Satellite downlink scheduling problem: A case study

The synthetic aperture radar (SAR) technology enables satellites to efficiently acquire high quality images of the Earth surface. This generates significant communication traffic from the satellite to the ground stations, and, thus, image downlinking often becomes the bottleneck in the efficiency of the whole system. In this paper we address the downlink scheduling problem for Canada's Earth observing SAR satellite, RADARSAT-2. Being an applied problem, downlink scheduling is characterised with a number of constraints that make it difficult not only to optimise the schedule but even to produce a feasible solution. We propose a fast schedule generation procedure that abstracts the problem specific constraints and provides a simple interface to optimisation algorithms. By comparing empirically several standard meta-heuristics applied to the problem, we select the most suitable one and show that it is clearly superior to the approach currently in use.Comment: 23 page

Rack level scheduling for containerized workloads

High performance SSDs have become ubiquitous in warehouse scale computing. Increased adoptions can be attributed to their high bandwidth, low latency and excellent random I/O performance. Owing to this high performance, multiple I/O intensive services can now be co-located on the same server. SSDs also introduce periodic latency spikes due to garbage collection. This, combined with multi-tenancy increases latency unpredictability since co-located applications now compete for CPU, memory, and disk bandwidth. The combination of these latency spikes and unpredictability lead to long tail latencies that can significantly decrease the system performance at scale. In this paper, we present a rack-level scheduling algorithm, which dynamically detects and shifts workloads with long tail latencies within servers in the same rack. Different from the global resource management methods, rack-level scheduling utilizes lightweight containers to minimize data movement and message passing overheads, leading to a much more efficient solution to reduce tail latency.With the algorithms implemented in the storage driver of the containerization infrastructure, it becomes viable to deploy and migrate applications in existing server racks without extensive modifications to storage, OS and other subsystems.by Qiumin Xu, Krishna T. Malladi and Manu Awasthi

Performance analysis of containerized applications on local and remote storage

by Qiumin Xu, Manu Awasthi, Krishna T. Malladi, Janki Bhimani, Jingpei Yang and Murali Annavara