survey

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Transcriptional Regulatory Network Topology with Applications to Bio-inspired Networking: A Survey

Authors:

Sajal K. DasAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 54, Issue 8

Article No.: 166, Pages 1 - 36

https://doi.org/10.1145/3468266

Published: 04 October 2021 Publication History

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Abstract

The advent of the edge computing network paradigm places the computational and storage resources away from the data centers and closer to the edge of the network largely comprising the heterogeneous IoT devices collecting huge volumes of data. This paradigm has led to considerable improvement in network latency and bandwidth usage over the traditional cloud-centric paradigm. However, the next generation networks continue to be stymied by their inability to achieve adaptive, energy-efficient, timely data transfer in a dynamic and failure-prone environment—the very optimization challenges that are dealt with by biological networks as a consequence of millions of years of evolution. The transcriptional regulatory network (TRN) is a biological network whose innate topological robustness is a function of its underlying graph topology. In this article, we survey these properties of TRN and the metrics derived therefrom that lend themselves to the design of smart networking protocols and architectures. We then review a body of literature on bio-inspired networking solutions that leverage the stated properties of TRN. Finally, we present a vision for specific aspects of TRNs that may inspire future research directions in the fields of large-scale social and communication networks.

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W. Chen, W. Lu, and N. Zhang. 2012. Time-critical influence maximization in social networks with time-delayed diffusion process. In Proceedings of the 26th AAAI Conference on Artificial Intelligence.

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Cited By

Chen NQiu TZhou XZhang SSi WOliver Wu D(2024)A Distributed Co-Evolutionary Optimization Method With Motif for Large-Scale IoT RobustnessIEEE/ACM Transactions on Networking10.1109/TNET.2024.340776932:5(4085-4098)Online publication date: Oct-2024
https://doi.org/10.1109/TNET.2024.3407769
Halder SRoy SGhosh PGhosh N(2024) ADRIN2.0 : Enabling Post-Disaster Communication Through Ad aptive Mobility-Informed R out in g IEEE Access10.1109/ACCESS.2024.343286612(102368-102380)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3432866
Roy SDas S(2023)Bio-Inspired Design of Biosensor NetworksEncyclopedia of Sensors and Biosensors10.1016/B978-0-12-822548-6.00131-X(86-102)Online publication date: 2023
https://doi.org/10.1016/B978-0-12-822548-6.00131-X

Index Terms

Transcriptional Regulatory Network Topology with Applications to Bio-inspired Networking: A Survey
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
    1. Redundancy
  2. Embedded and cyber-physical systems
    1. Embedded systems
    2. Robotics
2. Networks
  1. Network properties
    1. Network reliability

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 54, Issue 8

November 2022

754 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3481697

Editor:
Albert Zomaya
University of Sydney, Australia

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Copyright © 2021 Association for Computing Machinery.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 October 2021

Accepted: 01 May 2021

Revised: 01 March 2021

Received: 01 January 2020

Published in CSUR Volume 54, Issue 8

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Cited By

Chen NQiu TZhou XZhang SSi WOliver Wu D(2024)A Distributed Co-Evolutionary Optimization Method With Motif for Large-Scale IoT RobustnessIEEE/ACM Transactions on Networking10.1109/TNET.2024.340776932:5(4085-4098)Online publication date: Oct-2024
https://doi.org/10.1109/TNET.2024.3407769
Halder SRoy SGhosh PGhosh N(2024) ADRIN2.0 : Enabling Post-Disaster Communication Through Ad aptive Mobility-Informed R out in g IEEE Access10.1109/ACCESS.2024.343286612(102368-102380)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3432866
Roy SDas S(2023)Bio-Inspired Design of Biosensor NetworksEncyclopedia of Sensors and Biosensors10.1016/B978-0-12-822548-6.00131-X(86-102)Online publication date: 2023
https://doi.org/10.1016/B978-0-12-822548-6.00131-X
Al Musawi ARoy SGhosh P(2022)Identifying accurate link predictors based on assortativity of complex networksScientific Reports10.1038/s41598-022-22843-412:1Online publication date: 27-Oct-2022
https://doi.org/10.1038/s41598-022-22843-4

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