1. Paper by Song Guo and Oliver Yang; supporting images and definitions from Wikipedia Presentation prepared by Al Funk, VT CS 6204, 10/30/07

2. Table of Contents  Background and related work  Models: system, network, mobility  DMEM algorithm  Operations  Performance  Conclusions

3. Background and related work  Multicast: communication technique which enables a source to send a single packet to reach multiple receivers.  Objective: Create a distributed algorithm to solve the Minimum Energy Multicast (MEM) problem  Definition of MEM: Find a route for multicast transmission with the minimum total energy consumption for a given communication session.  Challenges: MANET changing network topology, lack of central authority; problem is NP-hard

4. Background and related work  Prior research focused on:  Creating centralized, not distributed, algorithms  Efficient heuristic algorithm design  Weaknesses of prior research  Examination of static, not dynamic, network topologies  Little examination of performance impact of node mobility

5. Models: System Model  Discrete Power Level Management Model  Transmission range based on power level, but power level increases at an exponential rate as distance increases  Identify discrete power levels appropriate to reach nodes at various distances from the transmitter  Vary transmitter power in granular increments to balance power use with the bandwidth usage necessary to constantly adjust transmission strength

6. Models: System Model  P vu = Power level required to transmit from node v to node u  l vu = Layer (concentric ring from prior slide) of u relative to v  K = Number of discrete power levels of the transmitter (and therefore number of layers)  r K = Distance of ring K  α = Parameter (2 to 4) representing rate of signal attenuation

7. Models: Network Model  Represent network as a directed graph, G(N,A,p)  N = set of nodes, A = set of arcs, p = function representing power required for each arc  Rooted tree: directed acyclic graph with a source node that has no incoming arcs and where other nodes have a single incoming arc  Leaf vs. internal/relay nodes

8. Models: Network Model  For any node v in the rooted tree, there exists a single acyclic source route π v  Our goal is to set l v, the transmission layer of node v, to the minimum necessary for v to reach all of its child nodes  Once this is known, we can calculate p v, the necessary power level for the node

9. Models: Mobility  Mobility is a differentiator for the contribution, as alternative models require the significant overhead associated with central coordination.  Authors use “Random Waypoint Model”  Calculate random speeds bounded by V min and V max ; assume random start and end points; introduce pause between journeys.  Objective: calculate the steady-state average speed:

10. Algorithm: Data Structure  We need to store the forwarding state at each tree node v.  Membership status – sender, receiver, forwarder (can be receiver and forwarder)  Source route π – directed path from the source to node v (used to avoid loops)  Tree neighborhood table TN v – stores neighbors, along with whether is a father, child or other, along with layer l vu

11. Algorithm: Tree Construction  Minimum Spanning Tree: Given a connected, undirected graph with weighted edges, an MST is a subgraph which connects all vertices together resulting in the minimum total weight.

12. Algorithm: Tree Construction  MULTICAST-JOIN-REQUEST (MJREQ): Broadcast message initiated by the source used when no route information is known  MULTICAST-JOIN-REPLY (MJREP): Response message sent to previous hop node  MJREQ: Transmitted at maximum transmission power  MJREP: Returned at necessary power  Necessary power determined by strength of the original MJREQ message

13. Algorithm: Tree Flood  MULTICAST-ALIVE (MA): Message sent periodically during session to refresh the tree (otherwise tree routes are cleared)  Message sent at maximum power  Used to adjust power dynamically  Only sent if received from father (but then always sent)  Supports tree repair and energy saving operations  Nodes update neighborhood information to identify nearby nodes

14. Localized Operations  Normal Energy Saving (NES): Upon receipt of MA from children, node adjusts its transmission power to the minimum necessary.  Reactive approach which could lower total power utilization  Keeps the tree connected but not with maximum efficiency

15. Localized Operations: SHO  Soft Hand-Off (SHO): Initiated by a node that detects it is leaving its father’s transmission range (K).  Goal is to identify a new father s.t. and power utilization is minimized  Node severs link with previous father (via MULTICAST-LEAVE (ML) message), selects the new father  Tree is maintained.

