Multidimensional vector radix FHT algorithms

In this paper, efficient multidimensional (M-D) vector radix (VR) decimation-in-frequency and decimation-in-time fast Hartley transform (FHT) algorithms are derived for computing the discrete Hartley transform (DHT) of any dimension using an appropriate index mapping and the Kronecker product. The proposed algorithms are more effective and highly suitable for hardware and software implementations compared to all existing M-D FHT algorithms that are derived for the computation of the DHT of any dimension. The butterflies of the proposed algorithms are based on simple closed-form expressions that allow easy implementations of these algorithms for any dimension. In addition, the proposed algorithms possess properties such as high regularity, simplicity and in-place computation that are highly desirable for software and hardware implementations, especially for the M-D applications. A close relationship between the M-D VR complex-valued fast Fourier transform algorithms and the proposed M-D VR FHT algorithms is established. This type of relationship is of great significance for software and hardware implementations of the algorithms, since it is shown that because of this relationship and the fact that the DHT is an alternative to the discrete Fourier transform (DFT) for real data, a single module with a little or no modification can be used to carry out the forward and inverse M-D DFTs for real- or complex-valued data and M-D DHTs. Thus, the same module (with a little or no modification) can be used to cover all domains of applications that involve the DFTs or DHTs.     

Queue length‐based load balancing in data center networks

Traffic load balancing in data centers is an important requirement. Traffic dynamics and possibilities of changes in the topology (e.g., failures and asymmetries) make load balancing a challenging task. Existing end‐host–based schemes either employ the predominantly used ECN or combine it with RTT to get congestion information of paths. Both congestion signals, ECN and RTT, have limitations; ECN only tells whether the queue length is above or below a threshold value but does not inform about the extent of congestion; similarly, RTT in data center networks is on the scale of up to few hundreds of microseconds, and current data center operating systems lack fine‐grained microsecond‐level timers. Therefore, there is a need of a new congestion signal which should give accurate information of congestion along the path. Furthermore, in end‐host–based schemes, detecting asymmetries in the topology is challenging due to the inability to accurately measure RTT on the scale of microseconds. This paper presents QLLB, an end‐host–based, queue length–based load balancing scheme. QLLB employs a new queue length–based congestion signal that gives an exact measure of congestion along the paths. Furthermore, QLLB uses relative‐RTT to detect asymmetries in the topology. QLLB is implemented in ns‐3 and compared with ECMP, CONGA, and Hermes. The results show that QLLB significantly improves performance of short flows over the other schemes and performs within acceptable level, of CONGA and Hermes, for long flows. In addition, QLLB effectively detects asymmetric paths and performs better than Hermes under high loads.     

SCM: Secure and accountable TLS certificate management

In classical public‐key infrastructure (PKI), the certificate authorities (CAs) are fully trusted, and the security of the PKI relies on the trustworthiness of the CAs. However, recent failures and compromises of CAs showed that if a CA is corrupted, fake certificates may be issued, and the security of clients will be at risk. As emerging solutions, blockchain‐ and log‐based PKI proposals potentially solved the shortcomings of the PKI, in particular, eliminating the weakest link security and providing a rapid remedy to CAs' problems. Nevertheless, log‐based PKIs are still exposed to split‐world attacks if the attacker is capable of presenting two distinct signed versions of the log to the targeted victim(s), while the blockchain‐based PKIs have scaling and high‐cost issues to be overcome. To address these problems, this paper presents a secure and accountable transport layer security (TLS) certificate management (SCM), which is a next‐generation PKI framework. It combines the two emerging architectures, introducing novel mechanisms, and makes CAs and log servers accountable to domain owners. In SCM, CA‐signed domain certificates are stored in log servers, while the management of CAs and log servers is handed over to a group of domain owners, which is conducted on the blockchain platform. Different from existing blockchain‐based PKI proposals, SCM decreases the storage cost of blockchain from several hundreds of GB to only hundreds of megabytes. Finally, we analyze the security and performance of SCM and compare SCM with previous blockchain‐ and log‐based PKI schemes.     

Inter-cell interference in multi-tier heterogeneous cellular networks: modeling and constraints

Telecommunication Systems - Interference is the main source of capacity limitation in wireless networks. In some medium access technologies in cellular networks, such as OFDMA, the allocation of...     

Modeling and Simulation for Transient Thermal Analyses Using a Voltage-in-Current Latency Insertion Method

This article presents a modeling and simulation method for transient thermal analyses of integrated circuits(ICs) using the original and voltage-in-current(VinC) latency insertion method(LIM). LIM-based algorithms are a set of fast transient simulation methods that solve electrical circuits in a leapfrog updating manner without relying on large matrix operations used in conventional Simulation Program with Integrated Circuit Emphasis(SPICE)-based methods which can significantly slow down the sol...     

