This document provides a comprehensive overview of advanced operating systems, focusing on multiprocessor architectures, process synchronization, and memory management. It discusses different multiprocessing configurations, their advantages, and associated challenges, including performance issues related to process scheduling and memory access. Additionally, it covers threading models, critical section solutions, and mechanisms for ensuring concurrency and reliability in multiprocessor systems.
Introduction to CS9222 Advanced Operating System, focusing on Unit V covering structures, design issues, threads, process synchronization, memory management, and database operating systems.
Motivations for multiprocessors include enhanced performance and fault tolerance. Discusses basic architectures (SISD, SIMD, MIMD) and memory access schemes (UMA, NUMA, NORMA).
Different OS structures for multiprocessors, such as separate supervisor, master/slave configuration and symmetric configuration, detailing their strengths and weaknesses.
Design issues in SMP systems include threads, process synchronization, scheduling, memory management, and types of threads (user, kernel, LWP).
Challenges in process synchronization illustrated by the producer-consumer problem, race conditions, and critical section solutions such as Peterson’s algorithm.
Hardware support for critical section control using atomic instructions like TestAndSet and Swap to manage access to shared variables.
Processor scheduling issues including co-scheduling, cache corruption, context switching, and the importance of efficient scheduling in multiprocessor systems.An overview of the Mach OS focusing on memory management concepts, virtual memory, memory objects, and the flexibility of its memory management system.
Communication in Mach OS using ports for message passing, emphasizing unidirectional communication between processes through kernel data structures.
Sequoia system's approach to fault tolerance with fault detection and recovery methods, illustrating the architecture's high level of reliability.Overview of database operating systems focusing on transaction management, concurrency control, and algorithms such as lock-based and timestamp-based models.
Unit - V
Structures– Design Issues – Threads – Process
Synchronization – Processor Scheduling – Memory
Management – Reliability / Fault Tolerance; Database
Operating Systems – Introduction – Concurrency
Control – Distributed Database Systems –
Concurrency Control Algorithms.
3.
Motivation for Multiprocessors
EnhancedPerformance -
Concurrent execution of tasks for increased
throughput (between processes)
Exploit Concurrency in Tasks (Parallelism
within process)
Fault Tolerance -
graceful degradation in face of failures
4.
Basic MP Architectures
SingleInstruction Single Data (SISD) -
conventional uniprocessor designs.
Single Instruction Multiple Data (SIMD) -
Vector and Array Processors
Multiple Instruction Single Data (MISD) -
Not Implemented.
Multiple Instruction Multiple Data (MIMD)
- conventional MP designs
5.
MIMD Classifications
Tightly CoupledSystem - all processors
share the same global memory and have
the same address spaces (Typical SMP
system).
Main memory for IPC and Synchronization.
Loosely Coupled System - memory is
partitioned and attached to each processor.
Hypercube, Clusters (Multi-Computer).
Message passing for IPC and synchronization.
6.
MP Block Diagram
cacheMMU
CPU
cache MMU
CPU
cache MMU
CPU
cache MMU
CPU
MM MM MM MM
Interconnection Network
7.
Memory Access Schemes
•Uniform Memory Access (UMA)
– Centrally located
– All processors are equidistant (access times)
• NonUniform Access (NUMA)
– physically partitioned but accessible by all
– processors have the same address space
• NO Remote Memory Access (NORMA)
– physically partitioned, not accessible by all
– processors have own address space
MP OS Structure- 1
Separate Supervisor -
all processors have their own copy of the kernel.
Some share data for interaction
dedicated I/O devices and file systems
good fault tolerance
bad for concurrency
10.
• Master/Slave Configuration
–master monitors the status and assigns work to
other processors (slaves)
– Slaves are a schedulable pool of resources for
the master
– master can be bottleneck
– poor fault tolerance
MP OS Structure - 2
11.
Symmetric Configuration -Most Flexible.
all processors are autonomous, treated equal
one copy of the kernel executed concurrently
across all processors
Synchronize access to shared data structures:
Lock entire OS - Floating Master
Mitigated by dividing OS into segments that normally
have little interaction
multithread kernel and control access to resources
(continuum)
MP OS Structure - 3
SMP OS DesignIssues
Threads - effectiveness of parallelism depends
on performance of primitives used to express
and control concurrency.
Process Synchronization - disabling interrupts
is not sufficient.
