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.     

Elastomeric Fibrous Hybrid Scaffold Supports In Vitro and In Vivo Tissue Formation

Biomimetic materials with biomechanical properties resembling those of native tissues while providing an environment for cell growth and tissue formation, are vital for tissue engineering (TE). Mechanical anisotropy is an important property of native cardiovascular tissues and directly influences tissue function. This study reports fabrication of anisotropic cell‐seeded constructs while retaining control over the construct's architecture and distribution of cells. Newly synthesized poly‐4‐hydroxybutyrate (P4HB) is fabricated with a dry spinning technique to create anelastomeric fibrous scaffold that allows control of fiber diameter, porosity, and rate ofdegradation. To allow cell and tissue ingrowth, hybrid scaffolds with mesenchymalstem cells (MSCs) encapsulated in a photocrosslinkable hydrogel were developed. Culturing the cellularized scaffolds in a cyclic stretch/flexure bioreactor resulted in tissue formation and confirmed the scaffold's performance under mechanical stimulation. In vivo experiments showed that the hybrid scaffold is capable of withstanding physiological pressures when implanted as a patch in the pulmonary artery. Aligned tissue formation occurred on the scaffold luminal surface without macroscopic thrombus formation. This combination of a novel, anisotropic fibrous scaffold and a tunable native‐like hydrogel for cellular encapsulation promoted formation of 3D tissue and provides a biologically functional composite scaffold for soft‐tissue engineering applications.     

New formulation of GNSS acquisition with CFAR detection

This paper deals with the analysis of the acquisition process performed by a global navigation satellite system (GNSS) receiver with a pilot and data channel or in case of GNSS hybrid receiver. Signal acquisition decides the presence or absence of GNSS signal by comparing signal under test with a fixed threshold and provides a code delay and a Doppler frequency estimation, but in low signal conditions or in a noisy environment; acquisition systems are vulnerable and can give a high false alarm and low detection probability. Firstly, we introduce a cell‐averaging‐constant false alarm rate (CFAR) then a data‐pilot cell‐averaging‐CFAR detector fusion based to deal with these situations. In this context, we use a new mathematical derivation to develop a closed‐form analytic expressions for the probabilities of detection and false alarm. The performances of the proposed detector are evaluated and compared with a non‐CFAR case through an analytical and numerical results validated by Mont Carlo simulations. Copyright © 2016 John Wiley & Sons, Ltd.     

A computationally efficient selected mapping technique for reducing PAPR of OFDM

In orthogonal frequency division multiplexing (OFDM) system, high value of peak-to-average power ratio (PAPR) is an operational problem that may cause non-linear distortion resulting in high bit error rate. Selected mapping (SLM) is a well known technique that shows good PAPR reduction capability but inflicts added computational overhead. In this paper, using Riemann sequence based SLM method, we applied reverse searching technique to find out low PAPR yielding phase sequences with significant reduction in computational complexity. Additionally, we explored side-information free transmission that achieves higher throughput but sacrifices PAPR reduction. Finally, to overcome this loss in PAPR reduction, we proposed application of Square-rooting companding technique over the output OFDM transmitted signal. Simulation results show that the proposed method is able to compensate the sacrifice in PAPR and achieved PAPR reduction of 8.9 dB with very low computational overhead.     

Congestion detection technique for multipath routing and load balancing in WSN

In WSN, nodes collect the information from the surrounding environment and transferring to base station. Multiple data transmission in a WSN causes the nodes near the base station to get congested. Here we propose to develop a congestion avoidance and mitigation technique. For that, we select routes based on the distance between sender and receiver, relative success rate (RSR) value of node and buffer occupancy of a node. Based on these three parameters, we define a utility function to be applied to each neighbor of a transmitter node. Hence the transmitter node chooses the highest U-valued node as its next hop node among its neighbors in packet forwarding. Thus we avoid congestion by choosing non-congested nodes as its next hop node and then we mitigate congestion based on RSR values.     

Polymeric Nanoparticles as a Self-Adjuvanting Peptide Vaccine Delivery System: The Role of Shape

Antigens incorporated in subunit vaccines are typically poorly immunogenic, so a strong immunostimulant (adjuvant) and/or delivery system is required to boost immunogenicity. In this work, the various functional polymer nanostructures, that is, rods, worms, spheres, and tadpoles are used to develop potent peptide antigen delivery systems. The antigen PADRE-J8 (PJ8), derived from Group A Streptococcus (GAS) M-protein, is either physically mixed or chemically conjugated to polymeric nanoparticles of different shapes. The physical mixture of polymeric nanoparticles and antigen is more effective in inducing antibody production than their chemical conjugates. Moreover, rod-shaped polymeric nanoparticles in physical mixture with PJ8 elicited higher and more opsonic antibody titers than powerful complete Freund's adjuvant (CFA)-adjuvanted antigen. Herein, for the first time it is demonstrated that a) the block copolymer, in nanoparticle form, can act as an immune adjuvant, b) nanoparticle shape plays a crucial role in their immunogenicity, and c) antigen conjugation is not required, nor is antigen encapsulation or absorption.     

Home Automation Using Augmented Reality (HAAR)

Wireless Personal Communications - The development of Smart Home Controllers has seen rapid growth in recent years, especially for smart devices, that can utilize the Internet of Things (IoT)....     

Biometric authentication based on PCG and ECG signals: present status and future directions

Due to the great advances in biomedical digital signal processing, new biometric traits have showed noticeable improvements in authentication systems. Recently, the ElectroCardioGram (ECG) and the PhonoCardioGraph (PCG) have been proposed as novel biometrics. This paper aims to review the previous studies related to the usage of the ECG and PCG signals in human recognition. In addition, we discuss briefly the most important techniques and methodologies used by researchers in the preprocessing, feature extraction and classification of the ECG and PCG signals. At the end, we introduce some future considerations that can be applied in this topic such as: the fusion between different techniques previously used, use both ECG and PCG signals in a multimodal biometric authentication system and building a prototype system for real-time authentication.     

IBLEACH: intra-balanced LEACH protocol for wireless sensor networks

Wireless sensor networks (WSNs) are composed of many low cost, low power devices with sensing, local processing and wireless communication capabilities. Recent advances in wireless networks have led to many new protocols specifically designed for WSNs where energy awareness is an essential consideration. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. Minimizing energy dissipation and maximizing network lifetime are important issues in the design of routing protocols for WSNs. In this paper, the low-energy adaptive clustering hierarchy (LEACH) routing protocol is considered and improved. We propose a clustering routing protocol named intra-balanced LEACH (IBLEACH), which extends LEACH protocol by balancing the energy consumption in the network. The simulation results show that IBLEACH outperforms LEACH and the existing improvements of LEACH in terms of network lifetime and energy consumption minimization.     

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.