Chapter 16: Distributed Coordination. 18.2 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Outline n Event.

Slides:



Advertisements
Similar presentations
Module 14: Network Structures
Advertisements

OSes: 16. Dist. Coord 1 Operating Systems v Objectives –introduce issues such as event ordering, mutual exclusion, atomicity, deadlock Certificate Program.
CS3771 Today: deadlock detection and election algorithms  Previous class Event ordering in distributed systems Various approaches for Mutual Exclusion.
Token-Dased DMX Algorithms n LeLann’s token ring n Suzuki-Kasami’s broadcast n Raymond’s tree.
Distributed Systems Distributed Coordination. Introduction Concurrent processes in same system –Common memory and clock –Easy to see order of events Concurrent.
Silberschatz, Galvin and Gagne ©2009 Operating System Concepts – 8 th Edition Lectures 25-26: Distributed Coordination (Ch 18)
Chapter 18: Distributed Coordination Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Chapter 18 Distributed Coordination Event Ordering.
Chapter 16: Distributed Coordination Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Chapter 16 Distributed.
Concurrency Control.
Lecture 11 Recoverability. 2 Serializability identifies schedules that maintain database consistency, assuming no transaction fails. Could also examine.
CSC 4320/6320 Operating Systems Lecture 13 Distributed Coordination
Database Systems, 8 th Edition Concurrency Control with Time Stamping Methods Assigns global unique time stamp to each transaction Produces explicit.
Silberschatz, Galvin and Gagne  Operating System Concepts Chapter 17 Distributed Coordination Event Ordering Mutual Exclusion Atomicity Concurrency.
Distributed Coordination CS 3100 Distributed Coordination1.
CS 582 / CMPE 481 Distributed Systems
What we will cover…  Distributed Coordination 1-1.
Computer Science Lecture 12, page 1 CS677: Distributed OS Last Class Distributed Snapshots –Termination detection Election algorithms –Bully –Ring.
Distributed DBMSPage © 1998 M. Tamer Özsu & Patrick Valduriez Outline Introduction Background Distributed DBMS Architecture Distributed Database.
Transaction Management and Concurrency Control
Chapter 18-1: Distributed Coordination Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Chapter 18 Distributed Coordination Chapter.
Module 2.4: Distributed Systems
Manajemen Basis Data Pertemuan 10 Matakuliah: M0264/Manajemen Basis Data Tahun: 2008.
Transaction Management
Chapter 18.2: Distributed Coordination Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Chapter 18 Distributed Coordination Chapter.
Chapter 18: Distributed Coordination (Chapter 18.1 – 18.5)
©Silberschatz, Korth and Sudarshan19.1Database System Concepts Distributed Transactions Transaction may access data at several sites. Each site has a local.
Silberschatz, Galvin and Gagne ©2009 Operating System Concepts – 8 th Edition, Chapter 7: Deadlocks.
©Silberschatz, Korth and Sudarshan16.1Database System Concepts 3 rd Edition Chapter 16: Concurrency Control Lock-Based Protocols Timestamp-Based Protocols.
18: Distributed Coordination 1 DISTRIBUTED COORDINATION Definitions: Tightly coupled systems: Same clock, usually shared memory. Communication is via this.
Modified from Silberschatz, Galvin and Gagne Principles of Computer Operating Systems Lecture 23 Chapter 16/18: Distributed Systems.
Database Systems: Design, Implementation, and Management Eighth Edition Chapter 10 Transaction Management and Concurrency Control.
Chapter 18.3: Distributed Coordination Silberschatz, Galvin and Gagne ©2005 Operating System Concepts Chapter 18 Distributed Coordination Chapter.
