SYNCHRONIZATION. DISTRIBUTED SYSTEMS Principles and Paradigms. Second Edition. Chapter 6 ANDREW S. TANENBAUM MAARTEN VAN STEEN
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1 DISTRIBUTED SYSTEMS Principles and Paradigms Second Edition ANDREW S. TANENBAUM MAARTEN VAN STEEN واحد نجف آباد Chapter 6 SYNCHRONIZATION Dr. Rastegari - rastegari@iaun.ac.ir - Tel:
2 Synchronization Previous chapters, looked at processes and communication between processes. Communication is important, but not entire story. It is related to how processes cooperate and synchronize with one another. Cooperation is partly supported by means of naming, which allows processes to at least share resources, or entities in general. This chapter, mainly concentrates on how processes can synchronize. 2
3 Clock Synchronization Normally, in UNIX, large programs are split up into multiple source files. Changing a source file only requires one file to be recompiled, not all. Actually, make examines the times at which all the source and object files were last modified. Suppose time of input.c is 2151 and the object file input.o has time 2150, make knows that input.c has been changed and must be recompiled. 3
4 Problem in Distributed System In a distributed system which there were no global agreement on time. Suppose that output.o has time 2144 as above, and shortly thereafter output.c is modified but is assigned time 2143 because the clock on its machine is slightly behind. make will not call the compiler. 4
5 Clock Synchronization Figure 6-1. When each machine has its own clock, an event that occurred after another event may nevertheless be assigned an earlier time. 5
6 Physical Clocks (1) Figure 6-2. Computation of the mean solar day. Solar second is defined 1/86400th of a solar day. 6
7 Atomic Clock In 1948, measure time much more accurately, by counting transitions of the cesium 133 atom. Defined the second by the cesium 133 atom to make exactly 9,192,631,770 transitions. Several laboratories around the world have cesium 133 clocks. Each laboratory tells BIR in Paris how many times its clock has ticked. The BIR averages these to produce International Atomic Time (TAI). 7
8 Leap Seconds Figure 6-3. TAI seconds are of constant length, unlike solar seconds. Leap seconds are introduced when necessary to keep in phase with the sun. 8
9 Clock Synchronization Algorithms Real timers do not interrupt exactly H times a second. A timer with H = 60 should generate 216,000 ticks per hour. In practice, get a value in the range 215,998 to 216,002 ticks per hour. Figure 6-5. relation between clock time and UTC when clocks tick at different rates. 9
10 Network Time Protocol Figure 6-6. Getting the current time from a time server. 10
11 The Berkeley Algorithm (1) Figure 6-7. (a) The time daemon asks all the other machines for their clock values. 11
12 The Berkeley Algorithm (2) Figure 6-7. (b) The machines answer. 12
13 The Berkeley Algorithm (3) Figure 6-7. (c) The time daemon tells everyone how to adjust their clock. 13
14 Lamport s Logical Clocks (1978) Logical Clocks The "happens-before" relation can be observed directly in two situations: If a and b are events in the same process, and a occurs before b, then a b is true. If a is the event of a message being sent by one process, and b is the event of the message being received by another process, then a b A message cannot be received before it is sent, or even at the same time. 14
15 Lamport s Logical Clocks Figure 6-9. (a) Three processes, each with its own clock. The clocks run at different rates. 15
16 Lamport s Logical Clocks Figure 6-9. (b) Lamport s algorithm corrects the clocks. 16
17 Middlewear Figure The positioning of Lamport s logical clocks in distributed systems. 17
18 Lamport s Algorithm To implement Lamport's logical clocks, each process P i maintains a local counter C i. (Raynal and Singhal, 1996): Updating counter C i for process P i 1. Before executing an event P i executes C i C i When process P i sends a message m to P j, it sets m s timestamp ts (m) equal to C i. 3. Upon the receipt of a message m, process P j adjusts its own local counter as C j max{c j, ts (m)}, after which it then executes the first step and delivers the message to the application. 18
19 Example: Totally Ordered Multicasting Figure Updating a replicated database and leaving it in an inconsistent state. Assume a customer in San Francisco wants to add $100 to his account, which currently contains $1,000. At the same time, a bank employee in New York initiates an update by which the customer's account is to be increased with 1 percent interest. 19
20 Vector Clocks Figure Concurrent message transmission using logical clocks. The problem is that Lamport clocks do not capture causality 20
