Abstract-In this paper, we present a framework for performance analysis of wireless MANET in combat/battle field environment. The framework uses a cross-layer design approach where four different kinds of routing protocols are compared and evaluated in the area of security operations. The resulting scenarios are then carried out in a simulation environment using NS-2 simulator. Research efforts also focus on issues such as Quality of Service (QoS), energy efficiency, and security, which already exist in the wired networks and are worsened in MANET. This paper examines the routing protocols and their newest improvements. Classification of routing protocols by source routing and hop-by-hop routing are described in detail and four major categories of state routing are elaborated and compared. We will discuss the metrics used to evaluate these protocols and highlight the essential problems in the evaluation process itself. The results would show better performance with respect to the performance parameters such as network throughput, end-to-end delay and routing overhead when compared to the network architecture which uses a standard routing protocol. Due to the nature of node distribution the performance measure of path reliability which distinguishes ad hoc networks from other types of networks in battlefield conditions, is given more significance in our research work.
Traffic congestion is defined as the state on transport which is characterized by slower speeds of vehicles this is also because of the bad condition of the roads, weather, concern zone, temperature, etc. This traffic flow prediction is mainly based on the realtime dataset which is collected with the help of various cameras and sensors. In recent day the deep learning concepts has dragged the attention for the detection of traffic flow predictions. In this paper, some of the common and familiar machine learning concepts like Deep Autoencoder (DAN), Deep Belief Network (DBN), and Random Forest (RF) are applied on the online dataset for the traffic flow predictions. The important attributes of weather, temperature, zone name, and day are used to predict the traffic flow of the particular zone. The performance of the proposed system can be evaluated by using accuracy, precision, and RMSE, and MSE value. Among the three methods, the DT technique produces a better result.
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