Process Scheduling - efficient, policy controlled,
task scheduling (process/threads)
global versus per CPU scheduling
Task affinity for a particular CPU
resource accounting and intra-task thread
dependencies
14.
Memory Management -complicated since
main memory is shared by possibly many
processors. Each processor must maintain its
own map tables for each process
cache coherence
memory access synchronization
balancing overhead with increased concurrency
Reliability and fault Tolerance - degrade
gracefully in the event of failures
SMP OS design issues - 2
15.
Typical SMP System
cacheMMU
CPU
cache MMU
CPU
cache MMU
CPU
cache MMU
CPU
I/O
subsystem
Issues:
• Memory contention
• Limited bus BW
• I/O contention
• Cache coherence
Main
Memory
50ns
Typical I/O Bus:
• 33MHz/32bit (132MB/s)
• 66MHz/64bit (528MB/s)
500MHz
System/Memory Bus
ether
scsi
video
Bridge
System Functions
(timer, BIOS, reset)
INT
16.
Some Definitions
Parallelism: degreeto which a multiprocessor
application achieves parallel execution
Concurrency: Maximum parallelism an
application can achieve with unlimited
processors
System Concurrency: kernel recognizes multiple
threads of control in a program
User Concurrency: User space threads
(coroutines) provide a natural programming
model for concurrent applications. Concurrency
not supported by system.
17.
Process and Threads
Process:encompasses
set of threads (computational entities)
collection of resources
Thread: Dynamic object representing an
execution path and computational state.
threads have their own computational state: PC,
stack, user registers and private data
Remaining resources are shared amongst threads
in a process
18.
Threads
Effectiveness of parallelcomputing depends on
the performance of the primitives used to
express and control parallelism
Threads separate the notion of execution from
the Process abstraction
Useful for expressing the intrinsic concurrency
of a program regardless of resulting
performance
Three types: User threads, kernel threads and
Light Weight Processes (LWP)
19.
User Level Threads
Userlevel threads - supported by user level
(thread) library
Benefits:
no modifications required to kernel
flexible and low cost
Drawbacks:
can not block without blocking entire process
no parallelism (not recognized by kernel)
20.
Kernel Level Threads
Kernellevel threads - kernel directly supports
multiple threads of control in a process. Thread
is the basic scheduling entity
Benefits:
coordination between scheduling and
synchronization
less overhead than a process
suitable for parallel application
Drawbacks:
more expensive than user-level threads
generality leads to greater overhead
21.
Light Weight Processes(LWP)
Kernel supported user thread
Each LWP is bound to one kernel thread.
a kernel thread may not be bound to an LWP
LWP is scheduled by kernel
User threads scheduled by library onto LWPs
Multiple LWPs per process
22.
Thread operations inuser space:
create, destroy, synch, context switch
kernel threads implement a virtual processor
Course grain in kernel - preemptive scheduling
Communication between kernel and threads library
shared data structures.
Software interrupts (user upcalls or signals). Example, for
scheduling decisions and preemption warnings.
Kernel scheduler interface - allows dissimilar thread
packages to coordinate.
First Class threads (Psyche OS)
23.
Scheduler Activations
An activation:
servesas execution context for running thread
notifies thread of kernel events (upcall)
space for kernel to save processor context of current
user thread when stopped by kernel
kernel is responsible for processor allocation =>
preemption by kernel.
Thread package responsible for scheduling
threads on available processors (activations)
24.
Support for Threading
•BSD:
– process model only. 4.4 BSD enhancements.
• Solaris:provides
– user threads, kernel threads and LWPs
• Mach: supports
– kernel threads and tasks. Thread libraries provide
semantics of user threads, LWPs and kernel threads.
• Digital UNIX: extends MACH to provide usual
UNIX semantics.
– Pthreads library.
25.
Process Synchronization:Motivation
Sequential executionruns correctly but
concurrent execution (of the same program)
runs incorrectly.
Concurrent access to shared data may result in
data inconsistency
Maintaining data consistency requires
mechanisms to ensure the orderly execution of
cooperating processes
Let’s look at an example: consumer-producer
problem.
26.
