As cloud providers scale up their data centers and distribute them around the world to meet demand, proposing new job schedulers that into account data center geographical distribution have been receiving considerable attention from the data center management research and practitioner community. However, testing and benchmarking new schedulers for geo-distributed data centers is complicated by the lack of a common, easily extensible experimental platform. To address this gap, we propose GDSim, an open-source job scheduling simulation environment for geo-distributed data centers that aims at facilitating development, testing, and evaluation of new geo-distributed schedulers.
GDSim is currently being developed as a trace generator and a simulator for execution of geo-distributed job schedulers. The trace generator was developed to help to create more diverse scenarios for simulations. The simulator uses an event-driven framework to replay activity present in the traces, allowing different schedulers to build their schedules so that they can be compared. This is not meant to substitute a testbed experiment, but allows a first-level comparison that is faster and less costly.
Publications
- Daniel Alves, Katia Obraczka, Abdul Kabbani, “GDSim: Benchmarking Geo-Distributed Data Center Schedulers”, 2021 IEEE 10th International Conference on Cloud Networking (CloudNet), November 2021. pdf