21 Causality Causality can be captured by means of vector clocks. A vector clock VC (a) assigned to an event a has the property that if VC (a) < VC (b) for some event b, then event a is known to causally precede event b. Vector clocks are constructed by letting each process P i maintain a vector VC i with the following two properties: VC i [ i ] is the number of events that have occurred so far at P i. In other words, VC i [ i ] is the local logical clock at P i. If VC i [ j ] = k then P i knows that k events have occurred at P j. It is thus P i s knowledge of the local time at P j. 21
22 Vector Clocks Steps carried out to accomplish property 2 of previous slide: 1. Before executing an event P i executes VC i [ i ] VC i [i ] When process P i sends a message m to P j, it sets m s (vector) timestamp ts (m) equal to VC i after having executed the previous step. 3. Upon the receipt of a message m, process P j adjusts its own vector by setting VC j [k ] max{vc j [k ], ts (m)[k ]} for each k, after which it executes the first step and delivers the message to the application. 22
23 Enforcing Causal Communication Figure Enforcing causal communication. The delivery of the message to the application layer will then be delayed until the following two conditions are met: 1. ts(m)[i] = VCj [i] ts(m)[k] VCj [k] for all k i 23
24 واحد نجف آباد Mutual Exclusion Dr. Rastegari - rastegari@iaun.ac.ir - Tel:
25 Mutual Exclusion A Centralized Algorithm (1) Figure (a) Process 1 asks the coordinator for permission to access a hared resource. Permission is granted. 25
26 Mutual Exclusion: A Centralized Algorithm (2) Figure (b) Process 2 then asks permission to access the same resource. The coordinator does not reply. 26
27 Mutual Exclusion A Centralized Algorithm (3) Figure (c) When process 1 releases the resource, it tells the coordinator, which then replies to 2. 27
28 A Distributed Algorithm (1) Three different cases: If the receiver is not accessing the resource and does not want to access it, it sends back an OK message to the sender. If the receiver already has access to the resource, it simply does not reply. Instead, it queues the request. If the receiver wants to access the resource as well but has not yet done so, it compares the timestamp of the incoming message with the one contained in the message that it has sent everyone. The lowest one wins. 28
29 A Distributed Algorithm (2) Figure (a) Two processes want to access a shared resource at the same moment. 29
30 A Distributed Algorithm (3) Figure (b) Process 0 has the lowest timestamp, so it wins. 30
31 A Distributed Algorithm (4) Figure (c) When process 0 is done, it sends an OK also, so 2 can now go ahead. 31
32 A Token Ring Algorithm Figure (a) An unordered group of processes on a network. (b) A logical ring constructed in software. 32
33 A Comparison of the Four Algorithms Figure A comparison of three mutual exclusion algorithms. 33
34 Global Positioning Of Nodes (1) Figure Computing a node s position in a two-dimensional space. 34
35 Global Positioning Of Nodes (2) Figure Inconsistent distance measurements in a one-dimensional space. 35
36 Election Algorithms The Bully Algorithm 1.P sends an ELECTION message to all processes with higher numbers. 2.If no one responds, P wins the election and becomes coordinator. 3.If one of the higher-ups answers, it takes over. P s job is done. 36
37 The Bully Algorithm (1) Figure The bully election algorithm. (a) Process 4 holds an election. (b) Processes 5 and 6 respond, telling 4 to stop. (c) Now 5 and 6 each hold an election. 37
38 The Bully Algorithm (2) Figure The bully election algorithm. (d) Process 6 tells 5 to stop. (e) Process 6 wins and tells everyone. 38
39 A Ring Algorithm Figure Election algorithm using a ring. 39
40 Elections in Wireless Environments (1) Figure Election algorithm in a wireless network, with node a as the source. (a) Initial network. (b) (e) The build-tree phase 40
41 Elections in Wireless Environments (2) Figure Election algorithm in a wireless network, with node a as the source. (a) Initial network. (b) (e) The build-tree phase 41
42 Elections in Wireless Environments (3) Figure (e) The build-tree phase. (f) Reporting of best node to source. 42
43 Elections in Large-Scale Systems (1) Requirements for superpeer selection: Normal nodes should have low-latency access to superpeers. Superpeers should be evenly distributed across the overlay network. There should be a predefined portion of superpeers relative to the total number of nodes in the overlay network. Each superpeer should not need to serve more than a fixed number of normal nodes. 43
44 Elections in Large-Scale Systems (2) Figure Moving tokens in a two-dimensional space using repulsion forces. 44
45 واحد نجف آباد Dr. Rastegari - rastegari@iaun.ac.ir - Tel:
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