In wireless ad-hoc network energy of node is very important issue. Less amount of energy is directly affect the lifetime of network because all nodes in networks are battery operated devices. So optimization of energy consumption in network has greater impact on network life. The power consumption can be reduced at node level, transmission and receiving level. This paper is focusing on how various propagation models affect the energy consumption in ad-hoc network with MANET routing protocols. The four widely used Ad-hoc routing protocols compared are: Ad-hoc on demand Distance Vector (AODV), Destination Sequenced Distance Vector (DSDV), Dynamic Source Routing (DSR), and Ad-hoc on demand Multipath Distance Vector (AOMDV). Simulation has been carried out using Network Simulator 2.34 and its associated tools like Network Animator.
An intrusion detection systems (IDS) detect and prevent network attacks. Due to the complicated network environment, the ID system merges a high number of samples into a small number of normal samples, resulting in inadequate samples to identify and train and a maximum false detection rate. External malicious attacks damage conventional IDS, which affects network activity. Adaptive Dolphin Atom Search Optimization overcomes this. Thus, the work aims to create an adaptive optimization-based network intrusion detection system that modifies the classifier for accurate prediction. The model selects feature and detects intrusions. Mutual information selects feature for further processing in the feature selection module. Deep RNNs detect intrusions. The novel Adaptive Dolphin Atom Search Optimization technique trains the deep RNN. Adaptive DASO combines the DASO algorithm with adaptive concepts. The DASO is the integration of the dolphin echolocation (DE) with the atom search optimization (ASO). Thus, the intrusions are detected using the adaptive DASO-based deep RNN. The developed adaptive DASO approach attains better detection performance based on several parameters such as specificity, accuracy, and sensitivity.
Dedicated Short Range Communication (DSRC) band is incapable to remove increasing demand on wireless traffic in vehicular network. The TV white Space band by FCC for cognitive access provides additional bandwidth to solve the DCRS spectrum problem. However, create a challenging environment for portable (e.g., vehicular) and fixed (e.g., IEEE 802.22) network which is FCC required portable device to use significantly lower transmitting power than fixed device. In this paper, first formulate the Mixed-Integer Non Linear Programming (MINLP) program, to which three algorithms are refined. The first algorithm converts the MINLP to a convex problem and gives the near-optimal solution to the initial MINLP. The other two algorithms, first convert the MINLP into an Integer Programming (IP) problem. Then, solve the linear program relaxation of the IP and obtain fractional solution. Consequently, two rounding algorithms are developed to round the fractional solution based on the column-sparse packing and dependent rounding techniques. In conclusion, compare the performance of the proposed algorithms with the optimal MINLP solver.
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