1 Mutual exclusion (mx) and Deadlock(dl) handling Overview of Event Ordering Mutual Exclusion Atomicity Locking protocols Time-stamping Deadlock Handling.
Distributed Deadlocks and Transaction Recovery.
Distributed Coordination 18: Distributed Coordination
DISTRIBUTED DATABASE SYSTEM.  A distributed database system consists of loosely coupled sites that share no physical component  Database systems that.
Operating Systems Distributed Coordination. Topics –Event Ordering –Mutual Exclusion –Atomicity –Concurrency Control Topics –Event Ordering –Mutual Exclusion.
Chapter 11 Concurrency Control. Lock-Based Protocols  A lock is a mechanism to control concurrent access to a data item  Data items can be locked in.
Chapter 15 Concurrency Control Yonsei University 1 st Semester, 2015 Sanghyun Park.
O/S 4740 Distributed Coordination. Event Ordering In a Centralized system, we have common memory and clock, –So we can always determine the order that.
國立台灣大學 資訊工程學系 Chapter 18: Distributed Coordination.
Silberschatz, Galvin and Gagne ©2013 Operating System Concepts – 9 th Edition Chapter 7: Deadlocks.
Transactions and Concurrency Control. Concurrent Accesses to an Object Multiple threads Atomic operations Thread communication Fairness.
7c.1 Silberschatz, Galvin and Gagne ©2003 Operating System Concepts with Java Module 7c: Atomicity Atomic Transactions Log-based Recovery Checkpoints Concurrent.
Distributed Transaction Management. Outline Introduction Concurrency Control Protocols  Locking  Timestamping Deadlock Handling Replication.
Chapter 18: Distributed Coordination Adapted to COP4610 by Robert van Engelen.
Chapter 19 Distributed Databases. 2 Distributed Database System n A distributed DBS consists of loosely coupled sites that share no physical component.
Concurrency Control Introduction Lock-Based Protocols
9 1 Chapter 9_B Concurrency Control Database Systems: Design, Implementation, and Management, Rob and Coronel.
10 1 Chapter 10_B Concurrency Control Database Systems: Design, Implementation, and Management, Rob and Coronel.
國立台灣大學 資訊工程學系 Chapter 18: Distributed Coordination.
Mutual Exclusion Algorithms. Topics r Defining mutual exclusion r A centralized approach r A distributed approach r An approach assuming an organization.
Chapter 18: Distributed Coordination Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Chapter 18 Distributed.
CS3771 Today: Distributed Coordination  Previous class: Distributed File Systems Issues: Naming Strategies: Absolute Names, Mount Points (logical connection.
CSC 8420 Advanced Operating Systems Georgia State University Yi Pan Transactions are communications with ACID property: Atomicity: all or nothing Consistency:
Silberschatz, Galvin and Gagne ©2009 Edited by Khoury, 2015 Operating System Concepts – 9 th Edition, Chapter 7: Deadlocks.
DBMS Deadlock.
Topics in Distributed Databases Database System Implementation CSE 507 Some slides adapted from Navathe et. Al and Silberchatz et. Al.
Chapter 13 Managing Transactions and Concurrency Database Principles: Fundamentals of Design, Implementation, and Management Tenth Edition.
Silberschatz and Galvin  Operating System Concepts Module 18: Distributed Coordination Event Ordering Mutual Exclusion Atomicity Concurrency.
Distributed Databases – Advanced Concepts Chapter 25 in Textbook.
Chapter 18: Distributed Coordination
Concurrency Control.
Commit Protocols CS60002: Distributed Systems
Outline Announcements Fault Tolerance.
Chapter 15 : Concurrency Control
Distributed Databases Recovery
Module 18: Distributed Coordination
Presentation transcript:

