It is now possible to use low-power, smart, micro-node sensors to monitor the functions of the human body. A wireless body area network (WBAN) is a wireless network consisting of a group of tiny biomedical nodes distributed inside or near the body of some person. One of the most critical problems of this technology is that sensor nodes usually have limited energy because of its size. Data collection from nodes to sink is the major task performed by sensor nodes. Therefore, efficient data collection protocols allows for better energy consumption. This article focuses on data collection protocols. These protocols referred to as convergecast strategies. This article studies the adoption of similar strategies in similar environment to evaluate their efficacy for being used in WBAN. Similar environment involves Delay Tolerant Network (DTN), Ad-Hoc, Wireless Sensor Network (WSN), etc. Some of these strategies have been implemented and evaluated in terms of power consumption, end-to-end delay and end-to-end success rate. The results show that each of the existing strategies outperform the others according to a specific metric. It is ensured that, the performance of existing strategies deteriorate with the movement of the body which is a default behavior in WBAN. In addition, most strategies have high power consumption. Therefore, it becomes clear that existing strategies still need more improvements to cope with the specific needs of WBAN. In a future work, a data collection strategy from cross layer can be incorporated aiming to improve the power saving capability at the sensor nodes.
Soliman, A., Mousa, H., & Amin, K. (2022). Convergecast strategies for Wireless Body Area Networks environment : state of the art. IJCI. International Journal of Computers and Information, 9(2), 1-13. doi: 10.21608/ijci.2022.109178.1065
MLA
Ahmed Elsayed Soliman; Hayam Mousa; Khalid Amin. "Convergecast strategies for Wireless Body Area Networks environment : state of the art", IJCI. International Journal of Computers and Information, 9, 2, 2022, 1-13. doi: 10.21608/ijci.2022.109178.1065
HARVARD
Soliman, A., Mousa, H., Amin, K. (2022). 'Convergecast strategies for Wireless Body Area Networks environment : state of the art', IJCI. International Journal of Computers and Information, 9(2), pp. 1-13. doi: 10.21608/ijci.2022.109178.1065
VANCOUVER
Soliman, A., Mousa, H., Amin, K. Convergecast strategies for Wireless Body Area Networks environment : state of the art. IJCI. International Journal of Computers and Information, 2022; 9(2): 1-13. doi: 10.21608/ijci.2022.109178.1065
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