Distributed Systems Intro EXAM Questions and Accurate Answers 2024/2025 | verified
What are the most common problems in distributed systems? - - Time
What are characteristics of distributed systems? - - Multiple processes: The system consists of
more than one sequential process. These processes can be either system or user processes, but each
process should have an independent thread of control—either explicit or implicit.
- Interprocess communication: Processes communicate with one another using messages that take a
finite time to travel from one process to another. The actual nature or order of the delay will depend on
the physical characteristics of the message links. These message links are also called channels.
- Disjoint address spaces: Processes have disjoint address spaces. We will thus not take into account a
shared-memory multiprocessor as a true representation of a distributed computing system. Note that
programmers often represent interprocess communication using shared-memory primitives, but the
abstraction of shared memory can be implemented using messages.
- Collective goal: Processes must interact with one another to meet a common goal. Consider two
processes P and Q in a network of processes. If P computes f(x) = x^2 for a given set of values of x, and Q
multiplies a set of numbers by π, then we hesitate to call (P, Q) a distributed system, since there is no
interaction between P and Q. However, if P and Q cooperate with one another to compute the areas of a
set of circles of radius x, then (P, Q) collectively represent a meaningful distributed system. Similarly, if a
set of sellers advertise the cost of their products, and a set of buyers post the list of the goods that they
are interested in buying as well as the prices they are willing to pay, then individually, neither the buyers
nor the sellers are meaningful distributed systems, but when they are coupled into an auction system
through the Internet, then it becomes a meaningful distributed system.
What is the reason for growing of the importance of distributed systems? - - Geographically
distributed environment: First, in many situations, the computing environment itself is geographically
distributed. As an example, consider a banking network. Each bank is supposed to maintain the accounts
of its customers. In addition, banks communicate with one another to monitor interbank transactions or
record fund transfers from geographically dispersed automated teller machines (ATMs). Another
common example of a geographically distributed computing environment is the Internet, which has
deeply influenced our way of life. The mobility of the users has added a new dimension to the
geographic distribution.
- Speed up: Second, there is the need for speeding up computation. The speed of computation in
traditional uniprocessors is fast approaching the physical limit. While multicore, superscalar, and very
, large instruction word (VLIW) processors stretch the limit by introducing parallelism at the architectural
level, the techniques do not scale well beyond a certain level. An alternative technique of deriving more
computational power is to use multiple processors. Dividing a total problem into smaller subproblems
and assigning these subproblems to separate physical processors that can operate concurrently are
potentially an attractive method of enhancing the speed of computation. Moreover, this approach
promotes better scalability, where the users or administrators can incrementally increase the
computational power by purchasing additional processing elements or resources. This concept is
extensively used by the social networking sites for the concurrent upload and download of the photos
and videos of millions of customers.
- Resource sharing: Third, there is a need for resource sharing. Here, the term resource represents both
hardware and software resources. The user of computer A may want to use a
What are some of the important issues in the study of the computational models of distributed systems?
- - Knowledge of a process: The knowledge of a process is local. No process is ordinarily expected
to have global knowledge about either the network topology or the global state. Each process thus has a
myopic view of the system. It is fair to expect that a process knows (1) its own identity, (2) its own state,
and (3) the identity of its immediate neighbors. In some special cases, a process may also have exact or
approximate knowledge about the size (i.e., the number of nodes) of the network. Any other knowledge
that a process might need has to be acquired from time to time through appropriate algorithmic actions.
- Network topology: A network of processes may either be completely connected or sparsely connected.
In a completely connected network, a channel (also called a link) exists between every pair of processes
in the system. This condition does not hold for a sparsely connected topology. As a result, message
routing is an important activity. A link between a pair of processes may be unidirectional or bidirectional.
Examples of sparse topologies are trees, rings, arrays, and hypercubes.
- Degree of synchronization: Some of the deeper issues in distributed systems center around the notion
of synchrony and asynchrony.
Assume that each process in a distributed system has a local clock. If these clocks represent the UTC
(static differences due to time zones can be easily taken care of and ignored from this equation), then
every process has a common notion of time, and the system can exhibit synchronous behavior by the
simultaneous scheduling of their actions. Unfortunately, in practical distributed systems, this is difficult
to achieve, since the drift of the local physical clocks is a fact of life. One approach to handle this is to use
a time server that keeps all the local clocks synchronized with one another. Thi
What are the most common problems in distributed systems? - - Time
What are characteristics of distributed systems? - - Multiple processes: The system consists of
more than one sequential process. These processes can be either system or user processes, but each
process should have an independent thread of control—either explicit or implicit.
