Exploiting Delay-Aware Load Balance for Scalable 802.11 PSM in Crowd Event Environments

Abstract

This paper presents ScaPSM (i.e., Scalable Power-Saving Mode Scheduler), a design that enables scalable competing background traffic scheduling in crowd event 802.11 deployments with Power-Saving Mode (PSM) radio operation. ScaPSM prevents the packet delay proliferation of previous study, if applied in the crowd events scenario, by introducing a new strategy of adequate competition among multiple PSM clients to optimize overall energy saving without degrading packet delay performance. The key novelty behind ScaPSM is that it exploits delay-aware load balance to control judiciously the qualification and the number of competing PSM clients before every beacon frame's transmission, which helps to mitigate congestion at the peak period with increasing the number of PSM clients. With ScaPSM, the average packet delay is bounded and fairness among PSM clients is simultaneously achieved. ScaPSM is incrementally deployable due to only AP-side changes and does not require any modification to the 802.11 protocol or the clients. We theoretically analyze the performance of ScaPSM. Our experimental results show that the proposed design is practical, effective, and featuring with significantly improved scalability for crowd events.

A Microservice-Based Big Data Analysis Platform for Online Educational Applications

“…We add tags and firewall rules to allow specific network traffic from the Internet, including MySQL service [33], Greenplum service, web service, and Hadoop service on the VPC (Virtual Private Cloud) network/Firewall rules in Google cloud platform. A minimal tuning of the system and the Nginx web proxy server [10] was done to support a high number of concurrent connections. In the following part, we will first describe the service deployment and then give two examples of the main applications on the platform.…”

“…As described in the introduction, there is a certain demand to get advanced tools for storing and sharing some kinds of environment for data science and big data research, which is configured by specific engineering staff on cloud computing infrastructure for individuals and research teams. A lot of systems have been developed in recent years and solved some of the problems mentioned above, including big data environment infrastructure constructing [4,10,19], microservice-based platform [5,11,20], and online educational programming platform [21][22][23]. However, several issues remain, which are not addressed well by existing approaches and systems.…”

“…For web-based platforms [8], JupyterHub is required [9]. For workers with big data needs, they also need to integrate the experimental environment based on Hadoop [10], Spark, and JupyterHub.…”

IEEE 802.11 PSM in ns-3: A Novel Implementation and Evaluation under Channel Congestion

“…[11] proposes dividing the beacon interval into multiple sub-intervals and instructing the STAs in PS to wake up at specific sub-intervals. For dense wireless environments, [16] presents a scalable delay-aware load balancing scheduler called ScaPSM, which dynamically determines the STAs allowed for channel access to reduce contention and improve power efficiency.…”