Unequal Clustering Protocol in IoT Networks Based on Multiple Criteria Processing
Foudil Mir, Farid Meziane
Abstract
The Internet of Things (IoT) is a rapidly expanding network characterized by a very significant number of heterogeneous devices with limited resources. Clustering is a very powerful technique used to reduce the communication load, conserve energy, aggregate data and optimize the performance of IoT systems. Designing an efficient clustering algorithm is a real challenge. Once the Cluster Heads (CHs) are elected, traditional clustering algorithms typically use a single clustering radius to group nodes to form clusters. However, this approach is potentially not optimized, as devices within a cluster may have different characteristics. In this paper, we focus on the DCOPA protocol proposed for clustering in IoT networks. Once the CHs are elected, the identical clustering radius is applied to these different elected CHs despite their differences in terms of residual energy and Distance to Base Station (DistBS). The new approach, called Unequal-DCOPA (UDCOPA), makes it possible to define for each CH its clustering radius which will be sensitive to the local criteria of energy and DistBS for the CH that is being considered. The radius is modelized as a multicriteria system. Simulation results show that our new protocol UDCOPA outperforms DCOPA in energy management and lifetime parameters of nodes and network. UDCOPA increases lifetime by 34.55% when compared to DCOPA.