ECMANSI - Energy Conserving Multicast for Ad- Hoc Networks with Swam Intelligence Chaiporn Jaikaeo Vinay Sridhara Chien-Chung Shen

Motivation Swarm Intelligence – Biological Metaphor MANSI – Overview MANSI – Framework Protocol Description ECMANSI – Description ECMANSI – Simulation Scenario ODMRP – Overview ECMANSI – Simulation Results Summary and Future work

More than often Point to Multipoint communication is required Power efficient multicast for MANETs –The mobile nodes are energy constrained –The communication module often accounts for a considerable amount of energy expenditure –Also the topology of the Ad-Hoc networks can be controlled by adjusting the transmission power of each individual node to reduce interference –Controlling the transmission power of node may increase the overall network lifetime MOTIVATION

Motivation Swarm Intelligence – Biological Metaphor MANSI – Overview MANSI – Framework Protocol Description ECMANSI – Description ECMANSI – Simulation Scenario ODMRP – Overview ECMANSI – Simulation Results Summary and Future work

Swarm Intelligence Biological Metaphor Essence of Swarm Intelligence –Positive and negative feedback search good solutions and stabilize the results –Amplification of fluctuation discover new solutions and adapt to changing environment –Multiple interactions Allows collaborations among distributed entities to coordinate and self-organize  A distributed adaptive control system

Ants likely choose paths with higher pheromone intensity Trail gets reinforced (positive feedback) skip Ants lay pheromone Without reinforcement, pheromone evaporates (negative feedback)

skip Most ants follow trail with highest intensity But some may choose alternate paths with small probability (amplification of fluctuation) Pheromone Trail

Motivation Swarm Intelligence – Biological Metaphor MANSI – Overview MANSI – Framework Protocol Description ECMANSI – Description ECMANSI – Simulation Scenario ODMRP – Overview ECMANSI – Simulation Results Summary and Future work

MANSI – Overview Connected subgraph containing all the forwarding nodes are extracted – Forwarding Set Forwarding Set consists of nodes which are shared by all the group members – Group Shared Approach Forwarding Nodes always rebroadcasts the packet regardless of the previous hop node – Mesh Based Approach Forwarding set is constructed only when a node (Source) has data to send – Reactive Approach  MANSI – Multicast for Ad Hoc Networks with Swarm Intelligence m1m1 m2m2 m3m3 skip

MANSI – Overview Each member establishes connectivity to a designed member which serves as the focal point. Multicast connectivity is more efficient when group members share existing forwarding nodes Forwarding set of 6 nodes m1m1 m3m3 m2m2 Forwarding set of 4 nodes m1m1 m3m3 m2m2

Motivation Swarm Intelligence – Biological Metaphor MANSI – Overview MANSI – Framework Protocol Description ECMANSI – Description ECMANSI – Simulation Scenario ODMRP – Overview ECMANSI – Simulation Results Summary and Future work

MANSI-Framework Protocol Operations  Three step process Source Node Neighbor Discovery –A node which has data to send becomes CORE node and broadcasts a JOIN_REQUEST –All the nodes that receive the JOIN_REQUEST rebroadcast the request and the one hop neighbor information is discovered skip

MANSI-Framework Protocol Operations Forwarding Set Initialization –A forwarding set is rapidly constructed on-demand –Non-duplicate announcement is rebroadcast by all nodes –Other members request to join the group via the reverse paths –Requested nodes become forwarding nodes and form the forwarding set Core Core floods announcement Members reply via reverse paths Initial Forwarding set has formed skip

MANSI-Framework Protocol Operations Forwarding Set Evolution –Forward Ants (packets) are deployed by members to opportunistically learn new connectivity that yields lower cost –A Forward Ant turns into a Backward Ant when it encounters another existing path and returns to its originator Core Cost = 3 Cost = 2 Ants follow current best paths and update costs Core Ants opportunistically discover other paths Cost = 2Cost = 1 Total cost = 5Total cost = 4 skip

MANSI-Framework Protocol Operations Pheromone Updating –The Backward Ant deposits pheromone on its return trip to the sender –The Amount of Pheromone deposited is inversely proportional to the cost of the trip. Shorter the trip  Higher the pheromone deposition skip Core Cost = 0 Cost = 1 Cost = 2 m2m2 m1m1 turn into Backward Ant B C A D E

