Integer Linear Programming with Ant-Colony Optimized Algorithm to Extend MANET Lifetime
Ben Bella S. Tawfik1, Mohamed M.A. Elgazzar2

1Ben Bella S. Tawfik, Asso. Prof., Suez Canal University – Faculty of Computers and Informatics, Egypt.
2Mohamed M.A. Elgazzar, Asso.Prof, Delta Technological University, Egypt.

Manuscript received on October 06, 2020. | Revised Manuscript received on October 25, 2020. | Manuscript published on November 30, 2020. | PP: 277-281 | Volume-9 Issue-4, November 2020. | Retrieval Number: 100.1/ijrte.D4709119420 | DOI: 10.35940/ijrte.D4709.119420
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© The Authors. 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: Network which is randomly sorted out remotely and organization that conveys without framework and experiencing low force battery is called Mobile Ad-hoc Network (MANET). Oneof the main objectives isto get thebest route from source to destination to minimize the node energy consumption. Linear Programming (Integer Linear Programming) and nature inspiration technique (Ant Colony Optimization) are two models that enhance energy consumption.The proposed models in our work are considered extension of our previous works with modified version and different measures [13]. We introduced a modified version for two models. In order to make the performance metric, two measures, namely, energy consumption and processing time are calculated.These measures aredone using as an experimental study. The First model is the enhancedLinear Programming model, the best route is selected from all possible combinatorial routes using the minimum total dissipated energy as an objective function and thefeasible region which satisfies a sequence of constraints. The second model is anenhanced ACO version, based on nature the source is the house of ant and the destination is the location of food.In this work routing selection use Ant-Colony with the Integer Linear Programming (ILP). In the research the Integer Linear Programming (ILP) is proved to be with longer lifetime compared with the ACO approach. In the meanwhile the ILP requires longer time to find the best route more than ACO approach. One of the main drawbacks of the ILP is after specific number of requests the packet losses are increasing. So, to get the best performance, the ILP is used till 500 requests then using ACO to reduce the packet losses and enhance the performance. 
Keywords: MANET, Lifetime, Ant Colony, ILP.