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Advanced Operating Systems
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Main Text:
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Project Reference Text:
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“Advanced Concepts in Operating Systems:
Distributed, Database, & Multiprocessor Operating
Systems” by Mukesh Singhal and Niranjan G.
Shivaratri. McGraw Hill publishers.
“Unix Network programming”, Richard Stevens,
Prentice Hall.
Reference Papers:
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Recommend reading appropriate reference papers
given in each chapter end.
B. Prabhakaran
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Contact Information
B. Prabhakaran
Department of Computer Science
University of Texas at Dallas
Mail Station EC 31, PO Box 830688
Richardson, TX 75083
Email: [email protected]
Fax: 972 883 2349
URL: http://www.utdallas.edu/~praba/cs6378.html
Phone: 972 883 4680
Office: ES 3.706
Office Hours: 12.15 – 2 pm, Fridays
Other times by appointments through email
Announcements: Made in class and on course web page.
TA: TBA.
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Course Outline
Proposed Outline. Might be modified
based on time availability:
 Introduction to operating systems, inter-process
communication. (Chapters 1 & 2).
 Distributed Operating Systems
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Architecture (Chapter 4)
Clock Synchronization, Ordering (Chapter 5)
Distributed Mutual Exclusion (Chapter 6)
Distributed Deadlock Detection (Chapter 7)
Agreement Protocols (Chapter 8)
Distributed Resource Management
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Distributed File Systems (Chapter 9)
Distributed Shared Memory (Chapter 10)
Distributed Scheduling (Chapter 11)
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Course Outline ...
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Recovery & Fault Tolerance
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Chapters 12 and 13
Concurrency Control/ Security
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Depending on time availability
Discussions will generally follow the main text. However,
additional/modified topics might be introduced from other
texts and/or papers. References to those materials will be
given at appropriate time.
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Evaluation
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1 Mid-term: in class. 75 minutes. Mix of MCQs (Multiple
Choice Questions) & Short Questions.
1 Final Exam: 75 minutes or 2 hours (Mix of MCQs and
Short Questions).
3 Quizzes: in class. 5-6 MCQs or very short questions.
15-20 minutes each.
Homeworks/assignments: 3 or 4 spread over the semester.
Programming Projects:
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1 preparatory (to warm up on thread and socket programming)
1 Long project with an intermediate and final submission.
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Grading
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Home works: 5%
Quizzes: 15%
Mid-term: 25%
Final: 25%
Preparatory Project: 5%
Intermediate & Final Projects (combined): 25%
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Schedule
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Quizzes: Dates announced in class & web, a week ahead.
Mostly just before midterm and final.
Mid-term: October 5, 2007
Final Exam: November 30, 2007 (As per UTD schedule)
Subject to minor changes
Quiz and homework schedules will be announced in class
and course web page, giving sufficient time for submission.
Likely project deadlines:
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Preparatory project: September 8, 2007
Intermediate project: October 14, 2007
Final Project: November 26, 2007
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Programming Projects
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No copying/sharing of code/results will be tolerated. Any instance of
cheating in projects/homeworks/exams will be reported to the
University.
No copying code from the Internet.
2 individual students copying code from Internet independently: still
considered copying in the project !!
Individual projects.
Projects might involve Unix, C/C++/Java programming, network
programming.
Deadlines will be strictly followed for projects and homeworks
submissions.
Projects submissions through Web CT.
Demo will be needed
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Two-track Course
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Programming Project Discussions:
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Announcements in class
Minimal Discussions in class
Design discussions during office hours based
on individual needs
Theory (Algorithms) Discussions:
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Full discussion in class
Office hours for clarification if needed
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Web CT
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Go to: http://webct6.utdallas.edu
Web CT has a discussion group that can be used for
project and other course discussions.
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Cheating
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Academic dishonesty will be taken seriously.
Cheating students will be handed over to
Head/Dean for further action.
Remember: home works/projects (exams too !)
are to be done individually.
Any kind of cheating in home works/ projects/
exams will be dealt with as per UTD guidelines.
Cheating in any stage of projects will result in 0
for the entire set of projects.
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Projects
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Involves exercises such as ordering, deadlock detection,
load balancing, message passing, and implementing
distributed algorithms (e.g., for scheduling, etc.).
Platform: Linux/Windows, C/C++/Java. Network
programming will be needed. Multiple systems will be
used.
Specific details and deadlines will be announced in class
and course webpage.
Suggestion: Learn network socket programming and
threads, if you do not know already. Try simple programs
for file transfer, talk, etc.
Sample programs and tutorials available at:
 http://www.utdallas.edu/~praba/projects.html
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Homeworks
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3 – 4 home works, announced in class and course web
page.
