Public Key Cryptosystem Based on Low Density Lattice Codes

McEliece and Goldreich–Goldwasser–Halevi (GGH) cryptosystems are two instances of code and lattice-based cryptosystems whose security are based on the hardness of coding theoretic and lattice problems, respectively. However, such cryptosystems have a number of drawbacks which make them inefficient in practice. On the other hand, low density lattice codes (LDLCs) are practical lattice codes which can achieve capacity over additive white Gaussian noise channel and also can be encoded and decoded efficiently. This paper introduces a public key cryptosystem based on Latin square LDLCs, by which a relationship can be attained between code and lattice-based cryptography. In this way, we can exploit the efficient properties of codes and lattices, simultaneously to improve the security and efficiency of the proposed scheme. For instance, the security of this scheme is based on the hard problems related to lattices, i.e., closest vector problem and shortest basis problem, which in turn lead to increase the security level. On the other hand, we exploit the low complexity decoding algorithm of LDLCs to reduce the computational complexity. Moreover, this property allows using the larger values of the codeword length. Also, we use the special Gaussian vector, whose variance is upper bounded by Poltyrev bound, as the perturbation (error) vector. These strategies make the proposed scheme to be secure against the conventional cryptanalytic attacks.     

A Location Privacy-Preserving Method for Spectrum Sharing in Database-Driven Cognitive Radio Networks

The great attention to cognitive radio networks (CRNs) in recent years, as a revolutionary communication paradigm that aims to solve the problem of spectrum scarcity, prompts serious investigation on security issues of these networks. One important security concern in CRNs is the preservation of users location privacy, which is under the shadow of threat, especially in database-driven CRNs. To this end, in this paper, we propose a Location Privacy Preserving Database-Driven Spectrum-Sharing \((\hbox {L-PDS}^2)\) protocol for sharing the spectrum between PUs and SUs in a database-driven CRN, while protecting location privacy of both primary and secondary users, simultaneously. We also present two specific algorithms as implementations of \(\hbox {L-PDS}^2\) protocol. Our analytical results for the privacy protection capability of \(\hbox {L-PDS}^2\) protocol prove that it provides location privacy preservation with very high probability for users of both networks. Moreover, the simulation results show that the proposed algorithms are efficient in terms of run time.     

Wide and multi-band reconfigurable Vivaldi antenna with slot-line feed

This paper presents a Vivaldi antenna. The antenna incorporates a slot-line feed, and is designed to operate in a wideband mode, along with four narrowband modes. The wideband mode extends from 1 to 3 GHz. A series of PIN diode switches is employed to reconfigure between the five different operating modes. Wideband-to-multiband reconfigurations are achieved by adjusting the antenna loading internally, and also by the incorporation of band-stop filters. To obtain the wideband mode, wideband matches load is used. On the other hand, to obtain the narrowband modes, two rectangular slits with narrowband matches load are used. The proposed Vivaldi antenna provides wideband operation. It is also supports operation within the LTE, GSM (L-band), GPS, and WiMAX bands.     

Optimal SMDP‐Based Connection Admission Control Mechanism in Cognitive Radio Sensor Networks

Traffic management is a highly beneficial mechanism for satisfying quality‐of‐service requirements and overcoming the resource scarcity problems in networks. This paper introduces an optimal connection admission control mechanism to decrease the packet loss ratio and end‐to‐end delay in cognitive radio sensor networks (CRSNs). This mechanism admits data flows based on the value of information sent by the sensor nodes, the network state, and the estimated required resources of the data flows. The number of required channels of each data flow is estimated using a proposed formula that is inspired by a graph coloring approach. The proposed admission control mechanism is formulated as a semi‐Markov decision process and a linear programming problem is derived to obtain the optimal admission control policy for obtaining the maximum reward. Simulation results demonstrate that the proposed mechanism outperforms a recently proposed admission control mechanism in CRSNs.     

