...
Traffic plane: two K8s clusters are deployed in private lab.
项目路标，待补充：
Envisioned Signpost
1、业务多集群分分发部署：Scheduling computing force by cluster weight;
...
3、算网协同调度算法增强；（可作为下一阶段的特性规划进来）
3. Designing of integrated computing and network resource scheduling algorithm
By the end of this stage, the CFN BP focuses on the functional integration of computing force scheduling in the ubiquitous computing environment composed of a number of heterogeneous computing nodes. Computing resource-demanding applications from OTT partner, MIGU, are successfully deployed under the guidance of the scheduling decision in our experiment. However, as CFN BP is still in an early stage, the network topology is simple and the number of nodes is limited. Thus, no modern network measurement techniques are deployed in the system. The scheduler only made scheduling decisions based on coarse information about the network, i.e., accessibility. The computing capability in nodes played a major role in the decision process, which is fine for the present experiment, but not sufficient for the final goal of the CFN BP.
...
4、基于成本、资源利用率的调度算法增强；（下一阶段）
4. Scheduling algorithm enhancement considering higher-level factors.
As the CFN is intended to provide service to wide consumers, in spite of technique issues, the computing and network resource scheduling will be also influenced by some higher level factors, such as the preference of computing force customers, intents of computing, and network resource suppliers, etc. Practically, consumers will not only care about how fast their computing tasks are finished and how good the performance of the desired service is but also how much is the cost. And different consumers may show different sensitivity to the cost, which deserves further work on the design of mapping from subjective preference to objective measurable metrics. Moreover, some consumers may also care about the robustness of their application, thus duplicate and redundant deployment of applications or just critical exponents should be taken into consideration.
The intent of resource suppliers will also impact resource scheduling. Some suppliers may prefer to use resources in a computing node with first priority to avoid the appearance of fragmented resources. In contrast, other suppliers may want their resources in different nodes to have balanced usage.
Only when these factors are quantitatively analyzed and characterized, can they can be adopted in the design of scheduling approaches, and high-level preferences and intents can be reflected in the computing force scheduling. These works will also be considered in the next stage of CFN BP.
...