CSC 8320 4.5 Distributed Mutual Exclusion

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CSC 83204.5 Distributed Mutual Exclusion

• Presenter Weiling Li
• Instructor Dr. Zhang

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Overview

• Part I Basic Knowledge 1,2,3
• Contention-based Mutual Exclusion
• Token-based Mutual Exclusion
• Part II Current Research
• Hybrid Distributed Mutual Exclusion4
• Use Multicast in Distributed Mutual Exclusion
  Algorithms for Grid File Systems 5
• Part III Future Research
• The Weak Mutual Exclusion problem 6
• References
• QA

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Preview three major communication scenarios

• One-way communication
• usually do not need synchronization.
• Client/Server communication
• multiple clients make service request to a
  shared server.
• Co-ordination there is no explicit
  interaction among client process.
• Intercrosses communication oftentimes
  processes need to exchange information to reach
  some conclusion about the system or some
  agreement among the cooperating processes.
• Peer communication
• there is no shared object or centralized
  controller.

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I. Distributed Mutual Exclusion 1

• Mutual exclusion ensures that concurrent
  processes make a serialized access to shared
  resources or data.
• A distributed mutual exclusion algorithm achieves
  mutual exclusion using only peer communication.
  The problem can be solved using either a
  contention-based or a token-based approach.

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Contd..

• Contention-based Mutual Exclusion
• Timestamp Prioritized Schemes
• Voting Schemes
• Token-based Mutual Exclusion
• Ring Structure
• Tree Structure
• Broadcast Structure

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Contention-based Mutual Exclusion1

• A contention-based approach means that each
  process freely and equally competes for the right
  to use shared resource by using a request
  resolution criteria.
• The fairest way is to grant the request to the
  process which asked first (Timestamp Prioritized
  scheme) or the process which got the most votes
  from the other processes (Voting scheme).

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Timestamp Prioritized Schemes

• 1) Lamport's algorithm 1
• The general mechanism is for a process Pi  to
  send a REQUEST ( with ID and time stamp ) to all
  other processes.
• When a process Pj receives such a request, it
  may reply immediately or it may defer sending a
  REPLY back.
• When responses are received from all processes,
  then Pi can enter its Critical Section.
• When Pi exits its critical section, the process
  sends RELEASE messages to all its deferred
  requests.
• The total message count is 3(N-1), where N is
  the
• number of cooperating processes.

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Contd..

• 2) Ricart and Agrawala algorithm 2
• Requesting Site
• A requesting site Pi sends a message
  request(ts,i) to all sites.
• Receiving Site
• Upon reception of a request(ts,i) message, the
  receiving site Pj will immediately send a
  timestamped reply(ts,j) message if and only if
• Pj is not requesting or executing the critical
  section OR
• Pj is requesting the critical section but sent a
  request with a higher timestamp than the
  timestamp of Pi
• Otherwise, Pj will defer the reply message.
• Improvement Number of network messages is
  2(N-1)
• Disadvantage One of the problems in this
  algorithm is failure of a node. In such a
  situation a process may starve forever. This
  problem can be solved by detecting failure of
  nodes after some timeout.

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Voting schemes 1

• Requestor 
• Send a request to all other process.
• Enter critical section once REPLY from a majority
  is received
• Broadcast RELEASE upon exit from the critical
  section.
•  
• Other processes 
• REPLY to a request if no REPLY has been sent.
  Otherwise, hold the request in a queue.
• If a REPLY has been sent, do not send another
  REPLY till the RELEASE is received.
• O(N) messages per request.
• Possibility of deadlock.

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Voting Schemes (Improved)

• One of the possible solutions would be
• Any process retrieves its REPLY message by
  sending an INQUIRY if the requestor is not
  currently executing in the critical section. The
  Requestor has to return the vote through a
  RELINQUISH message.

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Token-based Mutual Exclusion1

• Although contention-based distributed mutual
  exclusion algorithms can have attractive
  properties, their messaging overhead is high. An
  alternative to contention-based algorithms is to
  use an explicit control token, possession of
  which grants access to the critical section.
• Token-based algorithms use three typical
  topologies ring, tree, and broadcast structures.

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Ring Structure 1

• Here we have a bus network, as shown in Fig. a,
  (e.g., Ethernet), with no inherent ordering of
  the processes.
• In software, a logical ring is constructed in
  which each process is assigned a position in the
  ring, as shown in Fig. b. The ring positions may
  be allocated in numerical order of network
  addresses or some other means. It does not matter
  what the ordering is. All that matters is that
  each process knows who is next in line after
  itself.

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Contd..

• Advantages
• - simple, deadlock-free, and fair.
• - Token can also carry state information.
• Disadvantages
• -The token circulates even in the absence
   of any request (unnecessary traffic).
• -Long path (O(N)) the wait for token may
   be high.

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Tree Structure 1

• A problem with the ring structure approach is
  that the idle token is passed along the ring when
  no process is competing for it.
• Raymond's Algorithm Each process explicitly
  requests for a token and the token is moved only
  when no process if the process knows of a pending
  request.

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Tree Structure (Raymond's Algorithm)3

• The processes are organized in a logical tree
  structure, each node pointing to its parent.
  Further, each node maintains a FIFO list of token
  requesting neighbors. Each node has a variable
  Tokenholder initialized to false for everybody
  except for the first token holder (token
  generator).
• Entry Condition
• If not Tokenholder
• If the request queue empty
• request token from parent
• put itself in request queue
• block self until Tokenholder is true

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Contd..

