###### Abstract
This study extends the path distribution problem (vehicle-routing problem) and provides an alternative approach for solving time-varying networks. Third, considering that the widespread adoption of blockchain applications lack proper mechanisms of mutual consensus and management for across blockchains, it raises cross-blockchain consensus issue, which refers to one blockchain network reaching a consensus with another blockchain network to provide the ability to interact and share data. In the paper \"A Secure Interoperability Management Scheme for Cross-Blockchain Transactions\" [3], [PERSON] et al. presented a robust management scheme with symmetric cross-blockchain communication and certificateless signature primitives, in which two heterogeneous blockchains are linked by a relay chain to simultaneously deliver cross-blockchain transaction security, achieve compatibility among various blockchains, and ensure the consistency of data exchanged. To evaluate the practicability and security of the proposed scheme, the authors delivered an evaluation and security analysis and then demonstrated that their proposed scheme can be implemented on a common blockchain platform, i.e., Ethereum, with an acceptable computation cost. Fourth, in the paper \"Research and Application of Improved Clustering Algorithm in Retail Customer Classification\" [4], [PERSON] and [PERSON] aimed to improve and use the clustering algorithm for customer segmentation, which is an essential element in an enterprise's utilization of customer relationship management. First, the authors built a customer value system through analytic hierarchy process in which customer value can be quantified and divided into different classifications using clustering technology. In addition, an evaluating system for customer value is introduced, which is in line with the development of the enterprise, using the method of data mining based on the practical situation of the enterprise and through a series of practical evaluating indexes for customer value evaluation. The proposed system can be used to quantify customer value and segment customers, as well as to build a decision-supporting system for customer value management. Fifth, in the paper \"Genetic Algorithms with Variant Particle Swarm Optimization Based Mutation for Generic Controller Placement in Software-Defined Networks\" [5], [PERSON] et al. investigated a so-called generic controller placement problem considering the organization and placement of controllers, as well as the switch attachment, to optimize the delay between controllers and switches, the delay among controllers, and the load imbalance among controllers. To solve this problem without losing generality, the authors accordingly proposed a multi-objective genetic algorithm (MOGA) with a mutation based on a variant of the particle swarm optimization (PSO) technique. The proposed PSO technique chooses a global best position for a particle according to a pre-computed global best position set to lead the mutation of the particle. It successfully handles multiple conflicting objectives, fits the scenario of mutation, and can be applied in many other variants of MOGAs. Finally, evaluations over 12 real Internet service provider networks were conducted to show the effectiveness of the proposed MOGA in reducing convergence time and improving the diversity and accuracy of the Pareto frontiers. Sixth, in the paper \"Applying Federated Learning in Software-Defined Networks: A Survey\" [6], [PERSON] et al. aimed to provide a comprehensive survey on related mechanisms and solutions that enable FL (federated learning) in SDNs (software-defined networks). The authors highlighted three major challenges consisting of an incentive mechanism, privacy and security, and model aggregation, which affect the quality and quantity of participants, the security and privacy in model transferring, and the performance of the global model, respectively.