All-optical 6- and 8-channel demultiplexers based on photonic crystal multilayer ring resonators in Si/C rods

In this paper, we employed multilayer ring resonators in a silicon rod base structure to realize 6-channel and 8-channel demultiplexers based on two-dimensional photonic crystals. Both the main rings and basic structures are composed of silicon rods, and the interior rings of the multilayer rings are composed of carbon. Employing silicon and carbon rods of different radii in multilayer ring resonators enhanced the coupling efficiency between the rings and waveguides. The average quality factor and power transmission efficiency were 4320 and 93%, respectively. Crosstalk values from \(-11\) to ?46 dB in conjunction with the mentioned characteristics suggest the use of the device for optical communication applications. The compact size of the proposed structure and the materials used make the proposed demultiplexer suitable for optical integrated circuits.     

Supervisory routing control for dynamic load balancing in low data rate wireless sensor networks

Routing protocols for Wireless Sensor Networks (WSN) are designed to select parent nodes so that data packets can reach their destination in a timely and efficient manner. Typically neighboring nodes with strongest connectivity are more selected as parents. This Greedy Routing approach can lead to unbalanced routing loads in the network. Consequently, the network experiences the early death of overloaded nodes causing permanent network partition. Herein, we propose a framework for load balancing of routing in WSN. In-network path tagging is used to monitor network traffic load of nodes. Based on this, nodes are identified as being relatively overloaded, balanced or underloaded. A mitigation algorithm finds suitable new parents for switching from overloaded nodes. The routing engine of the child of the overloaded node is then instructed to switch parent. A key future of the proposed framework is that it is primarily implemented at the Sink and so requires few changes to existing routing protocols. The framework was implemented in TinyOS on TelosB motes and its performance was assessed in a testbed network and in TOSSIM simulation. The algorithm increased the lifetime of the network by 41 % as recorded in the testbed experiment. The Packet Delivery Ratio was also improved from 85.97 to 99.47 %. Finally a comparative study was performed using the proposed framework with various existing routing protocols.     

Incremental augmented complex adaptive IIR algorithm for training widely linear ARMA model

In this paper, we propose a distributed adaptive learning algorithm to train the coefficients of a widely linear autoregressive moving average model by measurements collected by the nodes of a network. We assume that each node uses the augmented complex adaptive infinite impulse response (ACA-IIR) filter as the learning rule, and nodes interact with each other under an incremental mode of cooperation. To derive the proposed algorithm, called the incremental ACAIIR (IACA-IIR), we firstly formulate the distributed adaptive learning problem as an unconstrained minimization problem. Then, we apply stochastic gradient optimization argument to solve it and derive the proposed algorithm. We further find the step size range where the stability of the proposed algorithm is guaranteed. We also introduce a reduced-complexity version of the IACA-IIR algorithm. Since the proposed algorithm relies on the augmented complex statistics, it can be used to model both types of complex-valued signals (proper and improper signals). To evaluate the performance of the proposed algorithm, we use both synthetic and real-world complex signals in our simulations. The results exhibit superior performance of the proposed algorithm over the non-cooperative ACA-IIR algorithm.     

Synthesis of polybutadiene nanoparticles by emulsion polymerization: The effect of electrolyte and initiator type on particle size and reaction kinetics