• Exit section 
• If the request queue is not empty     
• parent dequeue(request queue)    
• send token to parent     
• set Tokenholder to false     
• if the request queue is still not empty,
  request token from parent
• Upon receipt of a request
• If Tokenholder       
• If in critical section put the requestor in the
  queue            
• parent requestor
• Tokenholder false
• send token to parent           
• else   if the queue is empty      
• send a request to the parent   
                                  
• put the requestor in queue 

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Contd..

• Upon receipt of a token 
• Parent Dequeue(request queue)                  
  
• if self is the parent 
• Tokenholder true
• else        
• send token to the parent     
• if the queue is not empty      request token
  from parent 

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Broadcast Structure 1

• Imposing a logical topology like a ring or tree
  is efficient but also complex because the
  topology has to be implemented and maintained.
• However, a token can carry global information
  that can be useful for process coordination. The
  control token for mutual exclusion is centralized
  and can be used to serialize requests to critical
  sections. (Suzuki/Kasami's broadcast algorithm).

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Broadcast structure( Suzuki/ Kasamis algorithm)

• Data Structure 
• The token contains 
• Token vector T(.) number of completions of
  the critical section for every process.   
• Request queue Q(.) queue of requesting
  processes.
• Every process (i) maintains the following     
• seq_no how many times i requested critical
  section.  
• Si(.) the highest sequence number from every
  process i heard of.

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Contd..

• Entry Section (process i) 
• Broadcast a REQUEST message stamped with seq_no.
• Enter critical section after receiving token.
• Exit Section (process i) 
• Update the token vector T by setting T(i) to
  Si(i).
• If process k is not in request queue Q and there
  are pending requests from k (Si(k)gtT(k)), append
  process k to Q.
• If Q is non-empty, remove the first entry from Q
  and send the token to the process indicated by
  the top entry.

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Contd..

• Processing a REQUEST (process j) 
• Set Sj(k) to max(Sj(k), seq_no) after receiving a
  REQUEST from process k.
• If holds an idle token, send it to k. 
• Disadvantage Requires broadcast. Therefore
  message
• overhead is high.

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II. Current Research

• 1) Hybrid Distributed Mutual Exclusion4
• Providing deadlock-free distributed mutual
  exclusion algorithms is often difficult and it
  involves passing many messages.
• A hybrid distributed mutual exclusion algorithm
  is proposed.

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Contd..(Hybrid Distributed Mutual Exclusion)

• In this algorithm, it was assumed that the
  logical structure of the interconnecting network
  is a wraparound two-dimension array. It was
  proved that the algorithm is deadlock-free. The
  number of messages passed was calculated and it
  was shown that this number is at the least one
  and at the most 4vN, which are better than many
  other algorithms.

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2) Use Multicast in Distributed Mutual Exclusion
Algorithms for Grid File Systems

• In a file system, critical sections are
  represented by means of read or write operations
  on useful data (i.e files) as well as metadata of
  the system. In a grid environment, processes are
  compared to grid nodes and their synchronization
  is ensured by the sending of messages on the
  network.
• A method based on the use of the multicast, which
  makes it possible in some cases to decrease the
  access time to critical sections. This solution
  was implemented within a token- and tree-based
  distributed mutual exclusion algorithm and it was
  integrated in the grid middleware.

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Contd..(Multicast)

• the multicast is used to seek information
  concerning the identity of the root-node by means
  of the neighboring nodes of a site, in the hope
  to reduce the length of the path to reach the
  root.

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III. Future Research Weak Mutual Exclusion6

• Weak Mutual Exclusion (WME) problem, analogously
  to classical Distributed Mutual Exclusion (DME),
  WME serializes the accesses to a shared resource.
  
• Differently from DME, however, the WME
  abstraction regulates the access to a replicated
  shared resource, whose copies are locally
  maintained by every participating process. Also,
  in WME, processes suspected to have crashed are
  possibly ejected from the critical section.
• It's proved that, unlike DME, WME is solvable in
  a partially synchronous model, i.e. a system
  where the bounds on communication latency and on
  relative process speeds are not known in advance,
  or are known but only hold after an unknown time.

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Contd..

• Benefits
• -Performance
• the ability of the WME abstraction to serialize
  the sequences of operations issued by each user
  within the critical section can also provide
  benefits for what concerns the performances of
  typical building blocks used by replication
  schemes.
• - Simplicity
• finally, the WME abstraction exposes a simple
  lock-like interface that is familiar even to
  developers with no experience with distributed
  programming.

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References

• 1 Randy Chow, Theodore Johnson, Distributed
  Operating Systems Algorithms. Addison Wesley,
  1997
• 2 http//en.wikipedia.org/wiki/Ricart-Agrawala_a
  lgorithm
• 3 Kerry Raymond, A tree-based algorithm for
  distributed mutual exclusion. ACM Transactions on
  Computer Systems (TOCS) archive
• Volume 7 , Issue 1 ,February 1989.
• 4 Paydar, S. Naghibzadeh, M. Yavari, A. A
  Hybrid Distributed Mutual Exclusion Algorithm.
  Emerging Technologies, 2006. ICET '06.
  International Conference on 13-14 Nov. 2006
  Page(s)263 - 270
• 5 Ortiz, A. Thiebolt, F. Jorda, J. M'zoughi,
  A. How to use multicast in distributed mutual
  exclusion algorithms for grid file systems. High
  Performance Computing Simulation, 2009. HPCS
  '09. International Conference on 21-24. June 2009
  Page(s)122 - 130
• 6 Romano, P. Rodrigues, L. Carvalho, N.The
  Weak Mutual Exclusion problem.
• Parallel Distributed Processing, 2009.
  IPDPS 2009. IEEE International Symposium on 23-29
  May 2009 Page(s)1 - 12

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• QA
• Thank you !