Producer-Consumer Problem
Producer
while (true){
/* produce an item and put in
nextProduced */
while (count == BUFFER_SIZE); // do
nothing
buffer [in] = nextProduced;
in = (in + 1) % BUFFER_SIZE;
count++;
}
count: the number of items in the
buffer (initialized to 0)
Consumer
while (true) {
while (count == 0); // do nothing
nextConsumed = buffer[out];
out = (out + 1) % BUFFER_SIZE;
count--;
// consume the item in nextConsumed
}
What can go wrong in concurrent
execution?
27.
Race Condition
count++could be implemented as
register1 = count
register1 = register1 + 1
count = register1
count-- could be implemented as
register2 = count
register2 = register2 - 1
count = register2
Consider this execution interleaving with “count = 5” initially:
S0: producer execute register1 = count {register1 = 5}
S1: producer execute register1 = register1 + 1 {register1 = 6}
S2: consumer execute register2 = count {register2 = 5}
S3: consumer execute register2 = register2 - 1 {register2 = 4}
S4: producer execute count = register1 {count = 6 }
S5: consumer execute count = register2 {count = 4}
What are all possible values from concurrent execution?
28.
How to preventrace condition?
Define a critical section in
each process
Reading and writing
common variables.
Make sure that only one
process can execute in the
critical section at a time.
What sync code to put into
the entry & exit sections to
prevent race condition?
do {
entry section
critical section
exit section
remainder section
} while (TRUE);
29.
Solution to Critical-Section
Problem
1.Mutual Exclusion - If process Pi is executing in its critical section, then no
other processes can be executing in their critical sections
2. Progress - If no process is executing in its critical section and there exist
some processes that wish to enter their critical section, then the
selection of the processes that will enter the critical section next cannot
be postponed indefinitely
3. Bounded Waiting - A bound must exist on the number of times that
other processes are allowed to enter their critical sections after a process
has made a request to enter its critical section and before that request is
granted
What is the difference between
Progress and Bounded Waiting?
30.
Peterson’s Solution
Simple 2-processsolution
Assume that the LOAD and STORE instructions are
atomic; that is, cannot be interrupted.
The two processes share two variables:
int turn;
Boolean flag[2]
The variable turn indicates whose turn it is to enter
the critical section.
The flag array is used to indicate if a process is ready
to enter the critical section. flag[i] = true implies that
process Pi is ready!
31.
Algorithm for ProcessPi
while (true) {
flag[i] = TRUE;
turn = j;
while ( flag[j] && turn == j);
CRITICAL SECTION
flag[i] = FALSE;
REMAINDER SECTION
}
Mutual exclusion
Only one process enters critical section
at a time.
Proof: can both processes pass the while
loop (and enter critical section) at the
same time?
Progress
Selection for waiting-to-enter-critical-
section process does not block.
Proof: can Pi wait at the while loop
forever (after Pj leaves critical section)?
Bounded Waiting
Limited time in waiting for other
processes.
Proof: can Pj win the critical section
twice while Pi waits?
Entry Section
Exit Section
Synchronization Hardware
Manysystems provide hardware support for critical section code
Uniprocessors – could disable interrupts
Currently running code would execute without preemption
Generally too inefficient on multiprocessor systems
Operating systems using this not broadly scalable
Modern machines provide special atomic hardware instructions
Atomic = non-interruptable
TestAndSet(target): Either test memory word and set value
Swap(a,b): Or swap contents of two memory words
Solution using TestAndSet
Shared boolean variable lock, initialized to false.
Solution:
while (true) {
while ( TestAndSet (&lock ))
; /* do nothing
// critical section
lock = FALSE;
// remainder section
}
Does it satisfy mutual exclusion?
How about progress and bounded waiting?
How to fix this?
Entry Section
Exit Section
36.
Bounded-Waiting TestAndSet
• Sharedvariable
boolean waiting[n];
boolean lock; // initialized false.
• Solution:
do {
waiting[i] = TRUE;
while (waiting[i] &&
TestAndSet(&lock);
waiting[i] = FALSE;
// critical section
j=(i+1)%n;
while ((j!=i) && !waiting[j])
j=(j+1)%n;
If (j==i) lock = FALSE;
else waiting[j] = FALSE;
// reminder section
} while (TRUE);
Mutual exclusion
Proof: can two processes pass the
while loop (and enter critical section)
at the same time?
Bounded Waiting
Limited time in waiting for other
processes.
What is waiting[] for? When does
waiting[i] set to FALSE?
