Transfer Protocol (HTTP) for integration with the Web, while meeting specialized requirements such as multicast support, very low overhead and simplicity for constrained environments. On the other side, many people will still be driving even on the era of autonomous cars. The high cost of driverless cars, lack of trust and not wanting to give up driving might be among the reasons why those people will continue to drive their cars. Hence, many researchers and automotive engineers keep working on Driver Assistance Systems (DASs) and Driver Monitoring System (DMSs) as a primary safety feature required in order to achieve full marks in safety. DASs and DMSs are intelligent systems that reside inside the vehicle and help the driver in a variety of ways. These systems rely on a comprehensive sensing network and artificial intelligence techniques, and have made it possible to commence the era of connected cars. They can invoke action to maintain driver attention in both manual and autonomous driving. While the sensors are used to gather data regarding the inside/outside environment, vehicle's technical status, driving performance and driver's condition, the intelligent systems task is to make decisions based on these data. If the vehicle measurements are combined with those of the surrounding vehicles and infrastructure, a better environment perception can be achieved. In addition, with different intelligent systems located at these vehicles as well as at fog servers more efficient decisions can be attained. Substantial research has been done over the years to build and improve DASs and DMSs. Many big automotive companies such as Toyota, Nissan, Mercedes-Benz, BMW, Volvo, and Saab, as well as third parties including Seeing Machines, Veoneer, and Smart Eye, are conducting continuous research to develop such intelligent systems.