实验室硕士生吴朝锐，邓玉辉老师等人联合撰写的论文《Blender: A Container Placement Strategy by Leveraging Zipf-like Distribution within Containerized Data Centers》被计算机系统结构领域的权威国际学术期刊《IEEE Transactions on Network and Service Management》录用。论文针对容器化数据中心提出了一种新的容器放置策略。论文将于2022年正式发表。吴朝锐现在实验室攻读博士学位。
Abstract—Instantiated containers of an application are dis-tributed across multiple Physical Machines (PMs) to achieve high parallel performance. Container placement plays a vital role in network traffic and the performance of containerized data centers. Existing container placement techniques are inadequate due to the ignorance of container traffic patterns. To solve this issue, we first investigate the network traffic between containers and observe that it exhibits a Zipf-like distribution. Motivated by this finding, we propose a novel container placement approach - Blender - by taking into account the Zipf-like distribution. Blender employs two algorithms called RefineAlg and SplitAlg to divide containers of applications into blocks, and place these blocks across Virtual Machines (VMs). Blender exhibits two salient features: (i) it minimizes inter-block traffic by arranging the containers that communicate frequently in the same block.(ii) it achieves good load balancing by combining complementary blocks that request different resource types (e.g., CPU-intensive and memory-intensive blocks) and distributing these blocks across multiple VMs. The experimental results show that Blender significantly reduces communication traffic and network latency. In particular, Blender reduces the traffic of SBP and CA-WFD by 22% and 32%, respectively. Blender decreases network latency by 16% and 26% compared to SBP and CA-WFD. Furthermore, with Blender in place, the physical resources of hosting PMs are well balanced and utilized.