Networked manufacturing mode has some environmental characteristics that affect its energy saving potential, for example machining devices are numerous and scattered, manufacturing services are driven by customer orders, and significant random uncertainty occurs in manufacturing processes. Networked manufacturing is a new business model formed under enterprise informatization. Improving the energy efficiency of manufacturing industry is a globally common choice to pursue sustainable development and achieve the goals of carbon peak and carbon neutrality. The experimental results indicate that compared with the state-of-the-art matching methods, the proposed method reduces the overall completion time and response delay by up to 35.60% and 29.28%, respectively. Finally, a resource selection strategy is raised to guide the scheduling based on the matching degree. Then, a two-side matching degree metric is designed to comprehensively quantify the matching quality between the task requirements and resource capacities. First, the proposed method establishes the task requirement model and the resource capacity model using a uniform description based on the characteristic analysis to mitigate the impact of diversity and simplify the matching process. To achieve an efficient matching between task requirements and resource capacities, this study proposes a dynamic two-side matching of tasks and resources in wide-area distributed computing environments. However, the geographically distribution of diverse resources complicates the matching problems, thus degrading the system performance. In the wide-area distributed computing environment, matching between tasks and resources plays an important role in improving system performance. Recently, wide-area distributed computing environments have become popular due to its huge resource capacities.
0 kommentar(er)
