A branch and price algorithm for EOS constellation imaging and downloading integrated scheduling problem

Hu, Xiaoxuan; Zhu, Waiming; An, Bo; Jin, Pengfei; Wei, Xiaoying

doi:10.1016/j.cor.2018.12.007

Cited by 35 publications

(23 citation statements)

References 35 publications

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“…Several techniques were proposed in the last decade to define an observation selection and scheduling tool for a constellation of satellites. Some authors proposed to tackle a unique global optimization problem to define the activities of the satellites, based on Branch & Price [1,2] or MILP [3,4]. Several incomplete search methods were also tested such as tabu search [5], evolutionary algorithms [6,7], simulated annealing [8], or Pareto Search when multiple objective functions must be optimized [9,10].…”

Section: Related Workmentioning

confidence: 99%

“…The goal is to maximize the total reward (1). At most one mode is selected for each request (2). The interval associated with each observation is present iff one mode containing it is selected (3).…”

Section: Global Cp Approachmentioning

confidence: 99%

“…Then, we try to start scheduling activities for other CCAs while guaranteeing that the request reward order is always respected. For CCA c 2 , it is not possible to start adding observations o 6 and o 7 belonging to m 2 1 , since if the insertion of o 1 in c 1 fails, it might be the case that o 3 is part of a mode that has a better reward than ω m 2 1 . For CCA c 3 , no computation is triggered because no activity of c 3 belongs to the modes considered at this stage.…”

Section: Upccas: Examplementioning

confidence: 99%

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Parallel Scheduling of Complex Requests for a Constellation of Earth Observing Satellites

2022

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Nowadays, the Earth observation systems involve multiple satellites, multiple ground stations, and multiple end-users that formulate various observation requests. These requests might be heterogeneous (stereoscopic observations, periodic observations, systematic observations, etc.), and one difficulty is that the search space defined by the possible ways of performing the requests given the multiple satellites and ground stations available is huge. This paper studies several combinatorial optimization techniques for solving such an operational problem, including a constraint programming approach and parallel scheduling techniques that take advantage of the problem structure. These algorithms are evaluated on realistic instances involving various request types and objective functions depending on the cloud cover conditions, that highly impact the quality of the images collected.

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Section: Related Workmentioning

confidence: 99%

Section: Global Cp Approachmentioning

confidence: 99%

Section: Upccas: Examplementioning

confidence: 99%

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Parallel Scheduling of Complex Requests for a Constellation of Earth Observing Satellites

2022

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“…Cheng [41] proposed the approach based clustering algorithm and used Pareto to analysis the optimal resource management from the perspective of game theory. In addition, there are some models very similar to the adversarial environment setting in this work, and two categories based on the difference in the player's strategy space: double oracle [42][43][44] and column generation [45][46][47]. The work provided some methods to optimize the deployment of the sensor for outbreak detection problem, but the scenario setting of these methods are different from ours.…”

Section: Security Gamementioning

confidence: 99%

A Stackelberg Security Game for Adversarial Outbreak Detection in the Internet of Things

Chen

Wang

et al. 2020

Sensors

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With limited computing resources and a lack of physical lines of defense, the Internet of Things (IoT) has become a focus of cyberattacks. In recent years, outbreak propagation attacks against the IoT have occurred frequently, and these attacks are often strategical. In order to detect the outbreak propagation as soon as possible, t embedded Intrusion Detection Systems (IDSs) are widely deployed in the IoT. This paper tackles the problem of outbreak detection in adversarial environment in the IoT. A dynamic scheduling strategy based on specific IDSs monitoring of IoT devices is proposed to avoid strategic attacks. Firstly, we formulate the interaction between the defender and attacker as a Stackelberg game in which the defender first chooses a set of device nodes to activate, and then the attacker selects one seed (one device node) to spread the worms. This yields an extremely complex bilevel optimization problem. Our approach is to build a modified Column Generation framework for computing the optimal strategy effectively. The optimal response of the defender's problem is expressed as mixed-integer linear programming (MILPs). It is proved that the solution of the defender's optimal response is a NP-hard problem. Moreover, the optimal response of defenders is improved by an approximate algorithm-a greedy algorithm. Finally, the proposed scheme is tested on some randomly generated instances. The experimental results show that the scheme is effective for monitoring optimal scheduling.Sensors 2020, 20, 804 2 of 20 with IoT devices, such as the medical systems [7]. To detect the worm outbreak propagation as soon as possible, we can collect potential threat data by deploying specific embedded Intrusion Detection Systems (IDSs) in the IoT [8,9]. Therefore, the rapid detection of the worm outbreak propagation in the IoT with limited resources by IDS has become an urgent problem to be solved. Herein, such IoT devices with embedded IDS are collectively referred to as "sensors". The "scheduling strategy" mentioned in the following chapters of this paper is mainly aimed at methods of "sensor" combination opening. MotivationGenerally, the initiator of outbreak propagation is a malicious party, and our goal is to detect the outbreak propagation as soon as possible. For example, in a water network, the problem is where should we place a limited number of sensors to quickly detect contaminants [10][11][12][13][14], while in smart power grids, what is concerned about is finding the failure node in a short time [15]. It is natural in these scenarios to consider the problem of adversarial outbreak detection (AOD), where the defender can first select a set of nodes to deploy sensors, and subsequently the attacker can choose the source of infection to spread malicious information. Although there have been many studies on the AOD problem [11,15], the scenario setting of these works (e.g., a water network setting) is different from our scenario and assumptions (e.g., cybersecurity settings and parameters). A common assumption in the e...

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“…Some works have considered both the image collection and data relay problems within the same framework and provided various solutions to solve them [31][32][33] . However, Hu et al dedicated most of their paper to evaluating a branch and price technique for finding a solution instead of also providing an in-depth explanation of the problem itself [32] .…”

Section: Introductionmentioning

confidence: 99%

A network flow approach for constellation planning

Cox¹,

Droge²,

Humble³

et al. 2022

Space Missn Plann Oper

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A graph-based network flow approach to constellation planning is presented that respects spacecraft resources and mission constraints to arrive at a preliminary operational schedule. The method discretizes task fulfillment opportunity windows into graph nodes and then adds edges based on feasibility of transition between these opportunities, either by slew maneuvers or extended-time task fulfillment during downlink operations. Intelligent graph pruning is applied to improve computation performance and provide a versatile planning capability with a minimal impact on the resulting solution. A network flow formulation allows for a simultaneous search for spacecraft plans using a Mixed Integer Linear Program (MILP). The framework enables the definition of appropriate mission constraints to ensure viability and mission efficiency among the constellation of satellites. The planning technique is demonstrated for a mission of 100 satellites to illustrate its capability and performance within this proliferated regime.

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A branch and price algorithm for EOS constellation imaging and downloading integrated scheduling problem

Cited by 35 publications

References 35 publications

Parallel Scheduling of Complex Requests for a Constellation of Earth Observing Satellites

Parallel Scheduling of Complex Requests for a Constellation of Earth Observing Satellites

A Stackelberg Security Game for Adversarial Outbreak Detection in the Internet of Things

A network flow approach for constellation planning

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