16. Localized Operations: MTR  Multicast Tree Repair (MTR): In the case where loss of a node results in a tree partition, we need a way to repair the multicast tree.  Occurs when a forwarder or receiver fails to receive successive MAs from its father  Nodes furthest from the source attempt to reconnect first  MULTICAST-JOIN-SOLICITATION (MJS): Hop- limited message

17. Localized Operations: MTR  Disconnected node closest to source notifies the subtree that it is initiating repair procedures using an MA message  The closest node to the source initiates an MJREP message and attempts to reconnect the subtree back to the multicast tree  If an appropriate node responds, the tree is reconnected; if not, other nodes in the subtree attempt to reconnect, and the node(s) that failed must rejoin through a network flood.

18. Localized Operations: AES  Advanced Energy Savings (AES): A proactive method of reallocating child nodes s.t. overall power utilization of the system is reduced.  The major contribution of the paper  We must be able to retain the MST structure for multicast  Operation performed as part of MA  Approach: Each child node attempts to extend its transmission range to become the parent of a current child of its father – but only if such a change reduces the total power utilization of the system  More sophisticated than NES  They are not mutually exclusive

19. Localized Operations: AES  Using the MA message header means that no separate message is necessary for the operation  Use of MA messages fits the algorithm -- father to child propagation enables communication of power levels and supports child decision-making.  At each transmission from its father, a node modifies header with its own information and propagates to its neighbors  Because MA messages are at full power, neighbors of multicast tree nodes will receive.  As a result, non-multicast tree nodes can join, but must consider potential added cost of the link from a father node

20. Localized Operations: AES  AES-REQUEST: When a node identifies a power savings, it sends an AES-REQUEST to the source  Source reviews AES-REQUEST messages and sends AES-REPLY to the node with the greatest power savings

21. Localized Operations: AES  Finalizing the update  Selected node sends local broadcast TREE-UPDATE and assigns itself as father to the node to move  Moving node leaves father, sending MULTICAST- LEAVE.  If selected node is a non-tree node, it must find a father  It will be a forwarding node only, otherwise it would have been part of the original tree  Multiple nodes may become children of the selected node if power savings justify

22. Localized Operations: AES  Examples of AES tree revision

23. Performance Evaluation  Simulations  Ad hoc network with size 1,000 meters sq.  Each node can transmit 250 meters  K=10  α = 2  Modeled max node movement speeds of: 1, 5, 10, 15, 20 and 25 m/s  Multicast groups 5, 25, 50, 75, 100  Static networks considered  50 scenarios for each multicast group

24. Performance Evaluation  Measures  Relative tree power: Ratio of actual total tree power for heuristic algorithm vs. ideal of MST algorithm  Average tree power: Power used over time for the tree  Communication overheads: Overhead for AES, SHO and MTR as a total number of these operations over each simulation

25. Performance Evaluation  Static network evaluation  Compared DMEM against prior work  Not key to the paper, but demonstrates that DMEM is a useful heuristic compared with prior research

26. Performance Evaluation  Mobile network evaluation: Consider with and without optional protocol components

27. Performance Evaluation  Examine AES performance considering node speed and multicast group size.

28. Performance Evaluation  Examine SHO operations given node speed and multicast group size.

29. Performance Evaluation  MTR operations considering node speed and multicast group size.

30. Conclusions  In a static network, DMEM is superior to alternative algorithms for medium and large multicast groups.  Measures heuristics, but major contribution is on dynamic network  DMEM is efficient in reducing energy utilization  AES provides significant value relative to base case  SHO is mostly redundant when using AES  DMEM proven correct for maintaining tree structure using localized operations

31. Critique  Graphs are not presented in such a way to visually support the analysis  e.g., authors require visual comparison of separate charts to compare AES and SHO, rather than presenting a single chart  Is it scalable? Authors indicate that AES becomes saturated; this seems to occur rapidly in “large” networks even at slow speed.  Authors indicate that it is scalable with regard to mobility – but AES saturation seems to put this in question, as do some of their comments right before the conclusion  If scalability is an issue, possible approaches to address it would have been welcome  Do the arbitration performed by the source node along with the broadcast approach amount to centralization that reduces scalability and creates a bottleneck?