Multicast Multi-path Power Efficient Routing in Mobile ADHOC networks


Aim of this project work has been proposed to maximize the network lifetime and minimizes the power consumption during the source to destination route establishment. The proposed work is aimed to provide efficient power aware routing considering real and non real time data transfer.


This proposal of this project presents a measurement-based routing algorithm to load balance intra domain traffic along multiple paths for multiple multicast sources. Multiple paths are established using application-layer overlaying. The proposed algorithm is able to converge under different network models, where each model reflects a different set of assumptions about the multicasting capabilities of the network. The algorithm is derived from simultaneous perturbation stochastic approximation and relies only on noisy estimates from measurements. Simulation results are presented to demonstrate the additional benefits obtained by incrementally increasing the multicasting capabilities. The main application of mobile ad hoc network is in emergency rescue operations and battlefields. This project addresses the problem of power awareness routing to increase lifetime of overall network. Since nodes in mobile ad hoc network can move randomly, the topology may change arbitrarily and frequently at unpredictable times. Transmission and reception parameters may also impact the topology. Therefore it is very difficult to find and maintain an optimal power aware route


The existing work on multicast routing with power constraints are refer in the literatures Propose a solution to optimally distribute the traffic along multiple multicast trees. However, the solution covers the case when there is only one active source in the network. In addition, it is assumed that the gradient of an analytical cost function is available, which is continuously differentiable and strictly convex. These assumptions may not be reasonable due to the dynamic nature of networks.

Even though they approach the problem under a more general architecture, practicality of these solutions is limited due to the unrealistic assumption that the network is lossless as long as the average link rates do not exceed the link capacities. Moreover, a packet loss is actually much more costly when network coding is employed since it potentially affects the decoding of a large number of other packets. In addition, any factor that changes the min-cut max-flow value between a source and a receiver requires the code to be updated at every node simultaneously, which brings high level of complexity and coordination.


The proposal in this paper presented a distributed optimal routing algorithm to balance the load along multiple paths for multiple multicast sessions. Our measurement-based algorithm does not assume the existence of the gradient of an analytical cost function and is inspired by the unicast routing algorithm based on Simultaneous Perturbation Stochastic Approximation (SPSA). In addition, we address the optimal multipath multicast routing problem in a more general framework than having multiple trees. We consider different network models with different functionalities.

With this generalized framework, our goal is to examine the benefits observed by the addition of new capabilities to the network beyond basic operations such as storing and forwarding. In particular, we will first analyze the traditional network model without any IP multicasting functionality where multiple paths are established using (application-layer) overlay nodes. Next, we consider a network model in which multiple trees can be established. Finally, look at the generalized model by allowing receivers to receive multicast packets at arbitrarily different rates along a multicast tree. Such an assumption potentially creates a complex bookkeeping problem since source nodes have to make sure each receiver gets a distinct set of packets from different trees

REMiT (An algorithm for Refining Energy-Efficient Source-based Multicast Tree) for building an existing multicast tree into a more energyefficient multicast tree. As a distributed algorithm, REMiT uses minimum-weight spanning tree (MST) or single-source shortest path tree (SSSPT) as the initial solution and improves the multicast tree energy efficiency by switching some tree nodes from their respective parent nodes to new correspondingparent nodes. The selection of the initial tree is dependent on the energy model.


1. Route Discovery
The first criterion in wireless medium is to discover the available routes and establish them before transmitting. To understand this better let us look at the example below. The below architecture consists of 11 nodes in which two being source and destination others will be used for data transmission. The selection of path for data transmission is done based on the availability of the nodes in the region using the ad-hoc on demand distance vector routing algorithm. By using the Ad hoc on Demand Distance Vector routing protocol, the routes are created on demand, i.e. only when a route is needed for which there is no “fresh” record in the routing table. In order to facilitate determination of the freshness of routing information, AODV maintains the time since when an entry has been last utilized. A routing table entry is “expired” after a certain predetermined threshold of time. Consider all the nodes to be in the position. Now the shortest path is to be determined by implementing the Ad hoc on Demand Distance Vector routing protocol in the wireless simulation environment for periodically sending the messages to the neighbors and the shortest path.

In the MANET, the nodes are prone to undergo change in their positions. Hence the source should be continuously tracking their positions. By implementing the AODV protocol in the simulation scenario it transmits the first part of the video through the below shown path. After few seconds the nodes move to new positions.

2. Route Maintenance
The next step is the maintenance of these routes which is equally important. The source has to continuously monitor the position of the nodes to make sure the data is being carried through the path to the destination without loss. In any case, if the position of the nodes change and the source doesn’t make a note of it then the packets will be lost and eventually have to be resent.

The modified proposed algorithm
Threshold = 50%; success = 0; cutoff = 10%
A := S;
If g(A) >= threshold then
B := A;
Let A be neighbor of B that minimizes
pc(B,A) = power-cost(B,A) + v(s)f‘(A);
Send message to A;
success = 1;
Until A = D (* Destination reached *)
or if success <> 1 then
if threshold > cutoff then
threshold = threshold /2;
or A = B ( * Delivery failed *);

3. Data Transmission
The path selection, maintenance and data transmission are consecutive process which happen in split seconds in real-time transmission. Hence the paths allocated priory is used for data transmission. The first path allocated previously is now used for data transmission. The data is transferred through the highlighted path. The second path selected is now used for data transmission. The data is transferred through the highlighted path. The third path selected is used for data transmission. The data is transferred through the highlighted path.

4. Minimum-energy multicast tree Module:

Our main objective is to construct a minimum-energy multicast tree rooted at the source node. We explore the following two problems related to energy-efficient multicasting in WANETs using a source-based multicast tree wireless multicast and the concept of wireless multicast advantage . Because the problem of constructing the optimal energy-efficient broadcast/multicast tree is NP-hard, several heuristic algorithms for building a source-based energy-efficient broadcast/multicast tree have been developed recently . Wieselthier et al. presented BIP/MIP algorithm which is a centralized source-based broadcast/ multicast tree building centralized algorithm
System Configuration
H/W System Configuration
Processor - Pentium –III

Speed - 1.1 Ghz
RAM - 256 MB(min)
Hard Disk - 20 GB
Floppy Drive - 1.44 MB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA

Software Requirements :-

Language : Java RMI, SWING,J2ME

Mobile toolkit :J2ME Wireless Toolkit 2.5.2

Development Tool: My Eclipse 3.0

O/S : WIN2000/XP

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