Proof: how long does Pi’s wait till
waiting[i] becomes FALSE?
Progress
Proof: exit section unblocks at least
one process’s waiting[] or set the lock
to FALSE.
Entry Section
Exit Section
Solution using Swap
Shared Boolean variable lock initialized to FALSE; Each process
has a local Boolean variable key.
Solution:
while (true) {
key = TRUE;
while ( key == TRUE)
Swap (&lock, &key );
// critical section
lock = FALSE;
// remainder section
}
Mutual exclusion? Progress and Bounded Waiting?
Notice a performance problem with Swap & TestAndSet
solutions?
Entry Section
Exit Section
39.
Processor Scheduling
PS: readytasks are assigned to the processors so
that performance is maximized.
Cooperate and communicate through shared
variables or message passing, PS in multiprocessor
system is difficult problem.
PS is very critical to the performance of
multiprocessor systems because a naïve scheduler
can degrade performance substantially.
40.
Issues in ProcessorScheduling
3 major causes of performance degradation are
Preemption inside spinlock-controlled critical sections.
This situation occurs when a task is preempted inside CS when there are
other tasks spinning the lock to enter the same CS.
cache corruption
Big chunk of data needed by the previous tasks must be purged from the
cache and new data must be brought into the cache.
Very high miss ratio a processor switched to another task – Cache corrp.
context switching overheads
Execution of a large no. of instructions to save and store the registers, to
initialize the registers, to switch address space, etc.
41.
Co-Scheduling of theMedusa OS
Co-scheduling –proposed by ousterhout for MOS
for cm*
All runnable tasks of an application are scheduled
on the processor simultaneously.
Context switching between appl. Rather than bet.
Tasks of several different applications.
Pbm: tasks wasting resources in lock-spinning
while they wait for a preempted task to release
the critical section.
42.
Smart Scheduling
Proposed byzahorjan et al. – 2 nice features
It avoids preempting a task when the task is inside its
CS
It avoids the rescheduling of tasks that were busy
waiting at the time of their preemption until the task
that is executing the corresponding CS release it.
Eliminates the resource waste due to a processor
spinning a lock.
To reduce the overhead due to context switching
nor to reduce the performance degradation due to
cache corruption.
43.
Scheduling in theNYU Ultracomputer
Edler et al. and it cobines the the strategies of the
previous 2 scheduling techniques.
Tasks can be formed into groups and scheduled in
any of the following ways:
task – scheduled or preempted in the normal manner
All task in group are sched. Or preempted
simultaneously.
Tasks in group are never preempted.
44.
Memory Management
The MachOperating System
Virtual MM of mach OS developed at cm*
Design Issues
Portability
Data sharing
Protection
Efficiency
The Mach Kernel
Basic primitives necessary for building parallel and
distributed applications.
45.
The Mach Kernel
4.3BSD
emulator
System V
emulator HP/UX
emulator Other
emulator
Microkernel
User process
User space
Kernel space
Software
emulator
layer
46.
The kernel managesfive principal
abstractions:
1. Processes.
2. Threads.
3. Memory objects.
4. Ports.
5. Messages.
47.
Process Management inMach
Process
port
Bootstrap
port
Exception
port
Registered
ports
kernel
process
Thread
Address space
48.
Ports
The process portis used to communicate with the
kernel.
The bootstrap port is used for initialization when a
process starts up.
The exception port is used to report exceptions
caused by the process. Typical exceptions are division
by zero and illegal instruction executed.
The registered ports are normally used to provide a
way for the process to communicate with standard
system servers.
49.
Ports
A process canbe runnable or blocked.
If a process is runnable, those threads that are
also runnable can be scheduled and run.
If a process is blocked, its threads may not
run, no matter what state they are in.
50.
Process Management Primitives
CreateCreate a new process, inheriting certain properties
Terminate Kill a specified process
Suspend Increment suspend counter
Resume Decrement suspend counter. If it is 0, unblock the process
Priority Set the priority for current or future threads
Assign Tell which processor new threads should run on
Info Return information about execution time, memory usage, etc.
Threads Return a list of the process’ threads
51.
Threads
Mach threadsare managed by the kernel. Thread creation and destruction are
done by the kernel.
Fork Create a new thread running the same code as the
parent thread
Exit Terminate the calling thread
Join Suspend the caller until a specified thread exits
Detach Announce that the thread will never be jointed (waited
for)
Yield Give up the CPU voluntarily
Self Return the calling thread’s identity to it
52.
