Analysis of Multi-Node QoS in Shrimp Pond Monitoring System with Fog Computing

Authors

  • Anisah Universitas Syiah Kuala, Banda Aceh, Indonesia
  • Rizal Munadi Universitas Syiah Kuala, Banda Aceh, Indonesia
  • Yuwaldi Away Universitas Syiah Kuala, Banda Aceh, Indonesia
  • Al Bahri Universitas Syiah Kuala, Banda Aceh, Indonesia
  • Andri Novandri Universitas Syiah Kuala, Banda Aceh, Indonesia

DOI:

10.33395/sinkron.v9i1.13205

Keywords:

Fog Computing, Quality of Service, Sensors, Water Quality

Abstract

Most of Indonesia’s territory consists of oceans, presenting a significant potential for developing the fisheries sector. Shrimp is among Indonesia’s flagship commodities with substantial export potential. Internationally, Indonesia holds the fourth position as the largest exporter of frozen shrimp globally. However, shrimp cultivation faces various challenges, including declining water quality due to factors such as water sources and weather, which can adversely affect harvest yields. To preempt potential failures, employing smart devices and technology in shrimp cultivation offers an effective and efficient solution for monitoring and management. This study aims to analyze water quality monitoring in ponds considering the speed of data transmission from end devices to fog using Quality of Service (QoS) parameters like delay/latency, throughput, and packet loss. Data transmission tests were conducted at data rates of 5 Mbps and 10 Mbps, with a bandwidth of 1500 Mbps. The study involves three sensors—water temperature, pH, and salinity—placed in shrimp ponds. Test results showed a decrease in throughput by 1.54% at the sensor node and 2.99% at the sink node when packet data delivery encountered barriers like obstacles. There was a 74.13% increase in latency when the delivery distance extended to 35 meters. The achievable delivery range with low latency was up to 10 meters with barriers and 25 meters without. Thus, latency and throughput values vary depending on the presence of barriers and transmission distance. Barriers tend to increase latency and decrease throughput.

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How to Cite

Anisah, Munadi, R., Away, Y., Bahri, A., & Novandri, A. (2024). Analysis of Multi-Node QoS in Shrimp Pond Monitoring System with Fog Computing. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 9(1), 346-354. https://doi.org/10.33395/sinkron.v9i1.13205