{"title":"ADA2−IoT : An adaptive data aggregation algorithm for IoT infrastructure","authors":"","doi":"10.1016/j.iot.2024.101299","DOIUrl":null,"url":null,"abstract":"<div><p>In IoT infrastructure, high-frequency sensing and subsequent transmission of sensed data to computational facilities can lead to redundant data storage and processing, consuming significant storage and processing capacity. As a result, the IoT infrastructure needs more data transmission cycles, leading to data redundancy and low network up-time due to the drainage of limited battery capacity. Conversely, if the data is communicated at a lower rate, it may cause absolute data delivery to the processing unit, which is useless. As a result, a well-designed data aggregation algorithm is required. This paper proposes the <span><math><mrow><mi>A</mi><mi>D</mi><msup><mrow><mi>A</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>−</mo><mi>I</mi><mi>o</mi><mi>T</mi></mrow></math></span>, an Adaptive Data Aggregation Algorithm for IoT Infrastructure tailored to optimize parameters such as low data redundancy, limited data communication cycles, and high IoT infrastructure up times. The proposed algorithm consists of two key components: the Route Data Aggregator (RDA) performs aggregation during data transit towards the Edge node or gateway, and the Node Data Aggregator (NDA) performs data aggregation during capturing or sensing data. The algorithm employs metrics like Age of Information (AoI) and data freshness factor during the node and route data aggregation phase to capture and timely deliver data to the Edge node, where this data is processed for informed decision-making. The proposed algorithm was efficiently tested on a simulation and IoT hardware deployment environment. Both simulation and hardware results demonstrate a substantial improvement in QoS parameters, such as a decrease in data redundancy and packet exchanges, leading to considerable energy savings and prolonging the lifespan of IoT infrastructure.</p></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet of Things","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2542660524002403","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
In IoT infrastructure, high-frequency sensing and subsequent transmission of sensed data to computational facilities can lead to redundant data storage and processing, consuming significant storage and processing capacity. As a result, the IoT infrastructure needs more data transmission cycles, leading to data redundancy and low network up-time due to the drainage of limited battery capacity. Conversely, if the data is communicated at a lower rate, it may cause absolute data delivery to the processing unit, which is useless. As a result, a well-designed data aggregation algorithm is required. This paper proposes the , an Adaptive Data Aggregation Algorithm for IoT Infrastructure tailored to optimize parameters such as low data redundancy, limited data communication cycles, and high IoT infrastructure up times. The proposed algorithm consists of two key components: the Route Data Aggregator (RDA) performs aggregation during data transit towards the Edge node or gateway, and the Node Data Aggregator (NDA) performs data aggregation during capturing or sensing data. The algorithm employs metrics like Age of Information (AoI) and data freshness factor during the node and route data aggregation phase to capture and timely deliver data to the Edge node, where this data is processed for informed decision-making. The proposed algorithm was efficiently tested on a simulation and IoT hardware deployment environment. Both simulation and hardware results demonstrate a substantial improvement in QoS parameters, such as a decrease in data redundancy and packet exchanges, leading to considerable energy savings and prolonging the lifespan of IoT infrastructure.
期刊介绍:
Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT.
The journal will place a high priority on timely publication, and provide a home for high quality.
Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.