Application of local error method to SSSF simulation of vector propagation in dispersion compensated optical links

A local error method based on an analytical scheme previously developed for the scalar optical fiber channel is applied to the second-order symmetrized split-step Fourier simulation of polarization multiplexed signal propagation through dispersion compensated optical fiber links. It is found that the global simulation accuracy for the vector propagation can be satisfied using the local error bound from a scalar propagation model for the same global error over a large range of simulation accuracy, chromatic dispersion, and differential group delay. Furthermore, carefully designed numerical simulations are used to show that similar local simulation error are obtained for vector simulations and that the similar local error leads to higher computational efficiency compared to other prevalent step-size selection schemes. The scaling of the global simulation error with respect to the number of optical fiber spans is demonstrated, and global error control for multi-span simulations is proposed. Combining the local error and global error control, the developed simulation scheme can significantly speed up the time-consuming simulations in coherent optical fiber communication system analysis and design.     

An adaptive and efficient buffer management scheme for resource-constrained delay tolerant networks

Provisioning buffer management mechanism is especially crucial in resource-constrained delay tolerant networks (DTNs) as maximum data delivery ratio with minimum overhead is expected in highly congested environments. However, most DTN protocols do not consider resource limitations (e.g., buffer, bandwidth) and hence, results in performance degradation. To strangle and mitigate the impact of frequent buffer overflows, this paper presents an adaptive and efficient buffer management scheme called size-aware drop (SAD) that strives to improve buffer utilization and avoid unnecessary message drops. To improve data delivery ratio, SAD exactly determines the requirement based on differential of newly arrived message(s) and available space. To vacate inevitable space from a congested buffer, SAD strives to avoid redundant message drops and deliberate to pick and discard most appropriate message(s) to minimize overhead. The performance of SAD is validated through extensive simulations in realistic environments (i.e., resource-constrained and congested) with different mobility models (i.e., Random Waypoint and disaster). Simulation results demonstrate the performance supremacy of SAD in terms of delivery probability and overhead ratio besides other metrics when compared to contemporary schemes based on Epidemic (DOA and DLA) and PRoPHET (SHLI and MOFO).     

Highly Efficient and Water‐Insensitive Self‐Healing Elastomer for Wet and Underwater Electronics

Integrating self‐healing capabilities into soft electronic devices increases their durability and long‐term reliability. Although some advances have been made, the use of self‐healing electronics in wet and/or (under)water environments has proven to be quite challenging, and has not yet been fully realized. Herein, a new highly water insensitive self‐healing elastomer with high stretchability and mechanical strength that can reach 1100% and ≈6.5 MPa, respectively, is reported. The elastomer exhibits a high (>80%) self‐healing efficiency (after ≈ 24 h) in high humidity and/or different (under)water conditions without the assistance of an external physical and/or chemical triggers. Soft electronic devices made from this elastomer are shown to be highly robust and able to recover their electrical properties after damages in both ambient and aqueous conditions. Moreover, once operated in extreme wet or underwater conditions (e.g., salty sea water), the self‐healing capability leads to the elimination of significant electrical leakage that would be caused by structural damages. This highly efficient self‐healing elastomer can help extend the use of soft electronics outside of the laboratory and allow a wide variety of wet and submarine applications.     

Adaptive Modulation and Coding with Selective Retransmission under OFDM signaling

In this paper, we present bandwidth efficient selective retransmission method in conjunction with adaptive modulation and coding (AMC) scheme for OFDM waveform. In the proposed method, when a packet failure occurs, receiver requests retransmission of information symbols prone to error corresponding to the low signal-to-noise ratio (SNR) sub-carriers of OFDM modulation. The selective retransmission avoids unnecessary retransmission and AMC chooses a proper modulation and coding scheme with an objective to maximize the throughput. Our method achieves higher throughput as compared to conventional retransmission methods such as Chase combining hybrid automatic repeat reQuest (CC-HARQ) and incremental redundancy hybrid automatic repeat reQuest (IR-HARQ). We also provide the throughput and delay analysis of the proposed method for non-truncated ARQ. The simulation results demonstrate throughput gain without significant impact on delay as compared to the conventional retransmission approaches.     

Compact and High Speed Architectures of KASUMI Block Cipher

Wireless Personal Communications - This paper proposes highly compact and high speed hardware architectures of 64-bit KASUMI block cipher for wide range of wireless applications. A novel...     

A load-aware energy-efficient and throughput-maximized asynchronous duty cycle MAC for wireless sensor networks

Being a pivotal resource, conservation of energy has been considered as the most striking issue in the wireless sensor network research. Several works have been performed in the last years to devise duty cycle based MAC protocols which optimize energy conservation emphasizing low traffic load scenario. In contrast, considering the high traffic situation, another research trend has been continuing to optimize both energy efficiency and channel utilization employing rate and congestion control at the MAC layer. In this paper, we propose A Load-aware Energy-efficient and Throughput-maximized Asynchronous Duty Cycle MAC (LET-MAC) protocol for wireless sensor networks to provide an integrated solution at the MAC layer considering both the low-and high-traffic scenario. Through extensive simulation using ns-2, we have evaluated the performance of LET-MAC. LET-MAC achieves significant energy conservation during low traffic load (i.e., no event), compared to the prior asynchronous protocol, RI-MAC, as well as attains optimal throughput through maximizing the channel utilization and maintains lower delay in regard to the CSMA/CA-like protocol during a high volume of traffic (i.e., when an event occurs).     

