Distributed Computing (2008)
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Distributed Computing (2008)


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and broadcasts a request to take snapshot. When some other process receives
this request, it takes a snapshot. Channels are not FIFO.
Prove that such a collected distributed snapshot will be consistent iff the following
holds (assume there are n processes in the system and Vti denotes the vector timestamp
of the snapshot taken process pi):
\ufffdVt1\ufffd1\ufffd\ufffdVt2\ufffd2\ufffd\ufffd \ufffd \ufffd \ufffd \ufffd \ufffd Vtn\ufffdn\ufffd\ufffd=max\ufffdVt1\ufffdVt2\ufffd \ufffd \ufffd \ufffd \ufffd \ufffd Vtn\ufffd\ufffd
Don\u2019t worry about channel states.
Exercise 4.2 What good is a distributed snapshot when the system was never in
the state represented by the distributed snapshot? Give an application of distributed
snapshots.
Exercise 4.3 Consider a distributed system where every node has its physical clock
and all physical clocks are perfectly synchronized. Give an algorithm to record global
state assuming the communication network is reliable. (Note that your algorithm
should be simpler than the Chandy\u2013Lamport algorithm.)
Exercise 4.4 What modifications should be done to the Chandy\u2013Lamport snapshot
algorithm so that it records a strongly consistent snapshot (i.e., all channel states are
recorded empty).
Exercise 4.5 Consider two consistent cuts whose events are denoted by C1 =
C1\ufffd1\ufffd\ufffdC1\ufffd2\ufffd\ufffd 
 
 
 \ufffdC1\ufffdn\ufffd and C2 = C2\ufffd1\ufffd\ufffdC2\ufffd2\ufffd\ufffd 
 
 
 \ufffdC2\ufffdn\ufffd, respectively.
Define a third cut, C3 = C3\ufffd1\ufffd\ufffdC3\ufffd2\ufffd\ufffd 
 
 
 \ufffdC3\ufffdn\ufffd, which is the maximum of C1
and C2; that is, for every k, C3\ufffdk\ufffd= later of C1(k) and C2\ufffdk\ufffd.
Define a fourth cut, C4 = C4\ufffd1\ufffd\ufffdC4\ufffd2\ufffd\ufffd 
 
 
 \ufffdC4\ufffdn\ufffd, which is the minimum of C1
and C2; that is, for every k, C4\ufffdk\ufffd= earlierof C1(k) and C2\ufffdk\ufffd.
Prove that C3 and C4 are also consistent cuts.
4.12 Notes on references
The notion of a global state in a distributed system was formalized by Chandy and
Lamport [7] who also proposed the first algorithm (CL) for recording the global state,
and first studied the various properties of the recorded global state. The space\u2013time
diagram, which is a very useful graphical tool to visualize distributed executions, was
introduced by Lamport [19]. A detailed survey of snapshot recording algorithms is
given by Kshemkalyani et al. [16].
Spezialetti and Kearns proposed a variant of the CL algorithm to optimize con-
current initiations by different processes, and to efficiently distribute the recorded
snapshot [29]. Venkatesan proposed a variant that handles repeated snapshots effi-
ciently [32]. Helary proposed a variant of the CL algorithm to incorporate message
waves in the algorithm [12]. Helary\u2019s algorithm is adaptable to a system with non-
FIFO channels but requires inhibition [31]. Besides Helary\u2019s algorithm [12], the
123 References
algorithms proposed by Lai and Yang [18], Li et al. [20], and by Mattern [23] can
all record snapshots in systems with non-FIFO channels. If the underlying network
can provide causal order of message delivery [5], then the algorithms by Acharya
and Badrinath [1] and by Alagar and Venkatesan [2] can record the global state using
O\ufffdn\ufffd number of messages.
The notion of simultaneous regions for monitoring global state was proposed by
Spezialetti and Kearns [30]. The necessary and sufficient conditions for consistent
global snapshots were formulated by Netzer and Xu [25] based on the zigzag paths.
These have particular application in checkpointing and recovery. Manivannan et al.
analyzed the set of all consistent snaspshots that can be built from a given set of
checkpoints [21]. They also proposed an algorithm to enumerate all such consistent
snapshots. The definition of the R-graph and other notations and framework used
by [21] were proposed by Wang [33, 34].
Recording the global state of a distributed system finds applications at several
places in distributed systems. For applications in detection of stable properties such as
deadlocks, see [17] and for termination, see [22]. For failure recovery, a global state
of the distributed system is periodically saved and recovery from a processor failure
is done by restoring the system to the last saved global state [15]. For debugging
distributed software, the system is restored to a consistent global state [8, 9] and the
execution resumes from there in a controlled manner. A snapshot recording method
has been used in the distributed debugging facility of Estelle [11, 13], a distributed
programming environment. Other applications include monitoring distributed events
[30], setting distributed breakpoints [24], protocol specification and verification
[4, 10, 14], and discarding obsolete information [11].
We will study snapshot algorithms for shared memory in Chapter 12.
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