Homeworks Submission:
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Submit on paper to TA/Instructor.
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Basic Computer Organization
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Input Unit
Output Unit
CPU
Memory
ALU (Arithmetic &
Logic Unit)
Secondary Storage
Memory
ALU
Disk
CPU
I/O
Display
Keyboard
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Simplified View of OS
OS
Kernel
Physical
Memory
User i
Process j
OS Tools
User
Processes
Code
Data
Code
Code
Code
Data
User
Virtual
Memory Processes ..
Data
Data
Tools ++
Memory Space
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Distributed View of the System
hardware
hardware
hardware
Process
hardware
hardware
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Inter-Process Communication
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Need for exchanging data/messages among processes
belonging to the same or different group.
IPC Mechanisms:
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Shared Memory: Designate and use some data/memory as
shared. Use the shared memory to exchange data.
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Message Passing: Use “higher” level primitives to “send” and
“receive” data.
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Requires facilities to control access to shared data.
Requires system support for sending and receiving messages.
Operation oriented language constructs
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Request-response action
Similar to message passing with mandatory response
Can be implemented using shared memory too.
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IPC Examples
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Parallel/distributed computation such as sorting: shared
memory is more apt.
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Client-server type: message passing or RPC may suit
better.
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Using message passing/RPC might need an array/data manager
of some sort.
Shared memory may be useful, but the program is more clear
with the other types of IPCs.
RPC vs. Message Passing: if response is not a must,
atleast immediately, simple message passing should
suffice.
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Shared Memory
Writers/
Producers
Only one process
can write at any
point in time. No
access to readers.
Shared Memory
Multiple readers can
access. No access to
Writers.
Readers/
Consumers
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Shared Memory: Possibilities
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Locks (unlocks)
Semaphores
Monitors
Serializers
Path expressions
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Message Passing
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Blocked Send/Receive: Both sending and receiving
process get blocked till the message is completely
received. Synchronous.
Unblocked Send/Receive: Both sender and receiver are
not blocked. Asynchronous.
Unblocked Send/Blocked Receive: Sender is not blocked.
Receiver waits till message is received.
Blocked Send/Unblocked Receive: Useful ?
Can be implemented using shared memory. Message
passing: a language paradigm for human ease.
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Un/blocked
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Blocked message exchange
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Easy to: understand, implement, verify correctness
Less powerful, may be inefficient as sender/receiver might
waste time waiting
Unblocked message exchange
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More efficient, no waste on waiting
Needs queues, i.e., memory to store messages
Difficult to verify correctness of programs
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Message Passing: Possibilities
receiver i
sender
receiver j
receiver i
sender
receiver k
receiver j
receiver k
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Message Passing: Possibilities...
sender i
sender j
sender k
sender i
receiver
sender j
receiver
sender k
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Naming
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Direct Naming
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Port Naming
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Specify explicitly the receiver process-id.
Simple but less powerful as it needs the sender/receiver to know
the actual process-id to/from which a message is to be
sent/received.
Not suitable for generic client-server models
receiver uses a single port for getting all messages, good for
client-server.
more complex in terms of language structure, verification
Global Naming (mailbox)
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suitable for client-server, difficult to implement on a distributed
network.
complex for language structure and verification
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Communicating Sequential
Processes (CSP)
process reader-writer
OKtoread, OKtowrite: integer (initially = value);
busy: boolean (initially = 0);
*[ busy = 0; writer?request() ->
busy := 1; writer!OKtowrite;
•
busy = 0; reader?request() ->
busy := 1; reader!OKtoread;
•
busy = 1; reader?readfin() -> busy := 0;
•
busy = 1; writer?writefn() -> busy := 0;
]
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CSP: Drawbacks
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Requires explicit naming of processes in I/O commands.
No message buffering; input/output command gets
blocked (or the guards become false) -> Can introduce
delay and inefficiency.
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Operation oriented constructs
Remote Procedure Call (RPC):
Task A
Service declarations
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RPC: abc(xyz, ijk);
Task B
Service declarations
send xyz; wait for result
return ijk
…….
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Service declaration: describes in and out parameters
Can be implemented using message passing
Caller: gets blocked when RPC is invoked.
Callee implementation possibilities:
• Can loop “accepting” calls
• Can get “interrupted” on getting a call
• Can fork a process/thread for calls
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RPC: Issues
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Pointer passing, global variables passing can be difficult.
If processes on different machines, data size (number of
bits for a data type) variations need to be addressed.
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Abstract Data Types (ADTs) are generally used to take care of
these variations.
ADTs are language like structures that specify how many bits
are being used for integer, etc…
What does this imply?
