INTEGRATION OF MESSAGE QUEUE TELEMETRY TRANSPORT PROTOCOL AND CONSTRAINED APPLICATION PROTOCOL FOR DATA COMMUNICATION IN WIRELESS SENSOR NETWORKS

Abstract

Wireless sensor networks (WSN) consist of micro-sensors capable of monitoring physical and environmental factors. These are often mainly made up of resource constrained sensor nodes and gateways. Networking these nodes presents several challenges because the devices have limited computational capability, data storage, energy and communication bandwidth. Therefore, various lightweight communication protocols are emerging for Machine to Machine (M2M) communications. Among the various application layer protocols for data communication in WSNs, the two most popular protocols for constrained devices are the Message Queue Telemetry Transport Protocol (MQTT) with a variant for sensor nodes (MQTT-SN) and the Constrained Application Protocol (CoAP). Studies have shown that the performance of these different protocols are dependent on different network conditions. CoAP is more efficient in terms of message overhead while MQTT-SN is more efficient in terms of client complexity. Studies have further emphasized the levels of difficulties implementing any of these protocols regarding application requirements. This project proposes an integration of MQTT-CoAP protocols using an abstraction layer that enables both MQTT-SN and CoAP protocols to be used in a sensor node. The performance of the system was evaluated in terms of latency per message size in bytes transmitted for different quality of service (QoS) levels and energy consumption per node. The result of the study showed that latency values slightly increase as the packet size increased. The lowest latency was observed in MQTT-SN QoS 0 while similar latency values were obtained for the CoAP and MQTT-SN QoS 1. The average latency was observed to be 163.2ms, 188.5ms and 191.5ms for MQTT-SN QoS 0, MQTT-SN QoS 1 and CoAP respectively. Energy consumption of the node when using MQTT-SN for a single Tx/Rx operation in a 10s interval showed an average of 261.6mJ for both QoS 0 and QoS 1 while an average of 261.3mJ was observed for CoAP. Performance evaluation of these protocols when integrated shows that the system is feasible. While CoAP performs better in terms of energy consumption, the two protocols perform almost equally in latency. The observed values of latency and energy consumption in the developed integration technique is comparable to other studies. This work has shown that the two protocols can coexist in a single sensor node without impacting negatively on its performance. Future work will be required to test the integrated system in a more complex network conditions.