Building strong IDS is essential in today’s network traffic environment, feature reduction is one approach in constructing the effective IDS system by selecting the most relevant features in detecting most known and unknown attacks. In this work, proposing the hybrid feature selection method by combining Mutual Information and Linear Correlation Coefficient techniques (MI-LCC) in producing the most efficient and optimized feature subset. Support Vector Machine (SVM) classification technique being used in accurately classifying the traffic data into normal and malicious records. The proposed framework shall be evaluated with the standard benchmarked datasets including KDD-Cup-99, NSL-KDD, and UNSW-NB15 datasets. The test results, comparison analysis and reference graphs shows that the proposed feature selection model produces optimized and most important features set for classifier to achieve stated accuracy and less false positive rate compared with other similar techniques.

Space Division Multiplexing (SDM) based Elastic Optical Networks (EONs) (SDM-b-EONs) have been envisioned as a solution to both, the required upgradation of the single-mode fiber’s network capacity which is constrained by the non-linear Shannon’s limit and the capacity provisioning which will be necessitated by future diverse Internet traffic. The current SDM-b-EON designs are based on the use of Multiple Fibers (MF) technology; however, recently the Multiple Core Fiber (MCF) technology has gained momentum after laboratory experiments conducted on the MCF models established much lower inter-core crosstalk values. In the current work, we focus on the design of a MCF enabled SDM-b-EON for which, we formulate an Integer Linear Programming (ILP) model and then propose a heuristic algorithm to obtain the solutions for large sized networks in reasonable execution times. We then proceed to the performance comparison of the MCF and the MF enabled SDM-b-EON under the consideration of realistic parameters and network topologies which are characterized by different node(s) numbers and link distances. The obtained results demonstrate that the performance of the MCF enabled SDM-b-EON is very close to that of a MF enabled SDM-b-EON which implies that the network operators can benefit by utilizing the existing components for the MCFs rather than incurring any extra expense to provision the same traffic amount.

In the proposed 5G architecture where cell densification is expected to be used for network capacity enhancement, the deployment of millimetre wave (mmWave) massive multiple-input multiple-output (MIMO) in urban microcells located outdoor is expected to be used for high channel capacity small cell wireless traffic backhauling as the use of copper and optic-fibre cable becomes infeasible owing to the high cost and issues with right of way. The high cost of radio frequency (RF) chain and its prohibitive power consumption are big drawbacks for mmWave massive MIMO transceiver implementation and the complexity of using optimal detection algorithm as a result of inter-channel interference (ICI) as the base station antenna approaches large numbers. Spatial modulation (SM) and Generalized Spatial Modulation (GSM) are new novel techniques proposed as a low-complexity, low cost and low-power-consumption MIMO candidate with the ability to further reduce the RF chain for mmWave massive MIMO hybrid beamforming systems. In this work, we present the principles of generalized spatial modulation aided hybrid beamforming (GSMA-HBF) and its use for cost-effective, high energy efficient mmWave massive MIMO transceiver for small cell wireless backhaul in a 5G ultra-dense network.

This paper will present several research results evaluating the performance of ContikiMAC and XMAC protocols in data collection application with the RPL routing protocol. Simulation results show that ContikiMAC protocol gets better efficiency compared with XMAC protocol in both successful data delivery ratio and average energy consumption in the network. ContikiMAC protocol also performs well in high-density network condition. Meanwhile, successful data delivery ratio of XMAC protocol significantly reduced when the network density increases. The evaluating simulation results in this paper are an important basis for scientists to continue developing applications for wireless sensor networks in the future.