Distributed global snapshot (DGS) is one of the fundamental protocols in distributed systems. It is used for different applications like collecting information from a distributed system and taking checkpoints for process rollback. The Chandy–Lamport protocol (CLP) is famous and well‐known for taking DGS. The main aim of this protocol was to generate consistent cuts without interrupting the regular operation of the distributed system. CLP was the origin of many future protocols and inspired them. The first aim of this paper is to propose a novel formal hierarchical parametric colored Petri net model of CLP. The number of constituting processes of the model is parametric. The second aim is to automatically generate a novel message sequence chart (MSC) to show detailed steps for each simulation run of the snapshot protocol. The third aim is model checking of the proposed formal model to verify the correctness of CLP and our proposed colored Petri net model. Having vital tools helps greatly to test the correct operation of the newly proposed distributed snapshot protocol. The proposed model of CLP can easily be used for visually testing the correct operation of the new future under‐development DGS protocol. It also permits formal verification of the correct operation of the new proposed protocol. This model can be used as a simple, powerful, and visual tool for the step‐by‐step run of the CLP, model checking, and teaching it to postgraduate students. The same approach applies to similar complicated distributed protocols.

The problem of data association for tracking multiple targets based on using the ship-borne radar is addressed in this study. A robust fuzzy density clustering algorithm is proposed, that contains three steps. At first, a customized form of adaptive density clustering is used to determine valid measurements for each target’s state. In the second step, the degree of fuzzy membership for each valid measurement is determined based on the maximum entropy approach. At the final step, the measurements with a maximum degree of membership are used for updating the position of the targets. The proposed approach does not require gating techniques and led to the reduction of steps in comparison with other data association methods. In addition, the effect of ship movement in the performance of the tracking filter, based on the adaptive extended Kalman filter (AEKF) was studied. The efficiency and effectiveness of the proposed algorithm are compared with the nearest neighbor (NN) with Mahalanobis distance and Fuzzy nearest neighbor (FNN) methods. The results demonstrate the main advantages of the proposed algorithm, including its simplicity and suitability for real-time target tracking in cluttered environments.