- Interprocess communication: Processes communicate with one another using messages that take a
finite time to travel from one process to another. The actual nature or order of the delay will depend on
the physical characteristics of the message links. These message links are also called channels.
- Disjoint address spaces: Processes have disjoint address spaces. We will thus not take into account a
shared-memory multiprocessor as a true representation of a distributed computing system. Note that
programmers often represent interprocess communication using shared-memory primitives, but the
abstraction of shared memory can be implemented using messages.
- Collective goal: Processes must interact with one another to meet a common goal. Consider two
processes P and Q in a network of processes. If P computes f(x) = x^2 for a given set of values of x, and Q
multiplies a set of numbers by π, then we hesitate to call (P, Q) a distributed system, since there is no
interaction between P and Q. However, if P and Q cooperate with one another to compute the areas of a
set of circles of radius x, then (P, Q) collectively represent a meaningful distributed system. Similarly, if a
set of sellers advertise the cost of their products, and a set of buyers post the list of the goods that they
are interested in buying as well as the prices they are willing to pay, then individually, neither the buyers
nor the sellers are meaningful distributed systems, but when they are coupled into an auction system
through the Internet, then it becomes a meaningful distributed system.
What is the reason for growing of the importance of distributed systems? - - Geographically
distributed environment: First, in many situations, the computing environment itself is geographically
distributed. As an example, consider a banking network. Each bank is supposed to maintain the accounts
of its customers. In addition, banks communicate with one another to monitor interbank transactions or
record fund transfers from geographically dispersed automated teller machines (ATMs). Another
common example of a geographically distributed computing environment is the Internet, which has
deeply influenced our way of life. The mobility of the users has added a new dimension to the
geographic distribution.
- Speed up: Second, there is the need for speeding up computation. The speed of computation in
traditional uniprocessors is fast approaching the physical limit. While multicore, superscalar, and very
, large instruction word (VLIW) processors stretch the limit by introducing parallelism at the architectural
level, the techniques do not scale well beyond a certain level. An alternative technique of deriving more
computational power is to use multiple processors. Dividing a total problem into smaller subproblems
and assigning these subproblems to separate physical processors that can operate concurrently are
potentially an attractive method of enhancing the speed of computation. Moreover, this approach
promotes better scalability, where the users or administrators can incrementally increase the
computational power by purchasing additional processing elements or resources. This concept is
extensively used by the social networking sites for the concurrent upload and download of the photos
and videos of millions of customers.
- Resource sharing: Third, there is a need for resource sharing. Here, the term resource represents both
hardware and software resources. The user of computer A may want to use a
What are some of the important issues in the study of the computational models of distributed systems?
- - Knowledge of a process: The knowledge of a process is local. No process is ordinarily expected
to have global knowledge about either the network topology or the global state. Each process thus has a
myopic view of the system. It is fair to expect that a process knows (1) its own identity, (2) its own state,
and (3) the identity of its immediate neighbors. In some special cases, a process may also have exact or
approximate knowledge about the size (i.e., the number of nodes) of the network. Any other knowledge
that a process might need has to be acquired from time to time through appropriate algorithmic actions.
- Network topology: A network of processes may either be completely connected or sparsely connected.
In a completely connected network, a channel (also called a link) exists between every pair of processes
in the system. This condition does not hold for a sparsely connected topology. As a result, message
routing is an important activity. A link between a pair of processes may be unidirectional or bidirectional.
Examples of sparse topologies are trees, rings, arrays, and hypercubes.
- Degree of synchronization: Some of the deeper issues in distributed systems center around the notion
of synchrony and asynchrony.
Assume that each process in a distributed system has a local clock. If these clocks represent the UTC
(static differences due to time zones can be easily taken care of and ignored from this equation), then
every process has a common notion of time, and the system can exhibit synchronous behavior by the
simultaneous scheduling of their actions. Unfortunately, in practical distributed systems, this is difficult
to achieve, since the drift of the local physical clocks is a fact of life. One approach to handle this is to use
a time server that keeps all the local clocks synchronized with one another. Thi
