A Systematic Review of Data Collection Methods in Sensor-Cloud Environments
Vennila P1*, Maniraj V2
Abstract
The integration of cloud computing with Wireless Sensor Networks (WSNs) to form Sensor‑cloud architectures enhances the data processing and storage capabilities of traditional WSNs. Given the inherent communication limitations of WSNs, efficiently collecting, and transmitting sensor data to the cloud within restricted time frames has become a central challenge in Sensor‑cloud systems. Over the past decade, growing research interest in this area has led to a significant number of studies and contributions. The primary goal of this work is to systematically examine current research related to data collection in Sensor‑cloud environments. Accordingly, the study aims to identify, classify, and synthesize key literature in this field. To achieve this, an evidence‑based systematic review methodology was employed. Using this approach, 43 relevant studies were identified and analyzed to address the established research questions. This methodology ensures a rigorous, transparent, and repeatable process for selecting and evaluating studies. The findings reveal that research output on Sensor‑cloud data collection has remained relatively steady over the past five years. Ten main types of contributions most commonly system designs, frameworks, and algorithms were identified across the selected studies. Ultimately, the review highlights several research challenges and outlines future directions to support the development of more effective data collection solutions. Although interest in Sensor‑cloud data collection is growing, existing work remains insufficient, and more robust, well‑defined proposals are required to advance the field.
Keywords:
Data collection, sensor cloud, the Internet of Things (IoT) wireless sensor networks (WSN), systematic literature review (SLR)
