An Improved Ant Colony Otimization (IACO) Based Multicasting in MANET
Deepender Dhull1, Swati Dhull2
1Deepender Dhull, Computer Science Department, International Institute of Technology & Management, Sonipat, India.
2Swati Dhull, Electronics & Communication Department, BMIET, Sonipat, India.
Manuscript received on February 08, 2013. | Revised Manuscript Received on February 22, 2013. | Manuscript published on February 20, 2013. | PP: 8-12 | Volume-1 Issue-3, February 2013. | Retrieval Number: D0142021413/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A Mobile Ad hoc Network (MANET) is one of the challenging environments for multicast. Since the associated overhead is more, the existing studies illustrate that tree-based and mesh-based on-demand protocols are not the best choice. The costs of the tree under multiple constraints are reduced by the several algorithms which are based on the Ant Colony Optimization (ACO) approach. The traffic-engineering multicast problem is treated as a single-purpose problem with several constraints with the help of these algorithms. The main disadvantage of this approach is the need of a predefined upper bound that can isolate good trees from the final solution. In order to solve the traffic engineering multicast problem which optimizes many objectives simultaneously this study offers a design on Ant Based Multicast Routing (AMR) algorithm for multicast routing in mobile ad hoc networks. Apart from the existing constraints such as distance, delay and bandwidth, the algorithm calculates one more additional constraint in the cost metric which is the product of average-delay and the maximum depth of the multicast tree. Moreover it also attempts to reduce the combined cost metric. By reducing the number of group members that participate in the construction of the multicast structure and by providing robustness to mobility by performing broadcasts in densely clustered local regions, the proposed protocol achieves packet delivery statistics that are comparable to that with a pure multicast protocol but with significantly lower overheads. By this protocol we achieve increased Packet Delivery Fraction (PDF) with reduced overhead and routing load. By simulation results, it is clear that our proposed algorithm surpasses all the previous algorithms by developing multicast trees with different sizes.
Keywords: ACO, AMR, APPMULTICAST, MANET