Exam 1

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1
connecting existing networked computer systems into a
larger system
integrative view
2
An existing network is extended with additional computers
expansive view
3
a networked computer system in which processes and resources are necessarily spread across multiple computers
decentralized system
4
a networked computer system in which processes and resources are sufficiently spread across computers
distributed system
5
centralized solutions do not scale, t or f
f
6
when a systems logic is central, as in it has the same knowledge base allthroughout. (data, business logic)
logically centralized
7
when a system has a genuinely centralized infrastructure. (servers and hardware)
physically centralized
8
what is an example of a system that is logically centralized but physically distributed?
DNS
9
Centralized solutions have a single point of failure, t or f
f
10
a single point of failure is often easier to manage and make
robust
11
The phenomenon by which a distributed system attempts to hide the fact
that its processes and resources are *physically distributed across
multiple computers*, possibly *separated by large distances*.
transparency
12
transparency is handled through ___
middleware
13
the layer between operating systems and applications that facilitates transparency
middleware
14
Hide differences in data representation and how an
object is accessed
access transparency
15
Hide that an object may be moved to another location
while in use
relocation transparency
16
Hide that an object may move to another location
migration transparency
17
Hide that an object may be shared by several
independent users
concurrency
18
you can completely hide all failures, t or f
f
19
you can be sure a computer actually performed an operation before a crash, t or f
f
20
Distribution transparency is a nice feature, but achieving it is a
different story, and it should often not even be a goal, t or f
t
21
A system that offers components that can easily be used by, or
integrated into other systems.
open distributed system
22
The average time until a component fails
mean time to failure
23
the average time needed to repair a component
mean time to repair
24
mean time to failure + mean time to repair
mean time between failures
25
a component not living up to expectations (crashed)
failure
26
a part of a component that can lead to failure (programming bug)
error
27
cause of an error (sloppy programmer)
fault
28
Prevent the occurrence of a
fault
fault prevention
29
Build a component and make
it mask the occurrence of a
fault
fault tolerance
30
Reduce the presence, number,
or seriousness of a fault
fault removal
31
Estimate current presence,
future incidence, and
consequences of faults
fault forecasting
32
A distributed system that is not secure, is not
dependable
33
information is disclosed only to authorized parties
confidentiality
34
Ensure that alterations to assets of a system can be made
only in an authorized way
integrity
35
verifying the correctness of a claimed identity
authentication
36
does an identified entity has proper access rights?
authorization
37
one entity can be assured that another will perform particular
actions according to a specific expectation
trust
38
Encryption and Decryotion key are the same and kept secret
symmetric cryptosystem
39
private key and secret key are used to send messages
asymmetric cryptosystem
40
a function that returns a fixed length string that is affected heavily by the input changes
secure hash function
41
when we use a hash function we are essentially creating a
digital signature
42
Number of users or processes
size scalability
43
Maximum distance between nodes
geographical scalability
44
Number of administrative domains
administrative scalability
45
a centralized service can be modled as a simple __
queuing system
46
parallel computing type where the processors share memory
multiprocessor
47
parallel computing type where each processor has private memory
multicomputer
48
Essentially a group of high-end systems connected through a LAN, with same OS and single tightly coupled managing nodes
cluster computing
49
Heterogeneous
Dispersed across several organizations
Can easily span a wide-area network,
plenty of nodes everywhere
grid computing
50
An example of intregrating applications, this defines "transactions" of data between applications. EX: payroll account and Employee database communicating together
EAI
51
In EAI, data in a transaction is usually distributed, so a _ is responsible for coordinating the transaction
tp monitor
52
in our middleware, we can call functions that call functions on other applications, then return their returns to our middleware.
Remote Procedure Call
53
Messages are sent to logical
contact point (published), and forwarded to subscribed applications
message oriented middleware
54
distributed systems in which nodes are
small, mobile, and often embedded in a larger system, characterized
by the fact that the system naturally blends into the user’s
environment.
pervasive systems
55
a pervasive system that is visible and autonomous and continuously interacting with the user (think a system of health monitoring sensors on a body)
ubiquitous systems
56
a pervasive system of many mobile components (location is changing constantly) think all of your apple products and accessories
mobile computing
57
a pervasive system of many sensors
sensor networks
58
contains units for interfacing to users or external
applications
Application-interface layer
59
contains the functions of an application, i.e., without specific
data
Processing layer
60
contains the data that a client wants to manipulate through the
application components
Data layer
61
Components are objects, connected to each other through procedure calls. Objects
may be placed on different machines; calls can thus execute across a network.
object based style
62
View a distributed system as a collection of resources, individually managed by components. Resources may be added,
removed, retrieved, and modified by (remote) applications
restful architectures
63
example of restful architechtures where Objects (i.e., files) are placed into buckets (i.e., directories). Buckets cannot be placed into buckets.
