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Leader Election. Yu Meng 09-25-2013. Outline. Basic knowledge Overview of Leader Election Complete Topology Logical Ring Topology Three Topology Latest relevant knowledge Future works References. Basic knowledge. Leader election. - PowerPoint PPT Presentation
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LEADER ELECTIONYu Meng09-25-2013
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OUTLINE Basic knowledge
Overview of Leader Election Complete Topology Logical Ring Topology Three Topology
Latest relevant knowledge Future works References
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BASIC KNOWLEDGE
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LEADER ELECTION Centralized Controller greatly simplifies
process synchronization A simple point failure can limit service
availability A new controller (the leader) can be chose
upon failure of the existing controller Known to all other processes in the group The initial of the system or a existing leader
failed The detection of failure is based on a time-
out
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ELECTION CRITERIA Extrema Finding
Based on a global priority
Preference-based leader election algorithm Processes in the group can vote for a leader
based on a personal-preference More general than Extrema Finding Resulting in more complex decision-making
outcome
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LEADER ELECTION VS. MUTUAL EXCLUSION Both try to reach an agreement for
identifying a unique process Differences:
A mutual exclusion must ensure that no process is starved, while a leader election is more concerned with the fast and successful termination of the election process
Leader election need to be announced to all processes
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COMPLETE TOPOLOGY Each process in the group can reach any
other process in one message hop Assumptions:
All process ids are unique and known to other process
Communication network is reliable and only the process may fail
A failure is reliable detected Each process as a global priority and the
highest-priority is elected leader
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BULLY ALGORITHM Extrema-finding algorithm Process with the highest-priority process as
the leader Bully Algorithm:
Process P starts a leader election if it suspects the failure of existing leader
P sends inquiry message to nodes with higher priority
If any response then, P gives up the election and waits for higher priority node to elect itself leader
If no response then P becomes a leader
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BULLY ALGORITHM
Process 4 detected leader failure and request an election
Process 5 and 6 response, then 4 stop Process 5 and 6 each hold a election
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BULLY ALGORITHM
Process 6 take the response and act as the leader
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LOGICAL RING TOPOLOGY Easy to construct Message initiated by node will return to itself Indicating completion of a round of operation
without the need for acknowledge Two phases:
Initiation: One process send an election message to its successors with its ID then each process add its own ID in the forwarding message
Leader election: Message come back to initiator then the initiator announce itself as leader and broadcast to others
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LOGICAL RING TOPOLOGY
Phase 1: Initiator Phase 2: Leader election
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TREE TOPOLOGIES A tree used for representing topological
structure
Each node is considered as an autonomous entity to exchange message with adjacent nodes
A minimum-weight spanning tree (MST) are employed
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TREE TOPOLOGY Gallager, Humbelt, and Spira’s algorithm is
based on searching and combining
Starting from each node and attaching level by level till it ends up with the MST
The last node that merges and yields to the final MST becomes the leader
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LATEST RELEVANT KNOWLEDGE
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RELEVANT RESEARCH In a distribution computing system or mobile network, leader
election is a very important issue. They propose a consensus-based leader election algorithm. By analyzing the mathematic analysis and algorithm simulation results, we notice that, when a new leader is elected, the proposed algorithm guarantees a consensus be reached while at the same time reducing the number of message passing.
(Chi-Chun Lo et. al., 2012)
Leader election in the presence of selfish nodes for intrusion detection in mobile ad hoc networks (MANETs). To balance the resource consumption among all nodes and prolong the lifetime of an MANET, nodes with the most remaining resources should be elected as the leaders. They justify the effectiveness of the proposed schemes through extensive experiments.
(Prabir Bhattacharya et. al., 2009)
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RELEVANT RESEARCH The space complexity: The necessary or sufficient number
of bits on processors to execute a leader election algorithm. Only one bit memory is sufficient for a leader election algorithm which is specific to a fixed n. A lower bound Omega(log n) on the space complexity, that is, it is impossible to construct a leader election algorithm if only log n bits are available for a processor.
(Masafumi Yamashita et. al., 2008)
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FUTURE WORKS
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FUTURE WORKS Apply the algorithm to cloud computing
problem
Dynamic consolidation of virtual machine with performance and energy trade-off
Virtual machine live migration with detecting failure of physical host
Possible application to detect the failure nodes under service level agreements
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REFERENCES1. Chow, Randy, et. al.,Distributed Operating Systems & Algorithms,
Addison Wesley, March 18, 19972. R. G. Gallager, P. A. Humblet, and P. M. Spira. "A Distributed Algorithm
for Minimum-Weight Spanning Trees". ACM Transactions on Programming Languages and Systems 5 (1): 66–77
3. Ephraim Korach, Shay Kutten, Shlomo Moran. "A Modular Technique for the Design of Efficient Distributed Leader Finding Algorithms".ACM Transactions on Programming Languages and Systems 12 (1): 84–101
4. DALAL, Y. Broadcast protocols in packet switched computer networks. Tech. Rep. 128, Dep. of Electrical Engineering, Stanford Univ., Apr. 1977
5. Mohammed, N. ; Otrok, H. ; Lingyu Wang ; Debbabi, M. ; Bhattacharya, P. ,Mechanism Design-Based Secure Leader Election Model for Intrusion Detection in MANET.Dependable and Secure Computing, IEEE Transactions on, 2011, 89-103
6. HUMBLET, P.A. A distributed algorithm for minimum weight directed spanning trees. Rep LIDS-P-1149, Laboratory for Information and Decision Systems, Massachusetts Inst. of Technology, Cambridge, Mass., Sept. 1981
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REFERENCES7. Hsu-Chia Cahng ; Chi-Chun Lo, "A Consensus-Based Leader
Election Algorithm for Wireless Ad Hoc Networks" Computer, Consumer and Control (IS3C), 2012 International Symposium, 2012 , 232- 235
8. LAWLER, E. Combinatorial Optimization-Networks and Matroids. Holt, Rinehart & Winston, New York, 1976.
9. LIU, C.L. Introduction to Combinatorial Mathematics. McGraw Hill, New York, 1968
10. PRIM, R.C. Shortest connection networks and some generalizations. Bell Syst. Tech. J. 36 (1957), 1389-1401.
11. YAO, A.C.C. An O(E log log V) algorithm for finding minimum spanning trees. Inf. Process. Lett. 4 (1975), 21-23
12. Andot, E. ; Ono, H. ; Sadakane, K. ; Yamashita, M. “The space complexity of the leader election in anonymous networks” Parallel and Distributed Processing, 2008 , 1-8
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