Motivation Swarm Intelligence – Biological Metaphor MANSI – Overview MANSI – Framework Protocol Description ECMANSI – Description ECMANSI – Simulation Scenario ODMRP – Overview ECMANSI – Simulation Results Summary and Future work

Energy Conserving MANSI Assumptions –Nodes are capable of adjusting their transmission power levels (0, P max ) –Ant packets and Hello packets are always transmitted at full power Objective –Reduce total energy consumed per multicast packet –The cost of a node becoming a forwarding node is the transmission power level required by the node to transmit the multicast packet

30 mW 20 mW 2 mW 4 mW 8 mW Total of - 2 transmissions - 50 mW Total of - 2 transmissions - 50 mW Total of - 5 transmissions - 18 mW Total of - 5 transmissions - 18 mW Energy Conserving MANSI Number of transmission VS total power consumption

Energy Conserving MANSI Required Transmission Power Generic Propagation Formula Required Sensitivity Required Transmission power Calculated by transmitting HELLO packet at full power

Energy Conserving MANSI Required Transmission Power Calculated by transmitting HELLO packet at full power For data packets, a forwarding node i computes its transmission power level as follows: where Di is a set of nodes who request and are requested by i to be a forwarding node i i ’s communication range when broadcasting data packets

Cost of a node can increase when a farther node choose the current node as a forwarder Energy Conserving MANSI Join Request Path

ECMANSI – MANSI (Comparative illustration) Energy Conserving MANSI MANSI EC-MANSI

Forwarding cost over time Energy Conserving MANSI

With mobility, multicast connectivity becomes fragile (EC)MANSI with mobility-adaptive mechanism –Each node keeps track of link failure frequency which indicates stability of its surrounding area. –When link failure frequency is higher than the threshold, a forwarding/member node picks two forwarding nodes with highest pheromone intensities, instead of one Energy Conserving MANSI Without mobility-adaptiveWith mobility-adaptive – more robust group connectivity Adaptability to mobility

Motivation Swarm Intelligence – Biological Metaphor MANSI – Overview MANSI – Framework Protocol Description ECMANSI – Description ECMANSI – Simulation Scenario ODMRP – Overview ECMANSI – Simulation Results Summary and Future work

Energy Conserving MANSI Terrain dimension1000×1000 m 2 # Nodes Communication range250 m Mobility speed0-10 m/s # Members10 # Senders1-8 Application Traffic CBR (4  512B/s from each sender) Ten random networks on QualNet simulator Multicast sessions running for 30 minutes Network parameters Simulation Scenario

Motivation Swarm Intelligence – Biological Metaphor MANSI – Overview MANSI – Framework Protocol Description ECMANSI – Description ECMANSI – Simulation Scenario ODMRP – Overview ECMANSI – Simulation Results Summary and Future work

ODMRP Overview On Demand Multicast Routing Protocol (Lee, Su, Gerla – UCLA) Each sender floods JOIN-DATA (data+query) to find members on-demand Members propagate JOIN-REPLY back to the sender, resulting in mesh creation As long as a sender still has data to send, it periodically floods JOIN-DATA to refresh the mesh Flooding by every sender causes a scalability problem in large networks, especially with many senders

ODMRP Overview F A B E D G H I SenderNextHop HC SenderNextHop HD SenderNextHop HH C skip

Motivation Swarm Intelligence – Biological Metaphor MANSI – Overview MANSI – Framework Protocol Description ECMANSI – Description ECMANSI – Simulation Scenario ODMRP – Overview ECMANSI – Simulation Results Summary and Future work

Energy Conserving MANSI Simulation Results Network Size Number of Sources Mobility Packet Delivery Ratio

Energy consumed per multicast Packet Energy Conserving MANSI Simulation Results Network Size Number of Sources Mobility

Energy Conserving MANSI Simulation Results Control Packet Overhead Network Size Number of Sources Mobility

Motivation Swarm Intelligence – Biological Metaphor MANSI – Overview MANSI – Framework Protocol Description ECMANSI – Description ECMANSI – Simulation Scenario ODMRP – Overview ECMANSI – Simulation Results Summary and Future work

An Energy Conserving Multicast protocol – ECMANSI is proposed By adopting the Swarm Intelligence metaphor, forwarding nodes are chosen and their transmission power levels are adjusted dynamically Simulation experiments show that energy consumption can be reduced drastically Future Work –Incorporate changing of reception power into pheromone table maintenance, to deal with mobility more appropriately –Having an extra cost field for each node – amounting to remaining battery power

Questions

Thank You !!!