Chapter 16: Distributed Coordination

18.2 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Outline n Event Ordering n Mutual Exclusion n Atomicity n Concurrency Control n Deadlock Handling n Election Algorithms n Reaching Agreement

18.3 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Chapter Objectives n To describe various methods for achieving mutual exclusion in a distributed system n To explain how atomic transactions can be implemented in a distributed system n To show how some of the concurrency-control schemes discussed in Chapter 6 can be modified for use in a distributed environment n To present schemes for handling deadlock prevention, deadlock avoidance, and deadlock detection in a distributed system

18.4 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Event Ordering n Happened-before relation (denoted by  ) l If A and B are events in the same process, and A was executed before B, then A  B l If A is the event of sending a message by one process and B is the event of receiving that message by another process, then A  B l If A  B and B  C then A  C (transitive)

18.5 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Relative Time for Three Concurrent Processes

18.6 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Implementation of  n Associate a timestamp with each system event l For each pair of events A and B, if A  B, then the timestamp of A is less than the timestamp of B n Within each process Pi, a logical clock LCi is associated l Can be implemented as a simple counter that is incremented between any two successive events executed  Logical clock is monotonically increasing l A process advances its logical clock when it receives a message whose timestamp is greater than the current value of its logical clock n If the timestamps of two events A and B are the same, then they are concurrent l We may use the process identity numbers to break ties and to create a total ordering

18.7 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Distributed Mutual Exclusion (DME) n Assumptions l The system consists of n processes; each process P i resides at a different processor l Each process has a critical section that requires mutual exclusion n Requirement l If P i is executing in its critical section, then no other process P j is executing in its critical section n We present two algorithms to ensure the mutual exclusive execution of processes in their critical sections

18.8 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 DME: Centralized Approach n One of the processes in the system is chosen to coordinate the entry to the critical section l A process that wants to enter its critical section sends a request message to the coordinator l The coordinator decides which process can enter the critical section next, and its sends that process a reply message  When the process receives a reply message from the coordinator, it enters its critical section  After exiting its critical section, the process sends a release message to the coordinator and proceeds with its execution n This scheme requires three messages per critical- section entry: l Request, reply, release

18.9 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 DME: Fully Distributed Approach n When process P i wants to enter its critical section, it generates a new timestamp, TS, and sends the message request ( P i, TS ) to all other processes in the system l When process P j receives a request message, it may reply immediately or it may defer sending reply n When process P i receives a reply message from all other processes, it can enter its critical section n After exiting its critical section, the process sends reply messages to all its deferred requests

18.10 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 DME: Fully Distributed Approach (Cont.) n The decision whether process P j replies immediately to a request ( P i, TS ) message or defers its reply is based on three factors: l If P j is in its critical section, then it defers its reply to P i l If P j does not want to enter its critical section, then it sends a reply immediately to P i l If P j wants to enter its critical section but has not yet entered it, then it compares its own request timestamp with the timestamp TS  If its own request timestamp is greater than TS, then it sends a reply immediately to P i ( P i asked first)  Otherwise, the reply is deferred

18.11 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Desirable Behavior of Fully Distributed Approach n Freedom from deadlock is ensured n Freedom from starvation is ensured, since entry to the critical section is scheduled according to the timestamp ordering l The timestamp ordering ensures that processes are served in a first-come, first-served order The number of messages per critical-section entry: 2 x ( n – 1) l  the minimum number of required messages per critical-section entry when processes act independently and concurrently

18.12 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Three Undesirable Consequences n The processes need to know the identity of all other processes, which makes dynamic addition and removal of processes more complex n If one process fails, the entire scheme collapses l This can be dealt with by continuously monitoring the state of all processes in the system n Processes that have not entered their critical section must pause frequently to assure other processes that they intend to enter critical section l This protocol is therefore suited for small, stable sets of cooperating processes

18.13 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Token-Passing Approach n Processes logically organized in a ring structure n Circulate a token among processes l Token is special type of message l Possession of token entitles holder to enter critical section n Unidirectional ring guarantees freedom from starvation n Two types of failures Lost token – election must be called Failed processes – new logical ring established

18.14 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Atomicity n Either all operations associated with a program are fully executed, or none are performed n Ensuring atomicity in a distributed system requires a transaction coordinator, which is responsible for the following: l Starting the execution of the transaction l Breaking the transaction into a number of subtransactions, and distributing these subtransactions to the appropriate sites for execution l Coordinating the termination of the transaction, which may result in the transaction being committed at all sites or aborted at all sites

18.15 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Two-Phase Commit Protocol (2PC) n Assumes fail-stop model n The protocol is initiated by the coordinator after the last step of the transaction has been reached n The protocol involves all the local sites at which the transaction executed l When the protocol is initiated, the transaction may still be executing at some of the local sites n Example: Let T be a transaction initiated at site S i and let the transaction coordinator at S i be C i

18.16 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Phase 1: Obtaining a Decision n C i adds record to the log n C i sends message to all sites n When a site receives a message, the transaction manager determines if it can commit the transaction l If no: add record to the log and respond to C i with l If yes:  add record to the log  force all log records for T onto stable storage  send message to C i

18.17 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Phase 1 (Cont.) n Coordinator collects responses All respond “ ready ”, decision is commit At least one response is “ abort ”, decision is abort l At least one participant fails to respond within time out period, decision is abort

