PhD Forum Abstract: Exploring Service Placement and Request Scheduling Based on Cooperative Edge Computing in AIoT

Yuzhu Liang

Abstract: The rapid growth in data generated by the Artificial Internet of Things (AIoT) necessitates an increase in computational power and presents challenges to cloud infrastructure, including traffic congestion and latency issues in AIoT systems. This trend has fostered a shift toward edge-layer computation, with cooperative edge computing emerging as a potent solution to these challenges. However, the diversity and heterogeneity of AIoT systems present significant challenges with regard to service placement, cross-regional request scheduling, and efficient resource caching. My research aims to enhance cooperative edge computing by designing an optimized clustering algorithm for efficient service placement and data processing, developing a cooperative edge request scheduling method using digital twin technology to minimize system transmission delays, and devising a resource caching method employing deep reinforcement learning in cooperative game scenarios to optimize resource allocation. This research endeavors to enhance service placement and request scheduling efficiency, thereby offering substantial computational support to AIoT systems.

External IDs:dblp:conf/ipsn/Liang24