Traffic-aware contact plan design for disruption-tolerant space sensor networks

Fraire, Juan A.; Madoery, Pablo G.; Finochietto, Jorge M.

doi:10.1016/j.adhoc.2016.04.007

Cited by 40 publications

(21 citation statements)

References 14 publications

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“…In order to tackle the battery‐aware link scheduling problem for DTN satellite networks, we consider an abstraction of the satellite constellation based on a discrete set of time episodes where the topology is considered stable and can be modeled by a temporary static graph. The approach is known as time‐evolving graph and has been extensively used in previous works related with time‐evolving networks 18,25,26 …”

Section: System Modelmentioning

confidence: 99%

“…Previous work extending DTN routing 11,12 toward considering energy availability focused on remote nodes during a path validation phase, 13,14 where decisions are based on a precomputed schedule of the communication resources, a.k.a., contact plan. The problem of computing resource‐efficient contact plans based on fairness, 15 routing, 16 traffic, 17,18 and mission‐related tasks 19,20 was addressed to support the DTN data flow from ground. Moreover, recent work by the authors have introduced battery‐awareness constraints 5,6 .…”

Section: Introductionmentioning

confidence: 99%

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On the scalability of battery‐aware contact plan design for LEO satellite constellations

Fraire

Gerstacker

Hermanns

et al. 2020

Satell Commun Network

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Summary Size and weight limitations of low‐Earth orbit (LEO) small satellites make their operation rest on a fine balance between solar power infeed and power demands of supporting communication technologies, buffered by on‐board battery storage. As a result, the problem of planning battery‐powered intersatellite communication is a very difficult one. Nevertheless, there is a growing trend toward constellations and mega‐constellations that are to be managed using sophisticated software support. In earlier work, we have discussed how the effective construction of contact plans in delay‐tolerant satellite networking can profit from a refined model of the on‐board battery behavior. This paper presents a profound study of the scalability of the approach and discusses how to tailor it to the needs arising in the management of mega‐constellations, together with a variety of improvements to the base approach. Results show that efficient mega‐constellation operations are compromised, encouraging further research on the area.

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Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the scalability of battery‐aware contact plan design for LEO satellite constellations

Fraire

Gerstacker

Hermanns

et al. 2020

Satell Commun Network

Self Cite

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“…Thus, image data for different region suffers different network topology evolution during transmission from the source to destination. To cope with such challenge in RSNet caused by time-varying and divisional topology, Remote Sensing Disruption-Tolerant Network (RS-DTNet) is proposed [14], with specific-designed store-forward and retransmission mechanism. In [15], large image file transfer experiments for the remote sensing satellites were performed, with Bundle Protocol (BP) overlaying different sub-networks.…”

Section: Related Work a Remote Sensing Disruption Tolerant Networkmentioning

confidence: 99%

A Task-Driven Updated Discrete Graph Assisted Minimum Delivery Delay Routing for Remote Sensing Disruption-Tolerant Networks

et al. 2019

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Benefiting from the extensive coverage, remote sensing satellites have been playing important roles in surveillance for regions on the earth surface. In order to accommodate with intermittent connected and partitioned characteristics of satellite topology, disruption-tolerant network (DTN) develops a feasible solution for networking among such satellites. However, utilized widely and frequently in the future, numerous image covering hundreds of spectral bands and kilometers width is supposed to be delivered simultaneously. Due to the timeliness constrain, efficient routing design with minimum delivery delay for bulk and concurrent image data has become the bottleneck of remote sensing application. Considering data transmission initiated as different tasks, therefore, the Task-driven Updated Discrete Graph (TUDG) is designed to depict the topology evolution, with task data and edge capacity model for BP/LTP incorporated Remote Sensing DTN Network (RS-DTNet). In particular, the multitask-based delivery delay analytical framework is proposed based on the TUDG graph model, by solving a mixed integer Max-Min optimization problem. The Multi-Task Minimum Delay Routing (MTMDR) is designed with the delay-optimal flow distribution, dispatching appropriate bundle data to edges in the TUDG. This flow-based routing avoids the path selection procedure, which may degenerate the delivery delay performance. Through numerical simulation based on the representative RS-DTNet scene, the proposed MTMDR routing strategy shows to advantage on delivery delay, compared with typical path-based routing. INDEX TERMS Delivery delay, disruption-tolerant network, min-max optimization, remote sensing.

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“…Three ground stations are separately located at Xi’an (34.45° N, 109.50° E), Mi’yun (40.45° N, 116.86° E), and He’tian (37.11° N, 79.92° E). For simplicity, we set the data transfer rate to 1 Mb/s and the packet size to 1 Mbit [ 41 ], which means that the transmission of a packet will occupy one second of a contact. The default lifetime of a packet is set to 4200 s. In the MPSO, the group size is set to 100.…”

Section: Simulation and Analysismentioning

confidence: 99%

An Intelligent Computing Method for Contact Plan Design in the Multi-Layer Spatial Node-Based Internet of Things

Dai

Song

Guo

2018

Sensors

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Computational Intelligence (CI) has been addressed as a great challenge in recent years, particularly the aspects of routing, task scheduling, and other high-complexity issues. Especially for the Contact Plan Design (CPD) that schedules contacts in dynamic and resource-constrained networks, a suitable CI algorithm can be exchanged for a high-quality Contact Plan (CP) with the appropriate computational overhead. Previous works on CPD mainly focused on the optimization of satellite network connectivity, but most of them ignored network topology characteristics. In this paper, we study the CPD issue in the spatial node based Internet of Things (IoT), which enables the spatial nodes to deliver data cooperatively via intelligent networking. Specifically, we first introduce a Multi-Layer Space Communication Network (MLSCN) model consisting of satellites, High Altitude Platforms (HAPs), Unmanned Aerial Vehicles (UAVs), and ground stations, on which a Time-Evolving Graph (TEG) is used to illustrate the CPD process. Then, according to the characteristics of each layer in the MLSCN, we design the corresponding CPs for the inter-layer contacts and intra-layer contacts. After that, a CI algorithm named as Multidirectional Particle Swarm Optimization (MPSO) is proposed for inter-layer CPD, which utilizes a grid-based initialization strategy to expand the diversity of individuals, in which a quaternary search method and quaternary optimization are introduced to improve efficiency of particle swarms in iterations and to ensure the continuous search ability, respectively. Furthermore, an optimized scheme is implemented for the intra-layer CPD to reduce congestion and improve transmission efficiency. Simulation results show that the proposed CPD scheme can realize massive data transmission with high efficiency in the multi-layer spatial node-based IoT.

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Traffic-aware contact plan design for disruption-tolerant space sensor networks

Cited by 40 publications

References 14 publications

On the scalability of battery‐aware contact plan design for LEO satellite constellations

On the scalability of battery‐aware contact plan design for LEO satellite constellations

A Task-Driven Updated Discrete Graph Assisted Minimum Delivery Delay Routing for Remote Sensing Disruption-Tolerant Networks

An Intelligent Computing Method for Contact Plan Design in the Multi-Layer Spatial Node-Based Internet of Things

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