Contention-Aware Microservice Deployment in Collaborative Mobile Edge Networks

TL;DR

This paper introduces CAMD, a contention-aware deployment algorithm for microservices in mobile edge computing, which optimizes resource allocation to reduce latency and improve QoS.

Contribution

It presents a novel heuristic-based algorithm that decomposes deployment into sub-problems, addressing resource contention in MEC microservice deployment.

Findings

CAMD outperforms baseline algorithms in reducing latency.

The algorithm effectively balances response time and processing efficiency.

Experimental results validate the approach's superiority.

Abstract

As an emerging computing paradigm, mobile edge computing (MEC) provides processing capabilities at the network edge, aiming to reduce latency and improve user experience. Meanwhile, the advancement of containerization technology facilitates the deployment of microservice-based applications via edge node collaboration, ensuring highly efficient service delivery. However, existing research overlooks the resource contention among microservices in MEC. This neglect potentially results in inadequate resources for microservices constituting latency-sensitive applications, leading to increased response time and ultimately compromising quality of service (QoS). To solve this problem, we propose the Contention-Aware Multi-Application Microservice Deployment (CAMD) algorithm for collaborative MEC, balancing rapid response for applications with low-latency requirements and overall processing efficiency. The CAMD algorithm decomposes the overall deployment problem into manageable sub-problems, each focusing on a single microservice, then employs a heuristic approach to optimize these sub-problems, and ultimately arrives at an optimized deployment scheme through an iterative process. Finally, the superiority of the proposed algorithm is evidenced through intensive experiments and comparison with baseline algorithms.