The high growth of air traffic flow has increased more bottleneck traffic issues in the air traffic management (ATM) system. The challenges between flight flow, air traffic control service and airspace are the major key parameters which support capability of domestic and international air transportation need to be looked by stakeholders. Many models are designed to incorporate to address the potential bottleneck issues of ATM. However, in these models’ analysis was not clearly presented. The proposed research review paper presents an analysis and insights of different models used in an air traffic management which includes, Big Data, Artificial Neural Network, Cloud Computing and Enterprise models.

Sensor nodes deployed in wireless sensor networks (WSN) are resource constrained, battery operated and have a restricted energy resource. The significant number of wireless sensor network applications aim to extend the longevity of the network by using various strategies. Clustering algorithms were proven to be among the best efficient ways for increasing wireless sensor network reliability. In a wireless sensor network, clustering-based solutions control the network operations to manage the restricted energy in the optimal effective way to extend the network lifetime. Reviews in related subject could assist in gathering thorough and timely information about wireless sensor networks lifetime study through different clustering protocols. This research review study paper presents an extensive study of existing low energy adaptive clustering hierarchy (LEACH) homogeneous clustering procedures and analysis.