Questions and Answers
What does the term 'No SPOF' signify in the context of distributed computing?
Which characteristic best describes a 'computing intensive' application in distributed computing?
What is a primary advantage of load sharing in distributed computing?
In the context of distributed computing, what does 'data intensive' imply?
Signup and view all the answers
Why is distributed computing considered robust?
Signup and view all the answers
What is a defining characteristic of distributed applications?
Signup and view all the answers
Which of the following best describes grid computing?
Signup and view all the answers
In which way does grid computing improve computing capabilities?
Signup and view all the answers
What transition does 'peer-to-peer' computing signify in the context of distributed applications?
Signup and view all the answers
What limitation do conventional networks generally have compared to grid computing?
Signup and view all the answers
Study Notes
Distributed Computing
- Resource sharing enables users to utilize the computing power and storage of a system collectively.
- Load sharing distributes various tasks across nodes, optimizing overall system performance.
- Easy node expansion is anticipated to be quick and efficient with minimal time investment.
- Parallel computing is a subset within the broader category of distributed computing.
Nature of Applications in Distributed Computing
- Computing Intensive: Tasks that require extensive computation time, such as calculating Pi using Monte Carlo methods.
- Data Intensive: Involves handling large volumes of data, exemplified by platforms like Facebook and LHC data processing.
- Robustness: Absence of a Single Point Of Failure (SPOF); if one node fails, other nodes can continue the same task without interruption.
Distributed Applications
- Comprise processes dispersed across a network, working collaboratively to solve common issues.
- Historically centered around "client-server" models, which centralized resource management.
- The shift towards "Peer to Peer" computing promotes genuinely distributed applications.
Grid Computing
- A networking form that leverages unused processing power across computers for complex problem-solving.
- Virtualizes computing and data resources, providing a collective single-system image.
- Essential for scientific research, enabling computer simulations, data analysis, and enhanced data visualization.
- Facilitates efficient use of underutilized resources.
Types of Grids
- Computational Grid: Provides shared processing power for high-throughput applications.
- Data Grid: Supports storage, discovery, handling, and manipulation of large datasets from heterogeneous sources.
- Collaboration Grid: Enhances collaborative projects across organizations without revealing proprietary information.
- Network Grid: Offers high-performance, fault-tolerant communication services.
- Utility Grid: Shares not only data and computation but also software and resources, allowing applications to run on singular machines while serving multiple users.
Cluster Computing
- Consists of interconnected standalone computers working collaboratively as a single resource.
- Improves speed and reliability compared to a single computer, typically being more cost-effective.
- Employs high-performance interconnects and low-latency protocols to enhance communication.
Types of Clusters
- High Availability/Failover Clusters: Ensure continuous system availability through redundancy.
- Load Balancing Clusters: Distribute workloads evenly across multiple computers.
- Parallel/Distributed Processing Clusters: Enhance processing capabilities by dividing tasks among several nodes.
Key Operational Benefits of Clustering
- High system availability due to hardware redundancy.
- Supports varied business models such as pay-for-use and optimal resource utilization.
- Enables data center virtualization and provisioning.
- Streamlines web services delivery and automation processes.
Utility Computing
- On-demand cyber infrastructure providing flexible services to consumers and businesses.
- Pricing models mimic traditional utility services, including flat rates, tiered pricing, and pay-as-you-go systems.
- Risks include data backup, security, partner competency, and defining Service Level Agreements (SLAs).
Cloud Computing
- Defined by the US National Institute of Standards and Technology as a model for ubiquitous network access to shared configurable computing resources.
- Focuses on rapid provisioning with minimal management effort or service interactions, emphasizing convenience and scalability.
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Description
This quiz explores the fundamental concepts of distributed computing, including resource sharing, load sharing, and performance. Understand how these elements contribute to the efficiency and scalability of computing systems. It's essential for anyone looking to enhance their knowledge in computer science and engineering.
