Response Time and Energy-Aware Optimization for Co-Locating Microservices and Offline Tasks

With the widespread application of microservices, data centers use co-location to improve server resource utilization. However, co-location causes performance interference between tasks, which poses challenges to service quality levels. Most of the existing co-location research does not consider the characteristics of microservices and does not take energy consumption as the optimization target of co-location systems. This paper introduces a new indicator to represent the Relative fluctuation of response Time and Energy consumption (RTE). This paper proposes a processor energy optimization mechanism and an offline task scheduling method to solve this problem. This method reduces overall response time by providing a good operating environment for frequently called microservices. The energy consumption optimization mechanism reduces energy consumption by dynamically controlling voltage and frequency. Simulation experiments in practical applications show that our proposed algorithm has the best response time and RTE compared with other algorithms.