Emulsion polymerization of the butadiene (Bu) was performed in the presence of disproportionate potassium rosinate (DPR) as anionic emulsifier, potassium hydroxide (KOH), and potassium carbonate (K₂CO₃) as electrolytes, and three different initiators including potassium persulfate (KPS), 2,2^′-azobisisobutyronitrile (AIBN) or 4,4′-azobis(4-cyanovaleric acid) (ACVA, also known as VAZO) at 70 °C. Latexes were prepared with a solid content of about 30 wt%. The particle size and its distribution were measured by dynamic light scattering (DLS) analysis, while the polymerization conversion was determined gravimetrically at different time intervals. Results on the emulsion polymerization of Bu in the presence of KOH and K₂CO₃ co-electrolytes showed that adding KOH to the reaction media decreases the polymerization rate. Positive effect of co-electrolytes on the control over polybutadiene latex (PBL) particles size and its distribution was also confirmed, where K₂CO₃ played roles as electrolyte and pH buffer and KOH served double roles as electrolyte and alkaline supplier of the reaction media. Complete solubility of the AIBN in Bu resulted in higher rate of polymerization in the presence of AIBN in comparison to other initiators, i.e., VAZO or KPS. The results showed that initiator type plays a significant role on the formation of PBL nanoparticles and kinetics of the polymerization. The kinetic studies revealed that emulsion polymerization of Bu follows case 1 (i.e., \(\bar{n}\) ?0.5, where \(\bar{n}\) indicates average number of the propagating chains per particle) of the Smith-Ewart kinetics.     

Mechanical and morphological study of polymer composite plates having different fiber surface treatments with particular response to high velocity projectile impact

This study investigates morphological and mechanical behaviors of polymer composite plates reinforced with surface modified glass fiber woven roving with special interest in high velocity impact response. Four types of surface modification were applied to the glass fiber surface, namely: virgin fabric (silane coupling agent removed), silane-treated (as received fabric), corona-treated virgin fabric and silane- plus corona-treated fabric. Hand layup technique was adopted to make composite plates with [0/90, ±45₂, 0/90] layup using unsaturated polyester resin as matrix. Mechanical testing methods, such as tensile and bending loading as well as low velocity Izod impact and high velocity impact tests in velocities of 88.5, 108.3 and 144 m/s were conducted. The results showed that, although in lower part of high velocity impact rates, i.e., 88.5 m/s, the panels with fiber fabric treatment of silane plus corona revealed significant increase in ballistic resistance, but in general, it was found that the order of optimum performance for E-glass fiber woven roving surface modification methods are: silane, silane plus corona treatment, virgin fabric and sole corona treatment, respectively. The results further revealed that at impact velocities of 108.3 and 144 m/s, the energy absorptions for the samples with silane treatment are 7.9 and 6.6% higher compared to the samples with silane plus corona discharge treatment (S + C) samples, respectively. Damage assessment revealed higher damage extension in the samples with fiber having silane plus corona discharge treatment. Morphological studies on surface roughness were conducted by SEM analysis. The results correlated well with mechanical and impact results in those samples with higher surface roughness showed better mechanical performance and that silane treatment was the dominant factor in performance.     

A comparative study to assess structure–properties relationships in (acrylonitrile butadiene rubber)‐based composites: Recycled microfillers versus nanofillers

This paper reports on the reinforcing effects of different types of fillers, namely, nanoclay (NC), micron size calcium carbonate (MCC), and micron size recycled powder coating waste (MPCW), on the ultimate properties of acrylonitrile butadiene rubber (NBR) compounds. The microcomposites and nanocomposites were characterized by X‐ray diffraction and scanning electron microscopy, implying enlargement of d‐spacing of NC or intercalation of NBR chains and formation of exfoliated structure, while some agglomerates of MCC were detected. Curing characteristics of the studied composites showed that incorporation of the fillers into the NBR, in particular the NC, causes an increase in the torque, indicating a higher degree of crosslinking. Furthermore, different from micron size MPCW and MCC, the NC accelerated the vulcanization reaction. It was also found that the use of NC and MPCW results in a remarkable increase in the mechanical and rheological properties compared with pure NBR. All in all, variations in the aforementioned criteria were attributable to the extent of matrix/filler interaction reflected by scanning electron micrographs. The correlation established between the microstructure and characteristics of the prepared NBR composites can shed some light on how to develop composites with enhanced properties by incorporating waste materials into the polymers. J. VINYL ADDIT. TECHNOL., 23:13–20, 2017. © 2015 Society of Plastics Engineers