Scheduling algorithm
When athread blocks, exits, or uses up its quantum,
the CPU it is running on first looks on its local run
queue to see if there are any active threads.
If it is nonzero, run the highest-priority thread,
starting at the queue specified by the hint.
If the local run queue is empty, the same algorithm is
applied to the global run queue. The global queue
must be locked first.
53.
Scheduling
Global run queuefor processor set 1 Global run queue for processor set 2
Priority
(high) 0
Low 31
0
31
:Free
Count: 6
Hint: 2
:Busy
Count: 7
Hint: 4
54.
Memory Management inMach
Mach has a powerful, elaborate, and highly flexible memory
management system based on paging.
The code of Mach’s memory management is split into three
parts. The first part is the pmap module, which runs in the
kernel and is concerned with managing the MMU.
The second part, the machine-independent kernel code, is
concerned with processing page faults, managing address
maps, and replacing pages.
The third part of the memory management code runs as a
user process called a memory manager. It handles the logical
part of the memory management system, primarily
management of the backing store (disk).
55.
Virtual Memory
The conceptualmodel of memory that Mach user
processes see is a large, linear virtual address space.
The address space is supported by paging.
A key concept relating to the use of virtual address
space is the memory object. A memory object can be
a page or a set of pages, but it can also be a file or
other, more specialized data structure.
56.
An address spacewith allocated regions,
mapped objects, and unused addresses
File xyz region
Stack region
Data region
Text region
Unused
Unused
Unused
57.
System calls forvirtual address
space manipulation
Allocate Make a region of virtual address space usable
Deallocate Invalidate a region of virtual address space
Map Map a memory object into the virtual address space
Copy Make a copy of a region at another virtual address
Inherit Set the inheritance attribute for a region
Read Read data from another process’ virtual address
space
Write Write data to another process’ virtual address space
Advantages of Copy-on-write
1.some pages are read-only, so there is no
need to copy them.
2. other pages may never be referenced, so
they do not have to be copied.
3. still other pages may be writable, but the
child may deallocate them rather than using
them.
62.
Disadvantages of Copy-on-write
1.the administration is more complicated.
2. requires multiple kernel traps, one for each
page that is ultimately written.
3. does not work over a network.
63.
External Memory Managers
Each memory object that is mapped in a process’ address
space must have an external memory manager that controls
it. Different classes of memory objects are handled by
different memory managers.
Three ports are needed to do the job.
The object port, is created by the memory manager and will
later be used by the kernel to inform the memory manager
about page faults and other events relating to the object.
The control port, is created by the kernel itself so that the
memory manager can respond to these events.
The name port, is used as a kind of name to identify the
object.
64.
Distributed Shared Memoryin Mach
The idea is to have a single, linear, virtual
address space that is shared among processes
running on computers that do not have any
physical shared memory. When a thread
references a page that it does not have, it
causes a page fault. Eventually, the page is
located and shipped to the faulting machine,
where it is installed so that the thread can
continue executing.
65.
Communication in Mach
The basis of all communication in Mach is a kernel data
structure called a port.
When a thread in one process wants to communicate with a
thread in another process, the sending thread writes the
message to the port and the receiving thread takes it out.
Each port is protected to ensure that only authorized
processes can send it and receive from it.
Ports support unidirectional communication. A port that can
be used to send a request from a client to a server cannot also
be used to send the reply back from the server to the client. A
second port is needed for the reply.
66.
A Mach port
Messagequeue
Current message count
Maximum messages
Port set this port belongs to
Counts of outstanding capabilities
Capabilities to use for error reporting
Queue of threads blocked on this port
Pointer to the process holding the RECEIVE capability
Index of this port in the receiver’s capability list
Pointer to the kernel object
Miscellaneous items
67.
Message passing viaa port
port
Sending
thread
Receiving thread
Kernel
send receive
Primitives for ManagingPorts
Allocate Create a port and insert its capability in the capability list
Destroy Destroy a port and remove its capability from the list
Deallocate Remove a capability from the capability list
Extract_right Extract the n-th capability from another process
Insert_right Insert a capability in another process’ capability list
Move_member Move a capability into a capability set
Set_qlimit Set the number of messages a port can hold
70.