Improved aquila optimization-based parameter evaluation framework and meta-heuristic algorithm in radio-over-fiber SpatialMux multi-input multi-output long-term evolution system

In heterogeneous access network, Multiple-Input Multiple-Output (MIMO) radio-over-fiber (RoF) system is an efficient approach for multiple signal transmission with low cost and complexity. The performance of RoF fronthaul system in MIMO system will be varied with different nonlinear effects. By adjusting various transmission parameters, such as the input signal power or the laser bias current, the nonlinear impacts produced by the RoF system can be reduced. In this paper, a novel algorithm Improved Aquila Optimization (IAO) is proposed to optimize transmission circumstances of MIMO RoF system. It determines the appropriate bias current for both lasers and Radio Frequency (RF) signal power in a short period. The input signals are wavelength multiplexed with Intensity Modulation and Direct Detection (IM/DD) applied. The carrier as well as transmission frequency is governed by the MIMO-Long-Term Evolution (LTE) standard. The proposed system is implemented in MATLAB, and the performance is evaluated. The experimental results show that fast convergence and trade-off between noise and nonlinearity are obtained with varying bandwidth. In the experimental scenario, the maximum Error Vector Magnitude (EVM) of 1.88, 3.14, and signal-to-noise ratio (SNR) of 3.204, and 2.698 was attained for both quadrature phase shift keying (QPSK) and quadrature amplitude modulation (QAM) modulation. [Correction added on 24 April 2023, after first online publication: the SNR values were corrected in the preceding sentence.] For 100 iterations, the processing time was reduced to 0.137 s. When compared with the conventional state-of-the-art approaches, the accuracy and computational complexity of the proposed approach are improved.     

Investigation of directly suspended droplet micro extraction method for extraction of trihalomethane and halomethane in water samples

Simple and efficient directly suspended droplet micro extraction (DSDME) in conjunction with gas chromatography-electron capture detector (GC-ECD) has been developed for extraction and determination of Halomethane and Trihalomethane from water samples. In this technique a micro drop of n-hexane is delivered to the surface of an aqueous sample while being agitated by a stirring bar in the bulk of solution. Factors relevant to the extraction efficiency were studied and optimized. The optimized extraction conditions were extraction solvent: n- hexane; NaCl concentration: 1 M; solvent extraction volume: 50 μL; stirring rate: 720 rpm and the extraction time: 5 min. The detection limits of the method were in the range of 0.059–0.137 µg L^?1, relative standard deviation (n = 3) range were 0.019–0.048%. A good linearity (r² ≥ 0.997) and a relatively broad dynamic linear range (10–200 µg L^?1) were obtained and recoveries of method were in the range of 97.69–99.51%. Finally, the proposed method was successfully utilized for pre concentration and determination of halo methane in different real samples. Successfully DSDME technique combined with capillary GC-ECD for the analysis of THMs and HMs in the water investigated samples.     

Software‐defined networking approach for enhanced evolved packet core network

The evolved packet core (EPC) network is the mobile network standardized by the 3rd Generation Partnership Project and represents the recent evolution of mobile networks providing high‐speed data rates and on‐demand connectivity services. Software‐defined networking (SDN) is recently gaining momentum in network research as a new generation networking technique. An SDN‐based EPC is expected to introduce gains to the EPC control plane architecture in terms of simplified, and perhaps even software‐based, vendor independent infrastructure nodes. In this paper, we propose a novel SDN‐based EPC architecture along with the protocol‐level detailed implementation and provide a mechanism for identifying information fields exchanged between SDN‐EPC entities that maintains correct functionality with minimal impact on the conventional design. Furthermore, we present the first comprehensive network performance evaluation for the SDN‐based EPC versus the conventional EPC and provide a comparative analysis of 2 networks performances identifying potential bottlenecks and performance issues. The evaluation focuses on 2 network control operations, namely, the S1‐handover and registration operations, taking into account several factors, and assessing performance metrics such as end‐to‐end delay (E2ED) for completion of the respective control operation, and EPC nodes utilization figures.     

A Channel Borrowing Approach for Cluster-based Hierarchical Wireless Sensor Networks

Mobile Networks and Applications - In Wireless Sensor Networks (WSNs), energy-efficient routing is required to conserve the scarce resources of these networks. Various energy-efficient routing...