Leader Election Algorithms for Mobile Ad Hoc Networks Presented by: Joseph Gunawan

Purpose Introduce two new leader election algorithms for mobile ad hoc networks (one for single topology change and the other for multiple concurrent topology change), which ensure each connected component of the topology graph has exactly one leader.

Outline Introduction Related Works System Used Leader Algorithm for a Single Topology Change Leader Election Algorithm for Concurrent Changes

Why do we select a leader? Ad hoc network is formed when the nodes are deployed. Communication among nodes most likely happen within the network. If the formed network topology changes, some node within the network might fail to communicate with the previous node, such as in the distributed ad hoc network. Therefore, there is a need to form a leader so that the network could be maintained, such as maintaining the clock synchronization within the network or choosing a new coordinator when the group membership changes in the group communication protocols.

Leader Selection Since then, leader election becomes a useful building block in distributed systems for specific application, whether wired or wireless, especially when failures can occur. Standard definition of leader election: ◦There is a leader within a network ◦And, there should never be more than one leader.

Leader Selection If partition occurs, the algorithm ensures that the network has a unique leader within the partition. If the network merge, there should be only one leader based on the node id.

Leader Selection The two algorithms based on ◦TORA (Temporally Ordered Routing Algorithm), which is in turn based on a loop-free routing algorithm of GB (Gafni and Bertsekas). ◦TORA uses Directed Acyclic Graph (DAG) and uses the sink as the destination. ◦TORA can detect the partition.

Leader Selection The ideas of the algorithms: ◦Ensures each network eventually forms a leader-oriented DAG. ◦If there is a network partition detected by the current leader, a new leader is elected and its id is propagated throughout the component. ◦If the network is merge, the winner is the one who has the smallest id. The looser will be wiped out. ◦Whenever the new leader id is being propagated and the topology is indeed changing, the leader selection process may be repeated.

Outline Introduction Related Works System Used Leader Algorithm for a Single Topology Change Leader Election Algorithm for Concurrent Changes

Non-Compulsory & Compulsory Protocols Non-Compulsory does not affect the motion of the nodes. Compulsory determines the motion of the nodes. Nodes move in a bounded three-dimensional space S (regular polyhedron). Nodes know in advance the type and dimensions of the space Nodes must be able to measure the distance that they cover when they move. Never issue the creation of new network due to partitioning and merging the network.

Multicast Ad-hoc On-Demand Distance Vector (AODV) A new multicast group leader is being elected when a partition occurs. There will be two group leaders when partition happens. If the partition network reconnect, the AODV ensures that there will be only one group leader.

Outline Introduction Related Works System Used Leader Algorithm for a Single Topology Change Leader Election Algorithm for Concurrent Changes

Assumption Nodes have unique identifiers. Communication links are bidirectional, reliable and FIFO. Each of the nodes is aware of the set of nodes with which it can currently directly communicate by providing indications of link formations and failures.

System Model A set of n independent mobile nodes. Nodes communicate using message passing over a wireless network. Network is a dynamic network. Each node i in the system must have a local variable lidi that holds the identifier of the node currently considered to be the leader of i’s component. The network forms a directed acyclic graph with the leader as the single sink (called a leader-oriented)

Outline Introduction Related Works System Used Leader Algorithm for a Single Topology Change Leader Election Algorithm for Concurrent Changes

Gafni and Bertsekas Algorithm Gafni and Bertsekas (GB) describe two algorithm (generic algorithm and partial reversal algorithm) for constructing a destination-oriented DAG, which subject to link failures. Both of them assigning a unique height to each node, which is drawn from a totally ordered set. Each link between two nodes is considered to be directed from the node with the higher height to the node with the lower height. If the node is not a sink, a new height is being calculated, whenever it loses all its outgoing links, either because of a failure or because of a change in a neighbor’s height.

Gafni and Bertsekas Algorithm In the partial reversal algorithm, the height of a node I is a triple (∂i, βi, i) of integers. The height is compared lexicographically. A new height (∂i’, βi’, i) is chosen whenever the node i loses all its outgoing links, which ∂i’ is one larger than the smallest ∂i in the network. If ∂i’ = ∂i, then βi’ is the one which is lesser than the smallest β value in the network.

TORA Algorithm Most likely similar to GB algorithm. The height is setup to be 5-tuple The first three components form a reference level. Whenever, a node i loses its last outgoing link due to link failure, node i starts a new reference level. The third and fourth component are the important one. The third component is the instrument for detecting network partition. The fourth component help to form the destination-oriented DAG.

Leader Election Algorithm for a single topology change The height is 6-tuple The first component is the leader of the i’s network. The remaining five components are similar to TORA. The reference level (-1, -1, -1) is used by the leader of the network to ensure that it is a sink. The node elects itself to be a leader whenever it detects the partition and propagate its information into other nodes. When the network merges, the leader of the network will be the node with the smallest id.

Leader Election Algorithm for a single topology change Node i stores its neighbors’ ids in local variable Ni. Ni being updated every time the network fails or formed. Update message, which contains the node i’ height, is sent to all neighbors whenever the network is formed. Receiving the Update message, node updates a local data structure that keeps track of the current height reported for each of its neighbors. (height i [j], i is the node and j is node’s neighbors) After the height being update, each of the nodes sends the Update message with new height to its’ neighbors.

Leader Election Algorithm for a single topology change

Leader Election Algorithm for a concurrent change