Maximization of Underwater Sensor Networks Lifetime via Fountain Codes


Yıldız H. U.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, cilt.15, sa.8, ss.4602-4613, 2019 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 8
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1109/tii.2019.2892866
  • Dergi Adı: IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.4602-4613
  • Anahtar Kelimeler: Automatic repeat request (ARQ), fountain codes (FCs), integer linear programming (ILP), network lifetime (NL), underwater acoustic sensor networks (UASNs), RELIABLE DATA TRANSFER, ALGORITHMS, TRANSMISSIONS, OPTIMIZATION
  • TED Üniversitesi Adresli: Evet

Özet

The severe nature of underwater channel poses a great challenge for prolonging underwater acoustic sensor networks (UASNs) lifetime and achieving a reliable communication performance. Traditional approaches to improve the reliability such as automatic repeat request (ARQ) negatively affect the network lifetime (NL) due to energy dissipation caused by ARQ retransmission. A forward error correction (FEC) technique called fountain codes (FCs) can solve the energy efficiency problem of ARQ by transmitting both the original packet and some redundant packets to ensure a targeted reliability with few or no retransmissions. In this paper, we investigate performances of both traditional ARQ-and FC-based FECmethods in terms ofNL, end-to-end delay, energy consumption, and frame error rate (FER) for UASNs. In this context, we abstract energy dissipation characteristics of conventional ARQ-and FC-based FECmethod at the link-layer. We propose an integer linear programming (ILP) framework that maximizes the NL, which is operated on top of developed link-layer energy consumption models. Our results reveal that FC-based FEC methods can prolong the NL at a minimum of 16% while end-to-end delay, energy consumption, and FER can be reduced at least by 11%, 14%, and 9% as compared to classical ARQ, respectively.