Sending and ReceivingMessages
Mach_msg(&hdr, options, send_size, rcv_size, rcv_port, timeout, notify_port);
The first parameter, hdr, is a pointer to the message to be sent or to the place
where the incoming message is put, or both.
The second parameter, options, contains a bit specifying that a message is to be
sent, and another one specifying that a message is to be received. Another bit
enables a timeout, given by the timeout parameter. Other bits in options allow a
SEND that cannot complete immediately to return control anyway, with a status
report being sent to notify_port later.
The send_size and rcv_size parameters tell how large the outgoing message is and
how many bytes are available for storing the incoming message, respectively.
Rcv_port is used for receiving messages. It is the capability name of the port or
port set being listened to.
71.
The Mach messageformat
Message size
Capability index for destination port
Capability index for reply port
Message kind
Function code
Descriptor 1
Data field 1
Descriptor 2
Data field 2
Reply rights Dest. rightsComplex/Simple
Header
Message
body
Not examined
by the
kernel
72.
Complex message fielddescriptor
Data field size
In bits
Data field typeNumber of
in the data field
Bits1 1 1 1 12 8 8
Bit
Byte
Unstructured word
Integer(8,16,32 bits)
Character
32 Booleans
Floating point
String
Capability
0: Out-of-line data present
1: No out-of-line data
0: Short form descriptor
1: Long form descriptor
0: Sender keeps out-of-line data
1: Deallocate out-of-line data from sender
73.
Reliability/Fault Tolerance: the
SEQUOIASystem
Sequoia system – a loosely coupled
multiprocessor system.
Attains a high level of fault tolerance by
performing fault detection in hardware and
fault recovery in the OS.
Design Issues
Fault detection and isolation
Fault recovery
Efficiency
The sequoia Architecture
Reliability/Fault Tolerance: the
SEQUOIASystem
Fault detection
Error detecting codes
Comparison of duplicated operations
Protocol monitoring
Fault Recovery
Recovery from processor failures
Recovery from main memory failures
Recovery from I/O failures
76.
Database Operating Systems
Database system have
been implemented as
an application on top
of general purpose OS
Requrements of DBOS
Transaction
Management
Support for complex,
persistent data
Buffer Management
77.
Concurrency Control
CCis the process of controlling concurrent access to a database to
ensure that the correctness of the database is maintained.
Database systems
Set of shared data objects that can be accessed by users.
Transactions
A transaction consists of a sequence of R, compute & W s/m
that refer to the data objects of a database.
Conflicts
Transactions conflicts if they access the same data objects.
Transaction processing
A transaction is executed by executing its actions one by one
from the beginning to the end.
78.
A concurrency controlmodel of DBS
3 software modules
Transaction manager (TM)
Supervises the execution of a transaction
Data manager (DM)
Responsible for enforcing concurrency control
Scheduler
79.
Distributed Database System
A distributed database is a database in which storage devices
are not all attached to a common processing unit such as the
CPU.
It may be stored in multiple computers, located in the same
physical location; or may be dispersed over a network of
interconnected computers.
Unlike parallel systems, in which the processors are tightly
coupled and constitute a single database system, a distributed
database system consists of loosely coupled sites that share
no physical components.
Distributed Database System
Motivations: DDBS offers several advantages over a centralized
database system such as
Sharing
Higher system availability (reliability)
Improved performance
Easy expandability
Large databases
Transaction Processing Model
Serializability condition in DDBS
Data replication
Complications due to Data replication
Fully Replicated Database Systems
1. Enhanced reliability 2. Improved responsiveness 3. No directory
management 4. Easier load balancing
82.
Concurrency Control Algorithms
Itcontrols the interleaving of conflicting actions of
transactions so that the integrity of a database is
maintained, i.e., their net effect is a serial execution.
Basic synchronization primitives
Locks
A transaction can request, hold or release the lock on a data
object.
lock a data object in 2 modes: exclusive and shared
Timestamps
Unique number is assigned to a transaction or a data object and is
chosen from a monotonically increasing sequence.
Commonly generated using Lamport’s scheme
83.
Lock based algorithms
Staticlocking
Two Phase Locking (2PL)
Problems with 2PL: Price for Higher concurrency
2PL in DDBS
Timestamp Based locking
Conflict Resolution
Wait Restart Die Wound
Non-two-phase locking