Simplifying maximum flow computations: The effect of shrinking and good initial flows

Liers, Frauke; Pardella, G.

doi:10.1016/j.dam.2011.06.030

Cited by 18 publications

(6 citation statements)

References 12 publications

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“…The latter are of frequent interest in nanotomography, such as in the 3D investigation of porous supports for applications in heterogeneous catalysis 22 , particle chromatography 23 , fuel cells 24 or battery electrodes 25 . For homogeneous materials, reconstruction algorithms based on combinatorial optimization models have been presented in Liers and Pardella 26 . Since homogeneous materials consist of only one approximately constant density value (i.e., composition or material phase), they provide additional information that is known beforehand.…”

Section: Compressed Sensing Frameworkmentioning

confidence: 99%

“…25 For homogeneous materials, reconstruction algorithms based on combinatorial optimization models have been presented in Liers and Pardella. 26 Since homogeneous materials consist of only one approximately constant density value (i.e., composition or material phase), they provide additional information that is known beforehand. In particular, being composed of only one density value, these reconstructions are expected to exhibit either areas of said density or empty space (typically lled with vacuum or air), with only a few sharp edges in between.…”

Section: Compressed Sensing Frameworkmentioning

confidence: 99%

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Improving reconstructions in nanotomography for homogeneous materials via mathematical optimization

Kreuz,

Apeleo Zubiri,

Englisch

et al. 2024

Nanoscale Adv.

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Section: Compressed Sensing Frameworkmentioning

confidence: 99%

Section: Compressed Sensing Frameworkmentioning

confidence: 99%

Improving reconstructions in nanotomography for homogeneous materials via mathematical optimization

Kreuz,

Apeleo Zubiri,

Englisch

et al. 2024

Nanoscale Adv.

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show abstract

“…We present some techniques, based on [33] , to help shrink the size of the Event-Driven Graph. Shrinking this graph reduces memory consumption and makes the flow-maximization algorithm run faster.…”

Section: Vertex Shrinking and Edge Pruningmentioning

confidence: 99%

“…Based on [33] , this step is meant to speed up the max-flow algorithm. We traverse all vertices from the Event-Driven Graph; in each of them, we note the edge with maximum capacity leaving the node; and, if that capacity is larger than the summed capacity of all incoming edges, we reduce that outgoing capacity to the sum of the incoming edges.…”

Section: Event-driven Graph Capacity Normalizationmentioning

confidence: 99%

Data evacuation from data centers in disaster-affected regions through software-defined satellite networks

et al. 2019

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Large-scale disasters can severely disrupt Information Technology (IT) infrastructure, e.g., Data Centers. Earthquakes, hurricanes, tsunamis, and other natural catastrophes may lead to such a scenario. Manmade threats, e.g., a High-Altitude Electromagnetic Pulse (HEMP), can also provoke such an aftermath. In the HEMP case, however, the aftermath might include damage even to non-terrestrial IT infrastructure, such as satellites. After any disaster, it is important that critical data located in the affected region be evacuated to secure locations where it can be useful for emergency operations, mission-critical activities, rescue and relief efforts, and society and businesses in general. To minimize the time it takes to perform this evacuation, we must use all available resources as efficiently as possible. This includes using the remaining satellites to connect the affected regions of the network to the unaffected ones. Utilizing the Software-Defined Network (SDN) paradigm applied to satellite networks, we propose an algorithm that can be executed by the SDN controller. This algorithm generates an evacuation plan for data located in possibly-isolated terrestrial systems, such as Data Centers, through the satellite network, towards final destinations in the main network. The evacuation plan is a transmission schedule that maximizes the amount of evacuated data. Considering the current industrial interest in mega satellite constellations, we compare how two constellations of 66 and 720 satellites perform in terms of amount of data evacuated. Our results show how the evacuation is affected by different satellite constellation configurations (i.e., buffers, inter-satellite link capacities, etc.). Since our approach allows for Traffic Engineering (TE) to be performed, we also demonstrate how it enables fair resource utilization among different affected infrastructures during data evacuation. Our illustrative examples also compare our method to an approach designed for Delay-Tolerant-Vehicle networks and show how our solution can evacuate up to 60% more data after a disaster.

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“…NF problem has permanently been among the research hotspots in operational research, graph theory and combinatorial optimisation [20]. The solution to this problem generally falls into two categories: the first is to constantly seek a path which can be augmented, and gradually increase the value of flow by adding up the minimum sub-path flow [21,22]; the second is to calculate maximum flow value indirectly by applying the minimum cut theorem [23,24].…”

Section: Research Articlementioning

confidence: 99%

Exploring risk flow attack graph for security risk assessment

Dai

Zheng

et al. 2015

IET Information Security

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Simplifying maximum flow computations: The effect of shrinking and good initial flows

Cited by 18 publications

References 12 publications

Improving reconstructions in nanotomography for homogeneous materials via mathematical optimization

Improving reconstructions in nanotomography for homogeneous materials via mathematical optimization

Data evacuation from data centers in disaster-affected regions through software-defined satellite networks

Exploring risk flow attack graph for security risk assessment

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