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Research in Named Data Networking-based Mobile Ad hoc Network (NDN based MANET) experienced a lot of momentum and development in recent years. Such robust developments in the specific area surely contributes to advanced possibilities that Named Data Networking (NDN) can provide compared to traditional host centric networking solutions such as TCP/IP for dynamic routing that is much needed for MANET environment. Based on our observations, most existing work of NDN based MANET studies chose to use full wireless broadcast approach method for dynamic content routing as their solution in MANET environment. This review is carried out by analyzing how energy conservation of dynamic content routing was conducted in previous studies that has employed various methods of wireless broadcast smart control that are totally different from one another. We then discuss the disadvantages of the suggested solution from previous studies and scrutinizes it from the aspects of energy conservation of content routing in NDN based MANET point of view. Following that, we proceed to suggest on how dynamic content routing should have been done in order to achieve beneficial energy efficiency improvements of content routing mechanism in NDN based MANET. Following that, we suggest how dynamic content routing mechanisms for energy conservation can be improved in NDN based MANET. At the same time, we show the differences between our suggested solution and existing solution as a proposal towards the creation of next generation of content routing solution for NDN based MANET implementation.

In this article; Intelligent Water Drops (IWD) algorithm is adapted for feature selection with Rough Set (RS). Specifically, IWD is used to search for a subset of features based on RS dependency as an evaluation function. The resulting system, called IWDRSFS (Intelligent Water Drops for Rough Set Feature Selection), is evaluated with six benchmark data sets. The performance of IWDRSFS are analysed and compared with those from other methods in the literature. The outcomes indicate that IWDRSFS is able to provide competitive and comparable results. In summary, this study shows that IWD is a useful method for undertaking feature selection problems with RS.

The effect of the parameter values in GA is undeniable. Different working operators as well as different values for the parameters would result in different efficiency and performance for a given problem. The effect of parameters on exploration and exploitation is the main effective factor in GAs. Keeping a balance between the exploration and exploitation during the run would lead to good results. Different parameter has different role in keeping this balance. An adaptive parameter control is proposed. A weight is given to each parameter depend on its power in exploration. The parameters then will be ordered based on their explorative power. A comparison has been made among different orders of the parameters. The results suggest the most suitable parameters in exploration and exploitation in the process of evolution. The results have shown the selection pressure as the most explorative parameter and then mutation and crossover rates has the most effect on exploration.