- author = "Boxiong Tan and Hui Ma and Yi Mei",
- title = "A Hybrid Genetic Programming Hyper-Heuristic Approach for Online Two-level Resource Allocation in Container-based Clouds",
- booktitle = "2019 IEEE Congress on Evolutionary Computation, CEC 2019",
- year = "2019",
- editor = "Carlos A. Coello Coello",
- pages = "2681--2688",
- address = "Wellington, New Zealand",
- month = "10-13 " # jun,
- organization = "IEEE Computational Intelligence Society",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, container-based clouds, resource allocation, evolutionary computation, hyper-heuristic",
- isbn13 = "978-1-7281-2152-6",
-
URL = "
https://ecs.wgtn.ac.nz/Main/Here",
-
DOI = "
doi:10.1109/CEC.2019.8790220",
- size = "8 pages",
- abstract = "Container technology has become a new trend in both the software industry and cloud computing. Containers support the fast development of web applications and they have the potential to reduce energy consumption in data centres. Containers are usually first allocated to virtual machines (VMs) and VMs are allocated to physical machines. The container allocation is a challenging task which involves a two-level allocation problem. Current research overly simplifies the container allocation into a one-level allocation problem and uses simple rule-based approaches to solve the problem. As a result, the resource is not allocated efficiently which leads to high energy consumption. This paper provides a novel definition of the two-level container allocation problem. Then, we develop a hybrid approach using genetic programming hyper-heuristics combined with human-designed rules to solve the problem. The experiments show that our hybrid approach is able to significantly reduce energy consumption than solely using human-designed rules.",
-
notes = "also known as \cite{8790220}
Dec 2019 title tweak
IEEE Catalog Number: CFP19ICE-ART",
