An adaptive approach to space-based picosatellite sensor networks

Tughrul Arslan, Erfu Yang, Nakul Haridas, Alicia Morales, Ahmed O. El-Rayis, Ahmet T. Erdogan, Adrian Stoica

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

Abstract

The rapid advancements in ad hoc sensor networks, MEMS (micro-electro- mechanical systems) devices, low-power electronics, adaptive hardware and systems (AHS), reconfigurable architectures, high-performance computing platforms, distributed operating systems, micro-spacecrafts, and micro-sensors have enabled the design and development of a highperformance satellite sensor network (SSN). Due to the changing environment and the varying missions that a SSN may have, there is an increasing need to develop efficient strategies to design, operate, and manage the system at different levels from an individual satellite node to the whole network. Towards this end, this paper presents an adaptive approach to space-based picosatellite sensor network by exploiting efficient bio-inspired optimization algorithms, particularly for solving multi-objective optimization problems at both local (node) and global (network) system levels. The proposed approach can be hierarchically used for dealing with the challenging optimization problems arising from the energy-constrained satellite sensor networks. Simulation results are provided to demonstrate the effectiveness of the proposed approach through its application in solving both node-level and system-level optimization problems.

LanguageEnglish
Title of host publicationEvolutionary and Bio-Inspired Computation
Subtitle of host publicationTheory and Applications III
EditorsTeresa H. O'Donnell, Misty Blowers, Kevin L. Priddy
Place of PublicationBellingham, Washington
DOIs
Publication statusPublished - 1 Dec 2009
EventEvolutionary and Bio-Inspired Computation: Theory and Applications III - Orlando, FL, United Kingdom
Duration: 14 Apr 200915 Apr 2009

Publication series

NameProceedings of SPIE
PublisherSPIE
Volume7347
ISSN (Print)0277-786X

Conference

ConferenceEvolutionary and Bio-Inspired Computation: Theory and Applications III
CountryUnited Kingdom
CityOrlando, FL
Period14/04/0915/04/09

Fingerprint

Picosatellites
Sensor networks
Sensor Networks
Satellites
sensors
optimization
Computer systems
Vertex of a graph
Low power electronics
Optimization Problem
Reconfigurable architectures
Reconfigurable Architectures
Power Electronics
Computer operating systems
Multiobjective Optimization Problems
Ad hoc networks
Ad Hoc Networks
Multiobjective optimization
Micro-electro-mechanical Systems
Spacecraft

Keywords

  • adaptive systems
  • bio-inspired algorithm
  • multi-objective optimization
  • satellite
  • wireless sensor network

Cite this

Arslan, T., Yang, E., Haridas, N., Morales, A., El-Rayis, A. O., Erdogan, A. T., & Stoica, A. (2009). An adaptive approach to space-based picosatellite sensor networks. In T. H. O'Donnell, M. Blowers, & K. L. Priddy (Eds.), Evolutionary and Bio-Inspired Computation: Theory and Applications III (Proceedings of SPIE; Vol. 7347). Bellingham, Washington. https://doi.org/10.1117/12.820792
Arslan, Tughrul ; Yang, Erfu ; Haridas, Nakul ; Morales, Alicia ; El-Rayis, Ahmed O. ; Erdogan, Ahmet T. ; Stoica, Adrian. / An adaptive approach to space-based picosatellite sensor networks. Evolutionary and Bio-Inspired Computation: Theory and Applications III. editor / Teresa H. O'Donnell ; Misty Blowers ; Kevin L. Priddy. Bellingham, Washington, 2009. (Proceedings of SPIE).
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Arslan, T, Yang, E, Haridas, N, Morales, A, El-Rayis, AO, Erdogan, AT & Stoica, A 2009, An adaptive approach to space-based picosatellite sensor networks. in TH O'Donnell, M Blowers & KL Priddy (eds), Evolutionary and Bio-Inspired Computation: Theory and Applications III. Proceedings of SPIE, vol. 7347, Bellingham, Washington, Evolutionary and Bio-Inspired Computation: Theory and Applications III, Orlando, FL, United Kingdom, 14/04/09. https://doi.org/10.1117/12.820792

An adaptive approach to space-based picosatellite sensor networks. / Arslan, Tughrul; Yang, Erfu; Haridas, Nakul; Morales, Alicia; El-Rayis, Ahmed O.; Erdogan, Ahmet T.; Stoica, Adrian.

