A comparative analysis of data collection methods in internet of things

With the increase in demand of Internet of Things using smart devices, different architectures are available for collecting the data in IoT platforms. Data collection phase is one of the most critical phase in the whole process of communication between device and human. Numerous data collection solutions were proposed in the literature. But still these existing solutions are lacking rationale and can be further improvised. Therefore, this paper conducts a detailed review on the existing methods for data collection. Later, a comparison is made among the existing concurrent tree method, low-density parity check code method and context awareness routing method in terms of their research objectives, techniques, input and output. Finally this paper evaluates the energy consumption, latency and storage requirements for different data collection methods. Results show that concurrent data collection tree method provides maximum storage, consumes more energy and possess less latency.