Data Management in Pervasive Systems (Data-Centric Systems and

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Pervasive systems, also known as ubiquitous computing systems, are characterized by the presence of interconnected devices and sensors that collect and exchange data in real-time. These systems are often used in smart homes, smart cities, healthcare monitoring, and industrial automation.

Data management in pervasive systems is crucial for ensuring that the vast amount of data generated by these devices is stored, processed, and analyzed efficiently. Data-centric systems and databases play a key role in managing this data effectively.

Here are some key considerations for data management in pervasive systems:

1. Data collection: Pervasive systems generate a large volume of data from various sources, such as sensors, devices, and applications. It is important to have a robust data collection mechanism in place to ensure that all relevant data is captured accurately.

2. Data storage: Storing data in a reliable and secure manner is essential in pervasive systems. Data-centric systems like databases provide a structured way to store and organize data, making it easier to access and analyze.

3. Data processing: Once the data is collected and stored, it needs to be processed and analyzed to extract valuable insights. Data-centric systems can help in processing large datasets efficiently, enabling real-time decision-making.

4. Data security: With the proliferation of interconnected devices in pervasive systems, ensuring data security is paramount. Data-centric systems offer features like encryption, access control, and data masking to protect sensitive information from unauthorized access.

5. Data integration: Pervasive systems often involve disparate data sources that need to be integrated for comprehensive analysis. Data-centric systems provide tools for data integration, allowing users to combine data from multiple sources seamlessly.

Overall, effective data management in pervasive systems requires a combination of robust data-centric systems, data governance policies, and data analytics capabilities. By implementing best practices in data management, organizations can harness the full potential of pervasive systems and derive meaningful insights from the data they generate.
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