File Accessing Models in Distributed System

In a distributed system, multiple computers work together to provide a cohesive service to users. One of most critical components of a distributed system is ability to access files stored on different computers in network. Different file accessing models have been developed to manage this complexity and ensure efficient and secure file sharing. In this article, we will explore various file accessing models in a distributed system.

Centralized File Accessing Model

In a centralized file accessing model, all files are stored on a single server or node, and users access these files through server. This model is simple to implement and manage, as all files are located in a single location, making backup and recovery easy. However, it has a single point of failure, which can lead to entire system's failure.

Example: Network Attached Storage (NAS) is an example of a centralized file accessing model. In NAS, a central server stores all files, and users can access these files over network using protocols such as NFS, CIFS, or SMB.

Distributed File Accessing Model

In a distributed file accessing model, files are distributed across multiple servers or nodes, and users can access these files from any node in network. This model is highly scalable and fault-tolerant, as files are distributed across multiple nodes, reducing risk of a single point of failure.

Example − Hadoop Distributed File System (HDFS) is an example of a distributed file accessing model. In HDFS, files are distributed across multiple nodes in network, and users can access these files using Hadoop File System API.

Peer-to-Peer File Accessing Model

In a peer-to-peer file accessing model, there is no central server or node, and files are distributed across multiple nodes in network. Each node can act as a client or a server, allowing users to access files from any node in network. This model is highly decentralized and fault-tolerant, as there is no single point of failure.

Example

BitTorrent is an example of a peer-to-peer file accessing model. In BitTorrent, files are distributed across multiple nodes, and users can download and upload these files using a peer-to-peer protocol.

Client-Server File Accessing Model

In a client-server file accessing model, clients request files from a central server, and server sends requested files to clients. This model is highly centralized, with a single point of failure, but it is also highly secure, as server can control access to files.

Example − File Transfer Protocol (FTP) is an example of a client-server file accessing model. In FTP, clients request files from an FTP server, and server sends requested files to clients.

Remote Procedure Call (RPC) File Accessing Model

In an RPC file accessing model, clients can call remote procedures on a server to access files. This model is highly scalable, as clients can call remote procedures on multiple servers, and fault-tolerant, as clients can call remote procedures on alternative servers if a server fails.

Example − Network File System (NFS) is an example of an RPC file accessing model. In NFS, clients can call remote procedures on an NFS server to access files.

Let's explore some additional aspects of file accessing models in distributed systems.

Concurrency Control

In a distributed system, multiple users may access same file simultaneously, which can lead to concurrency issues. To prevent these issues, concurrency control mechanisms are used to manage access to files. Two popular mechanisms are −

• Locking − Locking ensures that only one user can access a file at a time. When a user requests access to a file, system grants them an exclusive lock, preventing other users from accessing file until lock is released.

• Versioning − Versioning ensures that each user can access their own version of file, preventing conflicts when multiple users modify same file. When a user modifies a file, system creates a new version of file, allowing other users to access original version.

Access Control

Access control mechanisms are used to control which users can access specific files in a distributed system. Two popular mechanisms are −

• Access Control Lists (ACLs) − ACLs define a list of users and their corresponding permissions to access files. When a user requests access to a file, system checks their credentials against ACL to determine if they have permission to access file.

• Role-Based Access Control (RBAC) − RBAC defines a set of roles, each with a set of permissions to access files. When a user requests access to a file, system assigns them a role based on their credentials, and system checks user's role against RBAC to determine if they have permission to access file.

File Replication

In a distributed system, files can be replicated across multiple nodes to improve performance and fault tolerance. When a file is replicated, multiple copies of file are stored on different nodes in network. This allows users to access file from any node in network, reducing latency and improving fault tolerance.

File Caching

In a distributed system, file caching is used to improve performance by storing frequently accessed files on a local node's cache. When a user requests a file, system checks if file is already in local cache, and if so, serves file from cache instead of fetching it from a remote node. This reduces network latency and improves performance.

Here are some additional information regarding file accessing models in distributed systems:

Distributed File Systems

Distributed file systems are designed to provide a consistent and reliable way to access files across a distributed network. Examples of distributed file systems include Hadoop Distributed File System (HDFS) and Google File System (GFS). These file systems are designed to scale horizontally, which means that as more nodes are added to network, file system can continue to provide efficient and reliable access to files.

HDFS is widely used in big data processing systems such as Hadoop and Spark. It is designed to handle large data sets and is optimized for sequential read/write operations. HDFS uses a master-slave architecture, where NameNode acts as a master and manages metadata of files, while DataNodes act as slaves and store actual file data.

GFS, on other hand, is designed for high-throughput, low-latency access to large files. It is used as file system for Google's MapReduce system, which is used for large-scale data processing. GFS uses a similar master-slave architecture, where Master manages metadata, and chunks of data are stored on ChunkServers.

Cloud File Systems

Cloud file systems are a type of distributed file system that is designed to provide access to files stored in cloud. Examples of cloud file systems include Amazon S3 and Microsoft Azure Blob Storage. These file systems are designed to be scalable and fault-tolerant, providing access to files from anywhere in world.

Amazon S3 is a popular cloud file system used for storing and retrieving data. It is designed to be highly scalable, providing access to millions of objects stored in cloud. It provides features such as versioning, lifecycle policies, and encryption, making it a secure and reliable way to store data in cloud.

Microsoft Azure Blob Storage is another cloud file system that is used for storing and retrieving data. It provides features such as geo-replication, access control, and encryption, making it a secure and reliable way to store data in cloud. It is designed to be highly scalable, providing access to terabytes of data stored in cloud.

Conclusion

In a distributed system, file accessing models are critical for efficient and secure file sharing. Each model has its advantages and disadvantages, and choice of a model depends on specific needs of system. Understanding different file accessing models is essential for designing and implementing an efficient and fault-tolerant distributed system.