Multiple processes can provide the same service? Naming
needs to be solved.
Synchronous/blocked message passing is equivalent to
RPC.
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Ada
task [type] <name> is
entry specifications
end
Task body <name> is
Declaration of local
variables
begin
list of statements
…..
accept <entry id> (<formal parameters> do
body of the accept statement
end<entry id>
exceptions
Exception handlers
end;
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task proc-buffer is
entry store(x:buffer);
remove(y:buffer);
end;
task body proc-buffer is
temp: buffer;
begin
loop
when flag accept store(x: bu
temp := x; flag :=0;
end store;
When !flag accept remove(y:
y := temp; flag :=1;
end remove;
end loop
end proc-buffer.
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Ada Message Passing
Task A
Task B
entry store(...)
….
accept Store(.)
…...
xyz is sent from
….
Task B to A
result
Store(xyz);
…..
Somewhat similar to executing procedure call. Parameter value
for the entry procedure is supplied by the calling task. Value of
Result, if any, is returned to the caller.
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RPC Design
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Structure
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Binding
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Caller: local call + stub
Callee: stub + actual procedure
Where to execute? Name/address of the server that offers a
service
Name server with inputs from service specifications of a task.
Parameter & results
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Packing: Convert to remote machine format
Unpacking: Convert to local machine format
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RPC Execution
Binding
Server
Local Proc.
Local
call
Stub
Receive
Query
Query
binding
server
Return
Server Address
Params
packing
Register
Services
Stub
Remote Proc.
Unpack
Execute
procedure
Local
call
Wait
Return
Pack
results
Unpack
result
Caller
Return
Callee
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RPC Semantics
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At least once
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Exactly once
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A RPC results in zero or more invocation.
Partial call, i.e., unsuccessful call: zero, partial, one or more
executions.
Only one call maximum
Unsuccessful? : zero, partial, or one execution
At most once
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Zero or one. No partial executions.
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RPC Implementation
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Sending/receiving parameters:
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Use reliable communication? :
Use datagrams/unreliable?
Implies the choice of semantics: how many times a RPC may be
invoked.
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RPC Disadvantage
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Incremental results communication not possible: (e.g.,)
response from a database cannot return first few matches
immediately. Got to wait till all responses are decided.
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Distributed Operating Systems
Issues :
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Global Knowledge
Naming
Scalability
Compatibility
Process Synchronization
Resource Management
Security
Structuring
Client-Server Model
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DOS: Issues ..
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Global Knowledge
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Lack of global shared memory, global clock, unpredictable
message delays
Lead to unpredictable global state, difficult to order events (A
sends to B, C sends to D: may be related)
Naming
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Need for a name service: to identify objects (files, databases),
users, services (RPCs).
Replicated directories? : Updates may be a problem.
Need for name to (IP) address resolution.
Distributed directory: algorithms for update, search, ...
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DOS: Issues ..
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Scalability
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System requirements should (ideally) increase linearly with the
number of computer systems
Includes: overheads for message exchange in algorithms used
for file system updates, directory management...
Compatibility
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Binary level: Processor instruction level compatibility
Execution level: same source code can be compiled and
executed
Protocol level: Mechanisms for exchanging messages,
information (e.g., directories) understandable.
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DOS: Issues ..
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Process Synchronization
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Resource Management
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Distributed shared memory: difficult.
Data/object management: Handling migration of files, memory
values. To achieve a transparent view of the distributed system.
Main issues: consistency, minimization of delays, ..
Security
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Authentication and authorization
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DOS: Issues ..
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Structuring
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Monolithic Kernel: Not needed (e.g.,) file management not
needed fully on diskless workstations.
Collective kernel: distributed functionality on all systems.
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Micro kernel + set of OS processes
Micro kernel: functionality for task, memory, processor
management. Runs on all systems.
OS processes: set of tools. Executed as needed.
Object-oriented system: services as objects.
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Object types: process, directory, file, …
Operations on the objects: encapsulated data can be manipulated.
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DOS: Communication
Computer
Switch
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ISO-OSI Reference Model
Application
Application
Presentation
Presentation
Session
Communication Network
Transport
Session
Transport
Network
Network
Network
Network
Datalink
Datalink
Datalink
Datalink
Physical
Physical
Physical
Physical
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Un/reliable Communication
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Reliable Communication
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Virtual circuit: one path between sender & receiver. All packets
sent through the path.
Data received in the same order as it is sent.
TCP (Transmission Control Protocol) provides reliable
communication.
Unreliable communication
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Datagrams: Different packets are sent through different paths.
Data might be lost or out of sequence.
UDP (User datagram Protocol) provides unreliable
communication.
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