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HGL: A hybrid global-local load balancing routing scheme for the Internet of Things through satellite networks

Ziluan Liu,Jiangsheng Li,Yanru Wang,Xin Li,Shan-zhi Chen

Published 2017 in Int. J. Distributed Sens. Networks

ABSTRACT

Satellite networks provide complete connectivity and worldwide data transmission capability for constructing the Internet of Things. However, because of the varying Internet of Things traffic density, satellite networks may endure imbalanced traffic requirements and frequent link congestion. To effectively resolve these problems and optimally transmit Internet of Things data, a novel hybrid global-local load balancing routing scheme for Low Earth Orbit satellite networks is proposed in this article. Hybrid global-local load balancing routing scheme enables satellites to route Internet of Things traffic through global planning and local real-time adjustments in two steps. In hybrid global-local load balancing routing scheme, given the predictive nature of Internet of Things traffic distribution and Low Earth Orbit satellite networks, the inter-satellite traffic demand is decomposed into a predictable long-range baseline and unpredictable short-range fluctuations. A global strategy is employed first for preliminary global traffic allocation based on long-range baselines, and a local strategy is then employed for route adjustments based on short-range fluctuations. With the combination of global planning and local real-time adjustments, network traffic can eventually obtain a near-optimal allocation. Numerical simulations indicate that in contrast to single-strategy schemes, hybrid global-local load balancing routing scheme can more thoroughly eliminate congestion, and it performs better in measures such as packet loss rate, average queuing delay, traffic distribution, route oscillation, and communication overhead.

PUBLICATION RECORD

  • Publication year

    2017

  • Venue

    Int. J. Distributed Sens. Networks

  • Publication date

    2017-03-01

  • Fields of study

    Computer Science, Engineering, Environmental Science

  • Identifiers
    DOI 10.1177/1550147717692586
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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