1.2 Manuscript Organization

This manuscript is divided in six chapters.

Chapter 2 introduces background concepts on distributed systems and on leader election problems.

Chapter 3 presents related work on the classical and eventual leader election problems in both static and dynamic systems. Algorithms are compared and classified in tables according to different criteria.

Chapter 4 describes the first contribution of this thesis, the Topology Aware eventual leader election algorithm. Evaluation results on PeerSim of Topology Aware and a flooding algorithm [VKT04] are presented.

Chapter 5 presents the second contribution, the Centrality-based Eventual Leader (CEL) election algorithm. Evaluations results on OMNeT++, using IEEE 802.11n communications, of CEL and the Ω algorithm of Gómez-Calzado et al. [Góm+13] are presented.

Finally, Chapter 6 concludes the thesis and discusses different future research directions.

Table of Contents

1 Introduction
1.1 Contributions
1.1.1 Topology Aware Leader Election Algorithm for Dynamic Networks
1.1.2 Centrality-Based Eventual Leader Election in Dynamic Networks
1.2 Manuscript Organization
1.3 Publications
1.3.1 Articles in International Conferences
1.3.2 Articles in National Conferences
2 Background
2.1 Properties of Distributed Algorithms
2.2 Timing Models
2.3 Process Failures
2.4 Communication Channels
2.5 Failures of Communication Channels
2.6 Distributed Systems
2.6.1 Static Systems
2.6.2 Dynamic Systems
2.7 Centralities
2.8 Messages Dissemination
2.9 Leader Election
2.9.1 Classical Leader Election
2.9.2 Eventual Leader Election
2.10 Conclusion
3 Related Work
3.1 Classical Leader Election Algorithms
3.1.1 Static Systems
3.1.2 Dynamic Systems
3.2 Eventual Leader Election Algorithms
3.2.1 Static Systems
3.2.2 Dynamic Systems
3.3 Conclusion
4 Topology Aware Leader Election Algorithm for Dynamic Networks
4.1 System Model and Assumptions
4.1.1 Node states and failures
4.1.2 Communication graph
4.1.3 Channels
4.1.4 Membership and nodes identity
4.2 Topology Aware Leader Election Algorithm
4.2.1 Pseudo-code
4.2.2 Data structures, variables, and messages (lines 1 to 6)
4.2.3 Initialization (lines 7 to 11)
4.2.4 Periodic updates task (lines 12 to 16)
4.2.5 Connection (lines 20 to 23)
4.2.6 Disconnection (lines 24 to 27)
4.2.7 Knowledge reception (lines 28 to 38)
4.2.8 Updates reception (lines 39 to 53)
4.2.9 Pending updates (lines 54 to 65)
4.2.10 Leader election (lines 17 to 19)
4.2.11 Execution examples
4.3 Simulation Environment
4.3.1 Algorithms
4.3.2 Algorithms Settings
4.3.3 Mobility Models
4.4 Evaluation
4.4.1 Metrics
4.4.2 Instability
4.4.3 Number of messages sent per second
4.4.4 Path to the leader
4.4.5 Fault injection
4.5 Conclusion
5 Centrality-Based Eventual Leader Election in Dynamic Networks
5.1 System Model and Assumptions
5.1.1 Node states and failures
5.1.2 Communication graph
5.1.3 Channels
5.1.4 Membership and nodes identity
5.2 Centrality-Based Eventual Leader Election Algorithm
5.2.1 Pseudo-code
5.2.2 Data structures, messages, and variables (lines 1 to 4)
5.2.3 Initialization (lines 5 to 7)
5.2.4 Node connection (lines 8 to 17)
5.2.5 Node disconnection (lines 18 to 23)
5.2.6 Knowledge update (lines 24 to 34)
5.2.7 Neighbors update (lines 35 to 41)
5.2.8 Information propagation (lines 42 to 47)
5.2.9 Leader election (lines 48 to 52)
5.3 Simulation Environment
5.3.1 Algorithms Settings
5.3.2 Mobility Models
5.4 Evaluation
5.4.1 Metrics
5.4.2 Average number of messages sent per second per node
5.4.3 Average of the median path to the leader
5.4.4 Instability
5.4.5 Focusing on the 60 meters range over time
5.4.6 A comparative analysis with Topology Aware
5.5 Conclusion
6 Conclusion and Future Work
6.1 Contributions
6.2 Future Directions
A Appendix
A.1 Energy consumption per node
A.1.1 Simulation environment
A.1.2 Algorithms settings
A.1.3 Mobility Models
A.1.4 Metric
A.1.5 Performance Results