18.18 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Phase 2: Recording Decision in the Database n Coordinator adds a decision record or to its log and forces record onto stable storage n Once that record reaches stable storage it is irrevocable (even if failures occur) n Coordinator sends a message to each participant informing it of the decision (commit or abort) n Participants take appropriate action locally

18.19 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Failure Handling in 2PC – Site Failure n The log contains a record l In this case, the site executes redo ( T ) n The log contains an record l In this case, the site executes undo ( T ) n The log contains a record; consult C i l If C i is up, committed -> redo(T), aborted -> undo(T) l If C i is down, site sends query-status T message to the other sites n The log contains no control records concerning T l In this case, the site executes undo ( T )

18.20 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Failure Handling in 2PC – Coordinator C i Failure n If an active site contains a record in its log, the T must be committed n If an active site contains an record in its log, then T must be aborted n If some active site does not contain the record in its log then the failed coordinator C i cannot have decided to commit T l Rather than wait for C i to recover, it is preferable to abort T n All active sites have a record in their logs, but no additional control records l In this case we must wait for the coordinator to recover Blocking problem – T is blocked pending the recovery of site C i

18.21 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Concurrency Control n Modify the centralized concurrency schemes to accommodate the distribution of transactions n Transaction manager coordinates execution of transactions (or subtransactions) that access data at local sites n Local transaction only executes at that site n Global transaction executes at several sites

18.22 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Locking Protocols n Can use the two-phase locking protocol in a distributed environment by changing how the lock manager is implemented Nonreplicated scheme – each site maintains a local lock manager which administers lock and unlock requests for those data items that are stored in that site l Simple implementation involves two message transfers for handling lock requests, and one message transfer for handling unlock requests l Deadlock handling is more complex (later in Sec. 16.5)

18.23 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Single-Coordinator Approach n A single lock manager resides in a single chosen site, all lock and unlock requests are made at that site n Simple implementation n Simple deadlock handling n Possibility of bottleneck n Vulnerable to loss of concurrency controller if single site fails n Multiple-coordinator approach distributes lock- manager function over several sites

18.24 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Majority Protocol n Avoids drawbacks of central control by dealing with replicated data in a decentralized manner n More complicated to implement n Deadlock-handling algorithms must be modified; possible for deadlock to occur in locking only one data item

18.25 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Biased Protocol n Similar to majority protocol, but requests for shared locks prioritized over requests for exclusive locks n Less overhead on read operations than in majority protocol; but has additional overhead on writes n Like majority protocol, deadlock handling is complex

18.26 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Primary Copy n One of the sites at which a replica resides is designated as the primary site l Request to lock a data item is made at the primary site of that data item n Concurrency control for replicated data handled in a manner similar to that of unreplicated data n Simple implementation, but if primary site fails, the data item is unavailable, even though other sites may have a replica

18.27 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Timestamping n Generate unique timestamps in distributed scheme: l Each site generates a unique local timestamp l The global unique timestamp is obtained by concatenation of the unique local timestamp with the unique site identifier l Use a logical clock defined within each site to ensure the fair generation of timestamps Timestamp-ordering scheme – combine the centralized concurrency control timestamp scheme with the 2PC protocol to obtain a protocol that ensures serializability with no cascading rollbacks

18.28 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Generation of Unique Timestamps

18.29 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Deadlock Prevention Resource-ordering deadlock-prevention – define a global ordering among the system resources l Assign a unique number to all system resources l A process may request a resource with unique number i only if it is not holding a resource with a unique number greater than i l Simple to implement; requires little overhead Banker ’ s algorithm – designate one of the processes in the system as the process that maintains the information necessary to carry out the Banker ’ s algorithm l Also easy to implement, but may require too much overhead

18.30 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Timestamped Deadlock-Prevention Scheme n Each process P i is assigned a unique priority number n Priority numbers are used to decide whether a process P i should wait for a process P j ; otherwise P i is rolled back n The scheme prevents deadlocks l For every edge P i  P j in the wait-for graph, P i has a higher priority than P j l Thus a cycle cannot exist  There ’ s possibility of starvation l Can be avoided using timestamps

