Podcast
Questions and Answers
Which feature is essential for systems in distributed environments to easily work together?
Which feature is essential for systems in distributed environments to easily work together?
Which factor does NOT contribute to the scalability challenges of centralized solutions?
Which factor does NOT contribute to the scalability challenges of centralized solutions?
What is a primary concern when implementing policies in distributed systems?
What is a primary concern when implementing policies in distributed systems?
Which type of scalability refers to the number of administrative domains involved in a distributed system?
Which type of scalability refers to the number of administrative domains involved in a distributed system?
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What does hard coding policies typically simplify in a distributed system?
What does hard coding policies typically simplify in a distributed system?
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What is a significant trade-off of strict separation between policy and mechanism?
What is a significant trade-off of strict separation between policy and mechanism?
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Which of the following is NOT a component used to measure scalability in distributed systems?
Which of the following is NOT a component used to measure scalability in distributed systems?
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Which mechanism can help address varying Quality of Service (QoS) requirements in distributed systems?
Which mechanism can help address varying Quality of Service (QoS) requirements in distributed systems?
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What is a key benefit of using computational grids?
What is a key benefit of using computational grids?
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What technique is used to hide communication latencies in systems?
What technique is used to hide communication latencies in systems?
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What is a potential problem mentioned when using replication in data systems?
What is a potential problem mentioned when using replication in data systems?
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In the context of scaling, why might computations be moved to clients?
In the context of scaling, why might computations be moved to clients?
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Which of the following correctly describes a shared equipment scenario?
Which of the following correctly describes a shared equipment scenario?
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How can replication and caching improve system performance?
How can replication and caching improve system performance?
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Which technique is most likely not beneficial in keeping copies of data consistent after modification?
Which technique is most likely not beneficial in keeping copies of data consistent after modification?
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Which of the following best illustrates a peer-to-peer network?
Which of the following best illustrates a peer-to-peer network?
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What does the utilization U of a service indicate?
What does the utilization U of a service indicate?
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If the arrival rate of requests is $ ext{λ}$ and processing capacity is $ ext{μ}$, how is the response time $R$ calculated?
If the arrival rate of requests is $ ext{λ}$ and processing capacity is $ ext{μ}$, how is the response time $R$ calculated?
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What happens to the system when utilization U approaches 1?
What happens to the system when utilization U approaches 1?
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How is the average number of requests in the system $N$ expressed mathematically?
How is the average number of requests in the system $N$ expressed mathematically?
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In a queuing system, the arrival rate and processing capacity feed into what critical measurement of performance?
In a queuing system, the arrival rate and processing capacity feed into what critical measurement of performance?
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Which statement best describes the relationship between service time S and processing capacity μ?
Which statement best describes the relationship between service time S and processing capacity μ?
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What challenge does geographical scalability present in distributed systems?
What challenge does geographical scalability present in distributed systems?
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What is a crucial solution to the scalability problems experienced in administrative systems?
What is a crucial solution to the scalability problems experienced in administrative systems?
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Study Notes
Openness of Distributed Systems
- Open systems can interact with each other regardless of their underlying structures
- Systems should follow well-defined standards for seamless communication and interoperability.
- Portability of applications should be supported, allowing applications to run on different systems.
- Systems must be expandable to adapt to evolving needs.
Policies Versus Mechanisms
- Policies: Determine the level of consistency for client-cached data, operations allowed for downloaded code, QoS adjustments for varying bandwidth, and security requirements for communication.
- Mechanisms: Implement these policies, such as allowing dynamic caching settings, offering various trust levels for mobile code, adjustable QoS parameters for data streams, and different encryption algorithms.
Strict Separation
- A strict policy-mechanism separation requires many configuration parameters, leading to complex management.
- Hardcoding policies simplifies management but reduces flexibility.
Scale in Distributed Systems
- Modern distributed systems often use "scalable" but don't always clearly explain their scalability.
- The key components for scalability include:
- The number of users and processes (size scalability)
- Network distance between nodes (geographical scalability)
- The number of administrative domains (administrative scalability)
- Current systems primarily focus on size scalability, with geographical and administrative scalability remaining a challenge.
Size Scalability
- Centralized solutions often face scalability limits due to:
- Finite CPU capacity.
- Limited storage capacity and transfer speed between CPUs and disks.
- Network limitations between the central service and users.
Formal Analysis
- A centralized service can be modeled as a queuing system.
- Assumptions for the queuing system include:
- Infinite queue capacity.
- Constant arrival rate of requests independent of the queue length.
- Processing capacity: represented by the service rate.
Formal Analysis (Continued)
- Utilization (U): The fraction of time a service is busy. U = 1 - P0
- Average number of requests (Ñ): The average number in the system = (1-U)U/μ
- Average throughput (X): The average rate at which requests are processed = U.μ +(1-U).0
Formal Analysis (Continued)
- Response time (R): Total time to process a request after submission, with S (service time) = 1/μ: R = S/(1-U)
- Observation: If U is small, response time is close to S. When U approaches 1, the system becomes heavily loaded, leading to extremely long response times. In this case, reducing the service time (S) is needed to improve scalability.
Client-Server vs. P2P: Example
- Client-server systems typically show a linear upload rate increase with the number of clients (N).
- P2P systems exhibit a slower upload rate increase for the same number of clients.
Problems with Geographical Scalability
- Synchronous client-server interactions are ineffective over wide area networks (WANs) due to high latency.
- WAN links, often unreliable, present a challenge for streaming or transferring large amounts of data.
- Lack of multipoint communication can also hinder distributed application scalability over geographically dispersed nodes.
Problems with Administrative Scalability
- Conflicting policies related to usage, management, and security can complicate the administration of distributed systems.
- Sharing large-scale resources (e.g., computational grids, shared telescopes) among different administrative domains or users requires careful management.
- Several peer-to-peer networks (e.g., file-sharing, telephony, streaming) offer alternative solutions but often rely on end-user collaboration rather than administrative control.
Techniques for Scaling
- Hiding communication latencies: Asynchronous communication and dedicated response handlers provide greater efficiency, but not applicable to all applications.
- Moving computations to clients: Reduces the workload on the server, optimizing response time for specific applications.
- Partitioning: Dividing data and computations across multiple machines to balance workload.
- Decentralized naming services (DNS): Allows efficient resource allocation and location discovery in large distributed environments.
- Replication and caching: Creating multiple copies of data and/or functionality for wider accessibility and reduced load.
Scaling: The Problem with Replication
- Replication introduces issues of maintaining consistency across multiple copies.
- Global synchronization is often necessary but prevents large-scale replication due to performance overhead and complexities.
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Description
This quiz explores the concepts of openness in distributed systems, focusing on interoperability, expandability, and the separation of policies and mechanisms. It emphasizes the importance of standards and the complexity that arises from strict policy-mechanism separation in system management.
