Mohammad Alsulami, Raafat S. Elfouly, R. Ammar, Huda Aldosari
{"title":"Deployment of Multiple Computing Systems in Underwater Wireless Sensor Networks","authors":"Mohammad Alsulami, Raafat S. Elfouly, R. Ammar, Huda Aldosari","doi":"10.1109/ISSPIT51521.2020.9408925","DOIUrl":null,"url":null,"abstract":"Underwater Wireless Sensor Networks(UWSNs) have emerged as a promising technology that is used to monitor underwater environment. Applications of UWSNs are numerous such as oil and gas pipeline monitoring, underwater animal detection, and object of interest detection. Automated Underwater Vehicles (AUVs) have been used to monitor underwater environment [13]. One of the significant challenges of AUVs usage is that it does not meet real-time constraints [15]. Researchers in [1] developed a real-time computing system that can collect, process, and transmit data to a gateway in real-time using a single processing node (computer). Nevertheless, a single computer cannot handle the whole load; Resources and equipment in general are limited. Thus, in this paper, we propose two approaches/algorithms that can group master nodes in the network into groups and allocate a computer for each group. In the first algorithm, we cluster master nodes using bottom-up approach. The process of assigning master nodes, in this approach, to groups is based on the communication range. In the second algorithm, nodes are deployed not only homogeneously but also heterogeneously. We add more constraints in order to make our assumptions are closer to real life. In result section, we provide some insights about our experiments. Simulation results show the merit of our proposed approaches.","PeriodicalId":111385,"journal":{"name":"2020 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT51521.2020.9408925","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Underwater Wireless Sensor Networks(UWSNs) have emerged as a promising technology that is used to monitor underwater environment. Applications of UWSNs are numerous such as oil and gas pipeline monitoring, underwater animal detection, and object of interest detection. Automated Underwater Vehicles (AUVs) have been used to monitor underwater environment [13]. One of the significant challenges of AUVs usage is that it does not meet real-time constraints [15]. Researchers in [1] developed a real-time computing system that can collect, process, and transmit data to a gateway in real-time using a single processing node (computer). Nevertheless, a single computer cannot handle the whole load; Resources and equipment in general are limited. Thus, in this paper, we propose two approaches/algorithms that can group master nodes in the network into groups and allocate a computer for each group. In the first algorithm, we cluster master nodes using bottom-up approach. The process of assigning master nodes, in this approach, to groups is based on the communication range. In the second algorithm, nodes are deployed not only homogeneously but also heterogeneously. We add more constraints in order to make our assumptions are closer to real life. In result section, we provide some insights about our experiments. Simulation results show the merit of our proposed approaches.