18.31 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Wait-Die Scheme n Based on a nonpreemptive technique n If P i requests a resource currently held by P j, P i is allowed to wait only if it has a smaller timestamp than does P j ( P i is older than P j ) l Otherwise, P i is rolled back ( dies ) n Example: Suppose that processes P 1, P 2, and P 3 have timestamps 5, 10, and 15 respectively l if P 1 requests a resource held by P 2, then P 1 will wait l If P 3 requests a resource held by P 2, then P 3 will be rolled back

18.32 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Wound-Wait Scheme n Based on a preemptive technique; counterpart to the wait-die system n If P i requests a resource currently held by P j, P i is allowed to wait only if it has a larger timestamp than does P j ( P i is younger than P j ). Otherwise P j is rolled back ( P j is wounded by P i ) n Example: Suppose that processes P 1, P 2, and P 3 have timestamps 5, 10, and 15 respectively l If P 1 requests a resource held by P 2, then the resource will be preempted from P 2 and P 2 will be rolled back l If P 3 requests a resource held by P 2, then P 3 will wait

18.33 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Deadlock Detection n Use wait-for graphs l Local wait-for graphs at each local site. The nodes of the graph correspond to all the processes that are currently either holding or requesting any of the resources local to that site l May also use a global wait-for graph. This graph is the union of all local wait-for graphs.

18.34 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Two Local Wait-For Graphs

18.35 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Global Wait-For Graph

18.36 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Deadlock Detection – Centralized Approach n Each site keeps a local wait-for graph n A global wait-for graph is maintained in a single coordination process n There are three different options (points in time) when the wait-for graph may be constructed: 1. Whenever a new edge is inserted or removed in one of the local wait-for graphs 2.Periodically, when a number of changes have occurred in a wait- for graph 3.Whenever the coordinator needs to invoke the cycle-detection algorithm n Unnecessary rollbacks may occur as a result of false cycles

18.37 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Detection Algorithm Based on Option 3 n Append unique identifiers (timestamps) to requests form different sites n When process P i, at site A, requests a resource from process P j, at site B, a request message with timestamp TS is sent n The edge P i  P j with the label TS is inserted in the local wait-for of A. The edge is inserted in the local wait-for graph of B only if B has received the request message and cannot immediately grant the requested resource

18.38 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 The Algorithm 1.The controller sends an initiating message to each site in the system 2.On receiving this message, a site sends its local wait- for graph to the coordinator 3.When the controller has received a reply from each site, it constructs a graph as follows: (a)The constructed graph contains a vertex for every process in the system (b) The graph has an edge Pi  Pj if and only if (1) there is an edge Pi  Pj in one of the wait-for graphs, (2) Or an edge Pi  Pj with some label TS appears in more than one wait-for graph If the constructed graph contains a cycle  deadlock

18.39 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Local and Global Wait-For Graphs

18.40 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Fully Distributed Approach n All controllers share equally the responsibility for detecting deadlock n Every site constructs a wait-for graph that represents a part of the total graph n We add one additional node P ex to each local wait- for graph n If a local wait-for graph contains a cycle that does not involve node P ex, then the system is in a deadlock state n A cycle involving P ex implies the possibility of a deadlock l To ascertain whether a deadlock does exist, a distributed deadlock-detection algorithm must be invoked

18.41 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Augmented Local Wait-For Graphs

18.42 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Augmented Local Wait-For Graph in Site S2

18.43 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Election Algorithms n Determine where a new copy of the coordinator should be restarted n Assume that a unique priority number is associated with each active process in the system, and assume that the priority number of process P i is i n Assume a one-to-one correspondence between processes and sites n The coordinator is always the process with the largest priority number. When a coordinator fails, the algorithm must elect that active process with the largest priority number n Two algorithms, the bully algorithm and a ring algorithm, can be used to elect a new coordinator in case of failures

18.44 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Bully Algorithm n Applicable to systems where every process can send a message to every other process in the system n If process P i sends a request that is not answered by the coordinator within a time interval T, assume that the coordinator has failed; P i tries to elect itself as the new coordinator n P i sends an election message to every process with a higher priority number, P i then waits for any of these processes to answer within T

