Exploiting the unicast functionality of the on-demand multicast routing protocol

2002 ◽  
Author(s):  
S.-J. Lee ◽  
W. Su ◽  
M. Gerla
Keyword(s):  
Routing Protocol ◽  
Multicast Routing ◽  
On Demand ◽  
Multicast Routing Protocol

scholarly journals On Demand Multicasting Routing Protocol compared with AODV and FSR in Mobile Ad hoc Network

2013 ◽  
Vol 6 (1) ◽  
pp. 705-710
Author(s):  
Kavita Kundlik Bondre ◽  
Prof. Ajitsinh.N. Jadhav
Keyword(s):  
Routing Protocol ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Multicast Routing ◽  
Mesh Networks ◽  
On Demand ◽  
Multicast Routing Protocol ◽  
Mobile Ad Hoc ◽  
Acquisition Delay

Mobile ad hoc network is a collection of wireless nodes that dynamically organize themselves to form a network without the need for any fixed infrastructure or centralized administration. The network topology dynamically changes frequently in an unpredictable manner since nodes are free to move. Support for multicasting is essential in such environment as it is considered to be an efficient way to deliver information from source nodes to many client nodes. On-Demand Multicast Routing Protocol is a protocol for routing multicast and unicast traffic throughout adhoc wireless mesh networks. ODMRP creates routes on demand so they suffer from a route acquisition delay,although it helps reduce network traffic in general. In future this  results will be compared with AODV and FSR protocol and ODMRP performs better as compared with AODV and FSR protocol.

Towards an Effective QoS On Demand Multicast Routing Protocol for Multi-Channel Multi Interface WMNs

2014 ◽  
Vol 10 (4) ◽  
pp. 1-20
Author(s):  
H. Santhi ◽  
N. Jaisankar
Keyword(s):  
Routing Protocol ◽  
Single Channel ◽  
Multicast Routing ◽  
Mesh Networks ◽  
Cost Effective ◽  
Path Selection ◽  
Wireless Internet ◽  
On Demand ◽  
Wireless Mesh ◽  
Multicast Routing Protocol

Wireless Mesh Networks (WMNs) is becoming an emerging paradigm, due to its simple and cost effective deployment, and increased growth in popularity for the next generation wireless Internet. Unlike the single channel, it is challenging to provision a robust multicasting by means of multi-channel and multi-interface WMNs. Therefore, in order to tackle the multicast issues, a high-quality path selection and channel assignment are essential. The proposed Quality of Service – On Demand Multichannel Multicast Routing Protocol (QoS- ODMMRP) includes merged path selection and top-down channel tuning mechanism to support multi-channel and multi-interface WMNs. Thus, the proposed work reduces the number of transmissions and increases the communication throughput efficiently.

scholarly journals Developing a Fuzzy Logic Based on Demand Multicast Routing Protocol

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Alireza Shams Shafigh ◽  
Kamran Abdollahi ◽  
Marjan Kouchaki
Keyword(s):  
Routing Protocol ◽  
Multicast Routing ◽  
Power Level ◽  
Poor Performance ◽  
Routing Algorithms ◽  
Control Packet ◽  
Additional Information ◽  
On Demand ◽  
Control Overhead ◽  
Multicast Routing Protocol

Multicast routing is an efficient method to lead data packets from one source group to several nodes as destination group. Although multicast routing algorithms could be efficient in many situations but their routing mechanism like as route request flooding packets likely results in poor performance in comparison to unicast routing algorithms. In this research, two efficient methods are proposed to improve the performance of On Demand Multicast Routing Protocol (ODMRP). The main proposed method tries to establish a small, efficient, and high-quality forwarding group. This is achieved by augmenting the Join Query packets with additional information such as speed, power level of node, and link bandwidths. Besides, the control overhead is further reduced by restricting the domain of control packet flooding (by restricting the domain of control packet flooding). The performance evaluation shows that the proposed scheme increases the packet delivery rate by up to 40%, while reducing average end-to-end delay and consumed power by about 35% and 45%, respectively.

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