Multi-Objective Decision-Making of Cluster Heads Election in Routing Algorithm for Field Observation Instruments Network

Field observation systems are mainly deployed in the harsh natural environment. These systems principally focus on observation and study within the station currently, which leads to problems such as the inability to form combined network observation and quite challenging to answer the scientific questions of wider regions and scales. To form Field Observation Instruments Networks (FOINs) and accelerate the general automation rate as well as in real-time data exchange in field observation, a multi-objective decision-making mehod named Entropy-based TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) Clustering routing algorithm (ETC) for FOIN is proposed in this paper. The ETC algorithm can select the optimal cluster head (Optimal-CH) through multi-objective decision-making and mainly solves the problem that some existing multi-objective optimization algorithms cannot dynamically and objectively allocate weights. The ETC algorithm was compared with some latest work and similar kinds of work from network lifespan, the number of CH and energy consumption in the Matlab simulations experiments. The result shows that the ETC algorithm performs well, enhancing energy conservation and extending the existence of FOIN.

Automated summary

The ETC algorithm proposed in this paper aims to form Field Observation Instruments Networks (FOIN) and accelerate the general automation rate as well as real-time data exchange in field observation. The algorithm can select the optimal cluster head (Optimal-CH) through multi-objective decision-making and enhances energy conservation in FOIN.