18.45 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Bully Algorithm (Cont.) n If no response within T, assume that all processes with numbers greater than i have failed; P i elects itself the new coordinator n If answer is received, P i begins time interval T´, waiting to receive a message that a process with a higher priority number has been elected n If no message is sent within T´, assume the process with a higher number has failed; P i should restart the algorithm

18.46 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Bully Algorithm (Cont.) n If P i is not the coordinator, then, at any time during execution, P i may receive one of the following two messages from process P j l P j is the new coordinator ( j > i ). P i, in turn, records this information l P j started an election ( j > i ). P i, sends a response to P j and begins its own election algorithm, provided that Pi has not already initiated such an election n After a failed process recovers, it immediately begins execution of the same algorithm n If there are no active processes with higher numbers, the recovered process forces all processes with lower number to let it become the coordinator process, even if there is a currently active coordinator with a lower number

18.47 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Ring Algorithm n Applicable to systems organized as a ring (logically or physically) n Assumes that the links are unidirectional, and that processes send their messages to their right neighbors n Each process maintains an active list, consisting of all the priority numbers of all active processes in the system when the algorithm ends n If process Pi detects a coordinator failure, it creates a new active list that is initially empty. It then sends a message elect(i) to its right neighbor, and adds the number i to its active list

18.48 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Ring Algorithm (Cont.) n If P i receives a message elect( j ) from the process on the left, it must respond in one of three ways: 1. If this is the first elect message it has seen or sent, P i creates a new active list with the numbers i and j F It then sends the message elect(i), followed by the message elect(j) 2. If i  j, then the active list for P i now contains the numbers of all the active processes in the system F P i can now determine the largest number in the active list to identify the new coordinator process 3. If i = j, then P i receives the message elect(i) F The active list for P i contains all the active processes in the system F P i can now determine the new coordinator process.

18.49 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Reaching Agreement There are applications where a set of processes wish to agree on a common “ value ” n Such agreement may not take place due to: l Faulty communication medium l Faulty processes  Processes may send garbled or incorrect messages to other processes  A subset of the processes may collaborate with each other in an attempt to defeat the scheme

18.50 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Faulty Communications n Process P i at site A, has sent a message to process P j at site B ; to proceed, P i needs to know if P j has received the message n Detect failures using a time-out scheme l When P i sends out a message, it also specifies a time interval during which it is willing to wait for an acknowledgment message from P j l When P j receives the message, it immediately sends an acknowledgment to P i l If P i receives the acknowledgment message within the specified time interval, it concludes that P j has received its message  If a time-out occurs, P j needs to retransmit its message and wait for an acknowledgment l Continue until P i either receives an acknowledgment, or is notified by the system that B is down

18.51 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Faulty Communications (Cont.) n Suppose that P j also needs to know that P i has received its acknowledgment message, in order to decide on how to proceed l In the presence of failure, it is not possible to accomplish this task l It is not possible in a distributed environment for processes P i and P j to agree completely on their respective states

18.52 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Faulty Processes (Byzantine Generals Problem) n Communication medium is reliable, but processes can fail in unpredictable ways n Consider a system of n processes, of which no more than m are faulty l Suppose that each process P i has some private value of V i Devise an algorithm that allows each nonfaulty P i to construct a vector X i = ( A i, 1, A i,2, …, A i,n ) such that:: l If P j is a nonfaulty process, then A ij = V j. l If P i and P j are both nonfaulty processes, then X i = X j. n Solutions share the following properties l A correct algorithm can be devised only if n  3 x m + 1 l The worst-case delay for reaching agreement is proportionate to m + 1 message-passing delays

18.53 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts – 7 th Edition, Apr 11, 2005 Faulty Processes (Cont.) n An algorithm for the case where m = 1 and n = 4 requires two rounds of information exchange: l Each process sends its private value to the other 3 processes l Each process sends the information it has obtained in the first round to all other processes l If a faulty process refuses to send messages, a nonfaulty process can choose an arbitrary value and pretend that that value was sent by that process n After the two rounds are completed, a nonfaulty process P i can construct its vector X i = (A i,1,A i,2,A i,3,A i,4 ): l A i,j = V i l For j  i, if at least two of the three values reported for process P j agree, then the majority value is used to set the value of A ij  Otherwise, a default value ( nil ) is used

End of Chapter 16