Evolutionary and Bio-Inspired Computation: Theory and Applications III. ed. / Teresa H. O'Donnell; Misty Blowers; Kevin L. Priddy. Bellingham, Washington, 2009. (Proceedings of SPIE; Vol. 7347).

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

TY - CHAP

T1 - An adaptive approach to space-based picosatellite sensor networks

AU - Arslan, Tughrul

AU - Yang, Erfu

AU - Haridas, Nakul

AU - Morales, Alicia

AU - El-Rayis, Ahmed O.

AU - Erdogan, Ahmet T.

AU - Stoica, Adrian

PY - 2009/12/1

Y1 - 2009/12/1

N2 - The rapid advancements in ad hoc sensor networks, MEMS (micro-electro- mechanical systems) devices, low-power electronics, adaptive hardware and systems (AHS), reconfigurable architectures, high-performance computing platforms, distributed operating systems, micro-spacecrafts, and micro-sensors have enabled the design and development of a highperformance satellite sensor network (SSN). Due to the changing environment and the varying missions that a SSN may have, there is an increasing need to develop efficient strategies to design, operate, and manage the system at different levels from an individual satellite node to the whole network. Towards this end, this paper presents an adaptive approach to space-based picosatellite sensor network by exploiting efficient bio-inspired optimization algorithms, particularly for solving multi-objective optimization problems at both local (node) and global (network) system levels. The proposed approach can be hierarchically used for dealing with the challenging optimization problems arising from the energy-constrained satellite sensor networks. Simulation results are provided to demonstrate the effectiveness of the proposed approach through its application in solving both node-level and system-level optimization problems.

AB - The rapid advancements in ad hoc sensor networks, MEMS (micro-electro- mechanical systems) devices, low-power electronics, adaptive hardware and systems (AHS), reconfigurable architectures, high-performance computing platforms, distributed operating systems, micro-spacecrafts, and micro-sensors have enabled the design and development of a highperformance satellite sensor network (SSN). Due to the changing environment and the varying missions that a SSN may have, there is an increasing need to develop efficient strategies to design, operate, and manage the system at different levels from an individual satellite node to the whole network. Towards this end, this paper presents an adaptive approach to space-based picosatellite sensor network by exploiting efficient bio-inspired optimization algorithms, particularly for solving multi-objective optimization problems at both local (node) and global (network) system levels. The proposed approach can be hierarchically used for dealing with the challenging optimization problems arising from the energy-constrained satellite sensor networks. Simulation results are provided to demonstrate the effectiveness of the proposed approach through its application in solving both node-level and system-level optimization problems.

KW - adaptive systems

KW - bio-inspired algorithm

KW - multi-objective optimization

KW - satellite

KW - wireless sensor network

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U2 - 10.1117/12.820792

DO - 10.1117/12.820792

M3 - Chapter (peer-reviewed)

SN - 9780819476135

T3 - Proceedings of SPIE

BT - Evolutionary and Bio-Inspired Computation

A2 - O'Donnell, Teresa H.

A2 - Blowers, Misty

A2 - Priddy, Kevin L.

CY - Bellingham, Washington

ER -

Arslan T, Yang E, Haridas N, Morales A, El-Rayis AO, Erdogan AT et al. An adaptive approach to space-based picosatellite sensor networks. In O'Donnell TH, Blowers M, Priddy KL, editors, Evolutionary and Bio-Inspired Computation: Theory and Applications III. Bellingham, Washington. 2009. (Proceedings of SPIE). https://doi.org/10.1117/12.820792