Importance of Value Education in Young India: Social Awareness and Cultural Values

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Value education plays a crucial role in shaping the youth of India by instilling moral values, cultural awareness, and social responsibility. Through teachings of diversity, tolerance, and respect, individuals are guided towards personal growth and understanding of societal principles. Values such as honesty, discipline, and unity are emphasized to nurture a generation that values social purpose over personal gain. This holistic approach towards education helps in creating a harmonious and ethical society.

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MASTER MEIM 2021-2022 Cloud Computing: Managing Data - Files and Binary Large Objects Digital Tech Prof. Raffaele Montella Associate Professor in Computer Science - Universit degli Studi di Napoli Parthenope www.meim.uniparthenope.it

Introduction Data storage was the first cloud service. Amazon launched Simple Storage Service (S3) in 2006. 2008: Dropbox: replaces USB drive exchange with the cloud. Microsoft SkyDrive (OneDrive in 2014). In 2012 Google launched Google Drive. Access data from anywhere, anytime, any device. With the exception of S3, the others mimic a file system.

Introduction File System storage: Familiar to tech savvy people. Is attached to the device as virtual drive. Needs for synchronization. Blob storage: Binary Large Object. Flat model of data. Really scalable.

Storage as a Service Data is the golden coin of science and engineering realm. Data storage, management (and processing) are one of the more remarkable services on the cloud.

Storage as a Service UC1 from models : meteo@uniparthenope produces monthly about 5 TB of Network Common Data Form (NetCDF) that have to be stored for 3 years and be accessible using a portal. UC2 from sensors : due to monitoring the Vesuvio activity, a seismic observatory collects 100 TB per measurement campaign of Comma Separated Values data. UC3 crowdsourced : in a data crowdsourcing scenario DYNAMO users collect (totally) several thousands of records per seconds. While each record is small, the full collection management is challenging.

Use Cases: Managing Environmental Data Different cloud providers offer data service matching many storage models. The design of a cloud application is strictly related to the storage model (and costs).

File System Familiar to every scientist or engineer. Intuitive storage abstraction. Portable Operating System Interface (POSIX APIs). Works with Linux, MacOS, Windows. Command Line, GUI, APIs.

File System Hierarchically organized in directories and files. Regular software doesn t need for cloud customization. Hierarchically could match data semantic organization. Concurrent access by multiple readers. Lustre ( 90s) is the first parallel file system.

Use Cases The File System storage can be used for UC1, UC2 and UC3. Leaks of data consistency tools. The user/application has to know the data stored in each file. Scalability: Usually the cloud File Systems suffer in scaling when data increase in size. For large data size, different models are used on the cloud.

Cloud Services: File Systems Virtual data drivers. Amazon Block Storage. Amazon Elastic File System (EFS).

Cloud Services: File Systems Microsoft Azure File Storage Attached FS using Samba (SMB) protocol. Google Cloud attached File System: Persistent Disks (64TB) - based on object store. Local SSD (max 3TB) - attached to an instance. Ram Disk (max 208 GB) - attached to an instance.

Object Store Unstructured data is stored as BLOB. Different cloud providers use different names for BLOBs. Technically it is simpler than a File System. There is no hierarchy. There is no updating, just versioning or deleting.

Object Store BLOBs are identified by URLs. BLOBs are accessed using HTTPS requests or API calls. Easy to replicate: Reliability. Performance. Security. Resiliency.

Object Store Limits: Data organization. Search Tools. The user needs to know the BLOBs URLs.

Use Cases The Object Store could work with the UC1 if NetCDF hierarchy is implemented as data partitioning. BLOBs are not adequate for the UC2 for managing CSV files. If we store all CSVs in an object, the user has to download the full BLOB. As for UC2, for UC3 the Object Store model suffers about the same limitations.

Use Cases Object1.v3 Metadata:netcdf Object1.v2 Metadata:netcdf Object1.v1 Metadata:netcdf Object2.v1 Metadata:jpeg One Object Store, many containers. Each object has some metadata. Different objects grouped matching the metadata.

Cloud Services: Object Store Amazon Simple Storage Service (S3): Trillions of objects. Billions of containers. The containers are called Buckets. Glacier: cheap and slow long persistence object store.

Cloud Services: Object Store Azure Blob (basic object store, as S3) Azure Storage Explorer http://storageexplorer.com Google Cloud Store (similar to S3): Standard. Regional. Nearline. Coldline (as Glacier). OpenStack Swift .

Conclusions Data management is a key feature of any cloud system. File Systems are a good solution for small amount of data that have to be accessed by regular software. Object store is an affordable solution for unstructured data that can be flattered and accessed concurrently using HTTP or APIs.