Openness and Policies in Distributed Systems

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Questions and Answers

Which feature is essential for systems in distributed environments to easily work together?

  • Centralized management
  • Well-defined interfaces (correct)
  • User-friendly interfaces
  • Proprietary protocols

Which factor does NOT contribute to the scalability challenges of centralized solutions?

  • User experience design (correct)
  • Limited CPU capacity
  • Large geographic distances
  • Network transfer rates

What is a primary concern when implementing policies in distributed systems?

  • Level of caching policies (correct)
  • User interface design
  • Cost of implementation
  • Hardware compatibility

Which type of scalability refers to the number of administrative domains involved in a distributed system?

<p>Administrative scalability (D)</p> Signup and view all the answers

What does hard coding policies typically simplify in a distributed system?

<p>Management and complexity (C)</p> Signup and view all the answers

What is a significant trade-off of strict separation between policy and mechanism?

<p>Complex management requirements (B)</p> Signup and view all the answers

Which of the following is NOT a component used to measure scalability in distributed systems?

<p>Number of redundant servers (D)</p> Signup and view all the answers

Which mechanism can help address varying Quality of Service (QoS) requirements in distributed systems?

<p>Adjustable QoS parameters (B)</p> Signup and view all the answers

What is a key benefit of using computational grids?

<p>They allow sharing of expensive resources between different domains. (B)</p> Signup and view all the answers

What technique is used to hide communication latencies in systems?

<p>Asynchronous communication (C)</p> Signup and view all the answers

What is a potential problem mentioned when using replication in data systems?

<p>Maintaining consistency across multiple copies. (A)</p> Signup and view all the answers

In the context of scaling, why might computations be moved to clients?

<p>To decrease server load and utilize client resources. (C)</p> Signup and view all the answers

Which of the following correctly describes a shared equipment scenario?

<p>Using a network to control shared radio telescopes. (B)</p> Signup and view all the answers

How can replication and caching improve system performance?

<p>By making copies of data available at different machines. (A)</p> Signup and view all the answers

Which technique is most likely not beneficial in keeping copies of data consistent after modification?

<p>Periodic data merging. (D)</p> Signup and view all the answers

Which of the following best illustrates a peer-to-peer network?

<p>Decentralized telephony services like Skype. (B)</p> Signup and view all the answers

What does the utilization U of a service indicate?

<p>The fraction of time the service is busy (A)</p> Signup and view all the answers

If the arrival rate of requests is $ ext{λ}$ and processing capacity is $ ext{μ}$, how is the response time $R$ calculated?

<p>$R = rac{N}{ ext{X}}$ (D)</p> Signup and view all the answers

What happens to the system when utilization U approaches 1?

<p>The system experiences delays in processing requests (B)</p> Signup and view all the answers

How is the average number of requests in the system $N$ expressed mathematically?

<p>$N = rac{U}{1-U}$ (B)</p> Signup and view all the answers

In a queuing system, the arrival rate and processing capacity feed into what critical measurement of performance?

<p>Throughput (B)</p> Signup and view all the answers

Which statement best describes the relationship between service time S and processing capacity μ?

<p>$S = rac{1}{μ}$ (D)</p> Signup and view all the answers

What challenge does geographical scalability present in distributed systems?

<p>Challenges in client-server interaction consistency (D)</p> Signup and view all the answers

What is a crucial solution to the scalability problems experienced in administrative systems?

<p>Developing separate naming and directory services (B)</p> Signup and view all the answers

Flashcards

Openness in Distributed Systems

The ability of different systems to interact and work together seamlessly, regardless of the underlying architecture.

Policies for Openness

Rules that determine how systems interact and behave, like setting data caching or security levels.

Mechanisms for Openness

The technical tools and methods used to implement policies, for example, dynamic caching or encryption.

Scalability in Distributed Systems

The ability of a distributed system to handle an increasing workload without performance degradation.

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Size Scalability

The ability of a system to handle an increasing number of users or processes.

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Geographical Scalability

The ability of a system to handle users and processes located at different geographical locations.

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Administrative Scalability

The ability to manage and maintain a system across different administrative domains.

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Centralized System Scalability Limitations

Centralized systems face issues handling increasing users due to CPU, storage limits, and network connection bottlenecks.

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System Utilization (U)

Fraction of time a service is busy; calculated as the arrival rate (λ) divided by the service capacity (μ).

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Average Number of Requests (N)

Average number of requests in the system at any given time; calculated as Utilization (U) / (1 - Utilization (U)).

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Average Throughput (X)

Average rate at which requests are processed; always equal to the arrival rate (λ).

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Response Time (R)

Average time taken to process a request, from submission to completion; calculated as (Average Number of Requests in System) / (Average Throughput).

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Service Time (S)

Average time required to process a single request.

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Arrival Rate (λ)

Rate at which requests arrive at the system.

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Service Capacity (μ)

Rate at which requests are processed by the server.

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Probability of k requests in the system (Pk)

The likelihood of finding exactly k requests in the system.

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Computational grids

A system where different domains share expensive resources like large-scale equipment.

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Scalability issues in replication

Maintaining consistency between multiple copies of data can be challenging.

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Asynchronous communication

A method of communication where responses aren't expected immediately.

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Client-side computation

Processing information on the user's device, reducing server load.

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Decentralized naming services

Systems where information isn't stored in a single location, e.g., DNS.

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Data and computation partitioning

Breaking down data and computation tasks across multiple computers.

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Replication & Caching

Making copies of data on multiple machines to improve response time and availability.

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Inconsistencies in replication

Mismatches in data across multiple copies of the same data when one is updated.

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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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