Operations on ObjectName in bucket BucketName require the following identifier
amazon simple storage service
64
occurs when two components must operate at the same time or in a specific sequence to function correctly
temporal coupling
65
occurs when one component needs a direct reference to another to function—like knowing its address, name, or interface.
refferential coupling
66
is where data is described by attribute value pairs
publish and subscribe
67
in publish and subscribe model what is it called when you specify where an attribute = value
topic based subscription
68
in publish and subscribe model what is it called when you specify a attribute withing a range
content based subscription
69
when we make middleware wrappers 1 to 1, it requires __ wrappers
N^2
70
when we make middleware wrappers through a broker, it requires __ wrappers
2N
71
dumb terminal/mainframe configuration
single tiered
72
client/single server configuration
two tiered
73
each layer on separate machine
three tiered
74
whats an example of client server architecture
network file system
75
A website consisted as a collection of HTML files
HTML files could be referred to each other by a hyperlink
A Web server essentially needed only a hyperlink to fetch a file
A browser took care of properly rendering the content of a file
this describes
Simple Web Servers
76
A website was built around a database with content
A Webpage could still be referred to by a hyperlink
A Web server essentially needed only a hyperlink to fetch a file
A separate program (Common Gateway Interface) composed a page
A browser took care of properly rendering the content of a file
this describes
web servers
77
Comes from dividing distributed applications into three logical layers, and running
the components from each layer on a different server (machine).
vertical distribution
78
A client or server may be physically split up into logically equivalent parts, but each
part is operating on its own share of the complete data set.
horizontal distribution
79
Processes are all equal: the functions that need to be carried out are represented
by every process
⇒
each process will act as a client and a server at the same time
(i.e., acting as a servant).
peer to peer architectures
80
each data item is uniquely associated with a key, in turn used as
an index. Common practice: use a hash function
semantic free index
81
simple example of a p2p system that stores key value pairs
hyper cube
82
another example of p2p where nodes are in a ring with a hash, there are shortcut links between nodes too
chord
83
Each node maintains a dynamic list of neighbors. The resulting overlay resembles a
random graph:
unstructured p2p
84
issuing node passes request for to all neighbors. Request is ignored
when receiving node had seen it before. Otherwise, searches locally for
(recursively). May be limited by a Time-To-Live: a maximum number of hops.
flooding
85
issuing node passes request for to randomly chosen neighbor,
. If does not have , it forwards request to one of its randomly chosen neighbors,
and so on
random walk
86
random walk is more communication efficient but takes more time to find result, t or f
t
87
we can upgrade p2p by having brokers or index servers to find data faster, this is called a
super peer network
88
whats an example of superpeer networks that allows you to trade chunks in a swarm
bittorrent
89
what is the type of computing that puts all data in a cloud (large data centers) that is managed by platforms like amazon s3 storage system, and can be interacted with by many types of applications?
cloud computing
90
systems depployed on the internet where servers are placed at the edge of the network and serve as a boundary between enterprise networks and the internet.
edge server architecture
91
these are common misconceptions: the cloud has bad bandwidth and latency, the cloud is unreliable, and that edge servers protect data, t or f
t
92
blocks are what in the blockchain
multiple validated transactions
93
the block chain is __ only
append
94
A single entity decides on which validator can go ahead and append a block. Does
not fit the design goals of blockchains
centralized consensus
95
A selected, relatively small group of servers jointly reach consensus on which validator can go
ahead.
None of these servers needs to be trusted, as long as roughly two-thirds behave according to
their specifications
permissioned consensus
96
Participants collectively engage in a leader election. Only the elected leader is allowed to append
a block of validated transactions.
Large-scale, decentralized leader election that is fair, robust, secure, and so on, is far from
trivial
permissionless consensus
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