Efficient Data Delivery Over MANET’s through Secured EGMP
Group communications are important in Mobile Ad hoc Networks (MANET). Multicast is an efficient method for implementing group communications. However, it is challenging to implement efficient and scalable multicast in MANET due to the difficulty in group membership management and multicast packet forwarding over a dynamic topology. We propose a Secured novel Efficient Geographic Multicast Protocol (EGMP). EGMP uses a virtual-zone-based structure to implement scalable and efficient group membership management. A network-wide zone-based bi-directional tree is constructed to achieve more efficient membership management and multicast delivery. The position information is used to guide the zone structure building, multicast tree construction and multicast packet forwarding, which efficiently reduces the overhead for route searching and tree structure maintenance. Several strategies have been proposed to further improve the efficiency of the protocol, for example, introducing the concept of zone depth for building an optimal tree structure and integrating the location search of group members with the hierarchical group membership management. To handle empty zone problem faced by most routing protocols using a zone structure. we design a scheme to handle security problem faced by multicasting. Finally, we design to maintain the data in the buffer of the zone leader to send the data to the crashed node. So due to this data ca efficiently reached to destination. The scalability and the efficiency of EGMP are evaluated through simulations and quantitative analysis. Our results demonstrate that EGMP has high packet delivery ratio, and low control overhead and multicast group joining delay under all test scenarios, and is scalable to both group size and network size. Compared to Scalable Position-Based Multicast (SPBM) , EGMP has significantly lower control overhead, data transmission overhead, and multicast group joining delay.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.
AASS©: World Science Publisher United States