Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Energy efficiency is a crucial challenge in cluster-based capillary networks for Internet of Things (IoT) systems, where the cluster heads (CHs) selection has great impact on the network performance. It is an optimization problem to find the optimum number of CHs as ll as which devices are selected as CHs. ,  formulate the clustering problem into the CHs selection procedure with the aim of maximizing the average network lifetime in every round. In particular,  propose a novel CHs selection scheme based on QPSO and investigate how effective it is to prolong network lifetime and reserve the overall battery capacity. The simulation results prove that the proposed QPSO outperforms other evolutionary algorithms and can improve the network lifetime by almost 10%.
['Liumeng Song', 'Kok Keong Chai', 'Yue Chen', 'Jonathan Loo', 'Shihab Jimaa', 'John A. Schormans']
I am writing a research paper on a idea QPSO-based energy-aware clustering scheme in the capillary networks for Internet of Things systems
[{"from": "human", "value": "I am writing a research paper on a idea QPSO-based energy-aware clustering scheme in the capillary networks for Internet of Things systems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Energy efficiency is a crucial challenge in cluster-based capillary networks for Internet of Things (IoT) systems, where the cluster heads (CHs) selection has great impact on the network performance. It is an optimization problem to find the optimum number of CHs as ll as which devices are selected as CHs. ,  formulate the clustering problem into the CHs selection procedure with the aim of maximizing the average network lifetime in every round. In particular,  propose a novel CHs selection scheme based on QPSO and investigate how effective it is to prolong network lifetime and reserve the overall battery capacity. The simulation results prove that the proposed QPSO outperforms other evolutionary algorithms and can improve the network lifetime by almost 10%."}]