Enhancing Sensor Network Performance through Cloud Computing and Virtualization: An Architectural Approach
Year: 2025
Type: article
Abstract: Sensor networks are increasingly integral to modern applications such as industrial automation, environmental monitoring, and smart infrastructure.As these networks grow in scale and complexity, the volume, variety, and velocity of generated data introduce significant challenges for traditional Sensor Information Systems (SIS).These challenges include scalability limitations, high operational costs, heterogeneous data processing, and inefficient resource allocation.This paper presents a cloud-based architecture model for sensor information systems to address these issues.The proposed model integrates cloud computing and sensor virtualization technologies to construct a flexible, scalable, cost-effective SIS.The architecture features a multi-layered structure, including a secure user front-end, application management, service orchestration, and a virtualization layer that abstracts physical sensor resources.This enables transparent access to data and dynamic provisioning of computational and storage resources.By leveraging the elasticity and service-oriented nature of cloud computing, the model supports real-time processing and efficient management of sensor data.Sensor virtualization further enhances system flexibility by representing one physical sensor as multiple virtual instances, enabling resource sharing and dynamic scaling based on demand.The proposed system is designed to support a wide range of sensor network configurations-wired or wireless, homogeneous or heterogeneous-and to improve performance through dynamic load balancing, efficient data handling, and user-centric service delivery.Overall, this architecture offers a generalizable and adaptive solution for the evolving demands of sensor-based applications, positioning itself as a promising approach to modern sensor information system design.
Authors: Hye-Seen Kang, Si-Yeong Kim, Tai-hoon Kim
Institution: Chonnam National University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W7083708510
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