Incremental clustering-based object tracking in wireless sensor networks

Recent Trends in Incremental Clustering: A Review

“…As of now, static cluster based object tracking is the most common approach for large-scale WSN. However, as static clusters are restricted to share information globally, tracking can be lost at the boundary region of static clusters [10].Teena Ajayan et al [2015] in this paper, the key idea is to find multiple representative sequences like medoids to represent a cluster in a chunk and final DNA analysis is carried out based on those identified medoids from all the chunks. The main advantage of this incremental clustering is that it uses multiple medoids to represent each cluster in each chunk which captures the pattern structure more accurately.…”

Object Tracking in Wireless Sensor Networks: Challenges and Solutions

“…While static clusters are confined to share information within cluster vicinity, on-demand dynamic clustering, on the other hand, is used when the object enters and exits the boundary region so sensors from different static clusters that intercept the object can temporarily share information. In the same context of solving the boundary problem, the authors in (Akter et al, 2015) proposed to combine static clustering with another incremental clustering algorithm to track an object consistently. In other words, incremental clusters are constructed at the boundaries of static clusters to continue the tracking task.…”

Dynamic Clustering Algorithm for Tracking Targets with High and Variable Celerity (ATHVC)

“…As its name suggests, this category includes solutions with several combined approaches. For example, in [16,17], the authors propose algorithms hybrid clustering in which dynamic reactive clusters are formed in collaboration with static proactive clusters. The major objective of this research is to continue to monitor targets in the cluster border regions with energy efficiency; however, these algorithms still suffer from energy inefficiency due to having a priori static cluster structure.…”

“…All other sensors must be in sleep mode. Numerous proposals have been published in recent years [6][7][8][9][10] which propose dynamic clustering algorithms; these form temporal clusters depending on the evolution of the target across the network. However, despite the efficiency of their energy, these algorithms are not adapted to an environment where the velocity of the target can become extremely large and variable.…”