Satellite Control Network Research Articles

A Generalized Consistent Neighborhood Search for Satellite Range Scheduling Problems

Many optimization problems require the use of a local search to find a satisfying solution in a reasonable amount of time, even if the optimality is not guaranteed. Usually, local search algorithms operate in a search space which contains complete solutions (feasible or not) to the problem. In contrast, in Consistent Neighborhood Search (CNS), after each variable assignment, the conflicting variables are deleted to keep the partial solution feasible, and the search can stop when all the variables have a value. In this paper, we propose a generalized version of CNS, discuss its performance according to various criteria, and present successful adaptations of CNS to three types of satellite range scheduling problems. Such problems are motivated by applications encountered by the French National Space and Aeronautic Agencies and the US Air Force Satellite Control Network. The described numerical experiments will demonstrate that CNS is a powerful and flexible method, which can be easily combined with efficient ingredients.

Understanding Algorithm Performance on an Oversubscribed Scheduling Application

The best performing algorithms for a particular oversubscribed scheduling application, Air Force Satellite Control Network (AFSCN) scheduling, appear to have little in common. Yet, through careful experimentation and modeling of performance in real problem instances, we can relate characteristics of the best algorithms to characteristics of the application. In particular, we find that plateaus dominate the search spaces (thus favoring algorithms that make larger changes to solutions) and that some randomization in exploration is critical to good performance (due to the lack of gradient information on the plateaus). Based on our explanations of algorithm performance, we develop a new algorithm that combines characteristics of the best performers; the new algorithm's performance is better than the previous best. We show how hypothesis driven experimentation and search modeling can both explain algorithm performance and motivate the design of a new algorithm.

AFSCN scheduling: How the problem and solution have evolved

The Air Force Satellite Control Network (AFSCN) coordinates communications to more than 100 satellites via nine ground stations positioned around the globe. Customers request an antenna at a ground station for a specific time window along with possible alternative slots. Typically, 500 requests per day result in more than 100 conflicts, which are requests that cannot be satisfied because other tasks need the same slot. Scheduling access requests is referred to as the Satellite Range Scheduling Problem (SRSP). This paper presents an overview of three key issues: (1) how has the problem changed over the last 10 years, (2) what algorithms work best and (3) what objective function is appropriate for AFSCN. We compared data sets from 1992 and from 2002/2003 and found significant differences in the problems. Our evaluation of solutions focuses on three algorithms: local search, Gooley’s algorithm from AFIT, and the Genitor genetic algorithm. It can be shown that local search (and therefore metaheuristics based on local search) fail to compete with Gooley’s algorithm and Genitor. Finally, while all prior work on AFSCN minimizes request conflicts, we explore an alternative objective function. Because human schedulers must eventually schedule all requests, it might be better to optimize schedules for “repairability”. Our results suggest that minimizing schedule overlaps makes it easier to fit larger requests into the schedule.

Scheduling Space–Ground Communications for the Air Force Satellite Control Network

We present the first coupled formal and empirical analysis of the Satellite Range Scheduling application. We structure our study as a progression; we start by studying a simplified version of the problem in which only one resource is present. We show that the simplified version of the problem is equivalent to a well-known machine scheduling problem and use this result to prove that Satellite Range Scheduling is NP-complete. We also show that for the one-resource version of the problem, algorithms from the machine scheduling domain outperform a genetic algorithm previously identified as one of the best algorithms for Satellite Range Scheduling. Next, we investigate if these performance results generalize for the problem with multiple resources. We exploit two sources of data: actual request data from the U.S. Air Force Satellite Control Network (AFSCN) circa 1992 and data created by our problem generator, which is designed to produce problems similar to the ones currently solved by AFSCN. Three main results emerge from our empirical study of algorithm performance for multiple-resource problems. First, the performance results obtained for the single-resource version of the problem do not generalize: the algorithms from the machine scheduling domain perform poorly for the multiple-resource problems. Second, a simple heuristic is shown to perform well on the old problems from 1992; however it fails to scale to larger, more complex generated problems. Finally, a genetic algorithm is found to yield the best overall performance on the larger, more difficult problems produced by our generator.

1 The Resource Management Segment ‐ A Case Study in the Role of Software Architecture in the Systems Engineering Process

AbstractThis paper provides a case study of the development of the Resource Management Segment (RMS) of the Air Force Satellite Control Network (AFSCN). The focus of the study is the role of the system architecture in the systems engineering process for this project. The RMS project was an attempt to modernize and consolidate software used for AFSCN resource scheduling, orbit analysis, and resource monitoring. The approach taken by the responsible contractor was to do a complete object‐oriented development using the 4+1 View methodology described by Phillipe Kruchten in (Kruchten 1995). Specifically, this paper outlines the architectural approach, describes key issues that arose, and discusses the processes that surrounded the architecture. The discussion is focused on how the architecture fits into the RMS systems engineering approach. Finally, some lessons learned are summarized.

Near term approach to data relay for satellites under test

The increasing need for a continuous communications link with U.S. Department of Defense (DoD) spacecraft during test missions in low Earth orbit (LEG) has resulted in greater interest in geosynchronous data relay services. This may be a more economical alternative to building additional remote tracking stations for the Air Force Satellite Control Network (AFSCN), and avoids tying up operational assets for a test mission. A low-cost near-term approach for such a space-based data relay system would utilize two existing Defense Satellite Communication System III spacecraft, two existing ground terminals, and a small, standardized terminal using autonomous antenna pointing for the space vehicle under test. Such a system design is presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>