Improving reliability is one of the major concerns of scientific workflow scheduling in clouds. The ever-growing computational complexity and data size of workflows present challenges to fault-tolerant workflow scheduling. Therefore, it is essential to design a cost-effective fault-tolerant scheduling approach for large-scale workflows. In this paper, we propose a dynamic fault-tolerant workflow scheduling (DFTWS) approach with hybrid spatial and temporal re-execution schemes. First, DFTWS calculates the time attributes of tasks and identifies the critical path of workflow in advance. Then, DFTWS assigns appropriate virtual machine (VM) for each task according to the task urgency and budget quota in the phase of initial resource allocation. Finally, DFTWS performs online scheduling, which makes real-time fault-tolerant decisions based on failure type and task criticality throughout workflow execution. The proposed algorithm is evaluated on real-world workflows. Furthermore, the factors that affect the performance of DFTWS are analyzed. The experimental results demonstrate that DFTWS achieves a trade-off between high reliability and low cost objectives in cloud computing environments.

The constrained application protocol CoAP is an IoT communication protocol proposed by the CoRE working group of IETF. It is widely used in the IoT field due to its features such as lightweight, low power consumption, support for IP multicast and RESTful architecture. However, IoT devices are often used in network environments with high packet loss rates and high latency, and the limited processing capability of the devices themselves is highly susceptible to packet loss, which may lead to network congestion, thus affecting the data transmission efficiency and network stability. Therefore, it is of great significance to study the CoAP congestion control algorithm to ensure network performance and service quality. Firstly, provide an introduction to the CoAP protocol model and its congestion control mechanisms. Secondly, there are mainly two types of CoAP congestion control algorithm research at present: those based on the improvement of CoCoA and other CoAP congestion control algorithms. Analyze the principles, advantages and disadvantages of each algorithm. Lastly, look forward to future research directions in CoAP congestion control algorithms.