Centrally controlled systems are designed to manage and operate from a single point of control, typically through a central server or control unit.
This architecture streamlines decision-making and data processing, making it a common choice for various applications, particularly in environments where centralized management is essential.
In a controlled system, decisions are made from a single point rather than being spread out across different locations.
Distributed Systems
Distributed systems refer to a collection of independent computers or nodes that collaborate to achieve a common goal while appearing to users as a single coherent system.
These systems can operate over local area networks (LANs), wide area networks (WANs), or even the internet, allowing multiple devices to communicate and share resources seamlessly.
Distributed System
Structure
Centrally Controlled Systems
All decision-making, control, and processing happen at a central node or server.
All other devices (clients) are dependent on this central hub for instructions and data processing.
Distributed Systems
Processing and decision-making are spread across multiple nodes.
Each node operates semi-independently, collaborating with others to perform tasks.
In a distributed system, each node can operate independently, leading to .
Performance
Centrally Controlled Systems
Performance can degrade if the central server becomes overloaded, leading to slower response times or system failures.
Since there’s a single point of processing, the system can experience bottlenecks when handling large tasks or many users.
Distributed Systems
Performance tends to scale better, as tasks are spread across multiple nodes.
The system can handle more concurrent processes since work is distributed. Bottlenecks are less common.
Distributed systems often improve performance by allowing processing of requests.
Security
Centrally Controlled Systems
Security is concentrated at the central hub. If the central server is breached, the entire system can be compromised.
Easier to manage security because all protective measures can be focused on a single point.
Distributed Systems
Security can be more complex due to the multiple nodes, which increases the potential attack surfaces.
However, the distributed nature means a compromise of one node doesn’t necessarily affect the entire system.
In distributed systems, security is more challenging because data is spread across multiple .
Scalability
Centrally Controlled Systems
Scalability is limited by the capacity of the central server.
Expanding the system often requires significant upgrades to the central control point, which can be expensive and time-consuming.
Distributed Systems
Distributed systems are highly scalable. New nodes can be added to the system to expand capacity with minimal disruption.
Scaling is often smoother and more cost-efficient, particularly for cloud-based or peer-to-peer systems.
One advantage of systems is that they can scale more easily than centralised systems.
Fault Tolerance
Centrally Controlled Systems
Highly vulnerable to failure at the central point. If the central node goes down, the entire system may fail.
Distributed Systems
More resilient to failure. If one node fails, others can continue to operate, providing redundancy and reducing downtime.
systems often improve redundancy and reliability because if one component fails, others can still operate.
A potential drawback of centralised systems is that they can create a point of failure.
Examples and Use Cases
Centrally Controlled Systems
Examples: Traditional banking systems, legacy enterprise systems, older networked databases.
Use Cases: Smaller organizations, environments with less data traffic, applications that need a simple and highly controlled structure (e.g., point-of-sale systems).
Use Cases: Large organizations, high-availability environments, services needing fast and scalable solutions (e.g., global e-commerce, streaming services).
Which of the following is an example of a distributed system?
Distributed systems often enhance by spreading resources across multiple nodes.
Data Management
Centralized Controlled Systems
Data Storage: Centralized in one repository
Data Security: Concentrated security but a single point of vulnerability
Data Backup and Recovery: Simplified backup and recovery
Data Management: Easier updates and maintenanc
Distributed Systems
Data Storage: Distributed across multiple nodes
Data Security: More complex security, resilience against node failures
Data Backup and Recovery: Redundant backups at each node, more complex recovery
Data Management: Complex management and synchronization needs
Distributed systems often require complex mechanisms to maintain data integrity.