On accounting for screen resolution in adaptive video streaming: QoE-driven bandwidth sharing framework

Screen resolution along with network conditions are main objective factors impacting the user experience, in particular for video streaming applications. User terminals on their side feature more and more advanced characteristics resulting in different network requirements for good visual experience. Previous studies tried to link mean opinion score (MOS) to video bitrate for different screen types (e.g., Common Intermediate Format [CIF], Quarter Common Intermediate Format [QCIF], and High Definition [HD]). We leverage such studies and formulate a Quality of Experience (QoE)-driven resource allocation problem to pinpoint the optimal bandwidth allocation that maximizes the QoE over all users of a network service provider located behind the same bottleneck link, while accounting for the characteristics of the screens they use for video playout. For our optimization problem, QoE functions are built using curve fitting on datasets capturing the relationship between MOS, screen characteristics, and bandwidth requirements. We propose a simple heuristic based on Lagrangian relaxation and Karush Kuhn Tucker (KKT) conditions to efficiently solve the optimization problem. Our numerical simulations show that the proposed heuristic is able to increase overall QoE up to 20% compared to an allocation with a TCP look-alike strategy implementing max-min fairness.     

Gas Sensing of NiO‐SCCNT Core–Shell Heterostructures: Optimization by Radial Modulation of the Hole‐Accumulation Layer

Hierarchical core–shell (C–S) heterostructures composed of a NiO shell deposited onto stacked‐cup carbon nanotubes (SCCNTs) are synthesized by atomic layer deposition (ALD). A film of NiO particles (0.80–21.8 nm in thickness) is uniformly deposited onto the inner and outer walls of the SCCNTs. The electrical resistance of the samples is found to increase of many orders of magnitude with the increasing of the NiO thickness. The response of NiO–SCCNT sensors toward low concentrations of acetone and ethanol at 200 °C is studied. The sensing mechanism is based on the modulation of the hole‐accumulation region in the NiO shell layer upon chemisorption of the reducing gas molecules. The electrical conduction mechanism is further studied by the incorporation of an Al₂O₃ dielectric layer at NiO and SCCNT interfaces. The investigations on NiO–Al₂O₃–SCCNT, Al₂O₃–SCCNT, and NiO–SCCNT coaxial heterostructures reveal that the sensing mechanism is strictly related to the NiO shell layer. The remarkable performance of the NiO–SCCNT sensors toward acetone and ethanol benefits from the conformal coating by ALD, large surface area of the SCCNTs, and the optimized p‐NiO shell layer thickness followed by the radial modulation of the space‐charge region.     

Complexity reduction of digital filters using shift inclusive differential coefficients

We present a graph theoretical methodology that reduces the implementation complexity of the multiplication of a constant vector and a scalar. The complexity of implementation is defined as the required amount of computations like additions. The proposed approach is called minimally redundant parallel (MRP) optimization and is mainly presented in a finite impulse response (FIR) filtering framework to obtain a low-complexity multiplierless implementation. The key idea is to expand the design space using shift inclusive differential coefficients (SIDCs) together with computation reordering using a graph theoretic approach to obtain maximal computation sharing. The problem is formulated using a graph in which vertices and edges represent coefficients and computational cost (number of resources). The multiplierless solution is obtained by solving a set cover problem on the vertices in the graph. A simple polynomial run time algorithm based on a greedy approach is presented. The proposed approach is compared with common-subexpression elimination to show slightly better results and is combined with it for further reduction of complexity. Simulation results show that 50-60% complexity reduction is achieved by only applying the MRP algorithm, and 70% complexity reduction is obtainable by combining it with common-subexpression elimination under a delay constraint of two or three.     

A noise constrained least mean fourth (NCLMF) adaptive algorithm

The learning speed of an adaptive algorithm can be improved by properly constraining the cost function of the adaptive algorithm. In this work, a noise-constrained least mean fourth (NCLMF) adaptive algorithm is proposed. The NCLMF algorithm is obtained by constraining the cost function of the standard LMF algorithm to the fourth-order moment of the additive noise. The NCLMF algorithm can be seen as a variable step-size LMF algorithm. The main aim of this work is to derive the NCLMF adaptive algorithm, analyze its convergence behavior, and assess its performance in different noise environments. Furthermore, the analysis of the proposed NCLMF algorithm is carried out using the concept of energy conservation. Finally, a number of simulation results are carried out to corroborate the theoretical findings, and as expected, improved performance is obtained through the use of this technique over the traditional LMF algorithm.