A secure search protocol for lightweight and low-cost RFID systems

In radio frequency identification (RFID) systems, search protocols are used to find a specific item in a large number of tagged products. These protocols should be secure against RFID attacks such as traceability, impersonation, DoS and eavesdropping. Sundaresan et al. (IEEE Trans Dependable Secure Comput, 2015) presented a server-less search protocol based on 128-bits PRNG function and claimed that their method can address all vulnerabilities of previous protocols. In this paper, we prove that Sundaresan et al.’s protocol is vulnerable to traceability attack with the high probability. In addition, we present an improved protocol to solve the proposed problem and analyze its security level informally and formally based on AVISPA tool and BAN logic.     

An Improvement Energy Consumption Policy Using Communication Reduction in Wireless Body Sensor Network

Dedicated short-range communications (DSRC) is an important wireless technology for current and future automotive safety and mitigation of traffic jams. In this work, we have designed a Coplanar waveguide microstrip patch antenna with linear, upper and bottom and side slots for application in DSRC. The patch antenna was designed using glass epoxy substrate (FR4). Various parametric analyses such as the current distribution, reflection coefficient, radiation pattern on E- and H-plane as well as the realized gain (dB) were performed. The results were obtained by simulation using high-frequency structure simulator tool. The proposed antenna covers a frequency band of 5.8–5.9 GHz which is highly dedicated to the DSRC wireless communication technology for enhancement of safety of the automotive transport system. The designed antenna shows a good return loss of ??19 dB at 5.9 GHz.The designed antenna shows a promising gain, return loss and radiation pattern for use in DSRC for automotive transport systems.

     

Optimal Resource Allocation in Heterogeneous MIMO Cognitive Radio Networks

The optimal resource allocation in MIMO cognitive radio networks with heterogeneous secondary users, centralized and distributed users, is investigated in this work. The core aim of this work is to study the joint problems of transmission time and power allocation in a MIMO cognitive radio scenario. The optimization objective is to maximize the total capacity of the secondary users (SUs) with the constraint of fairness. At first, the joint problems of transmission time and power allocation for centralized SUs in uplink is optimized. Afterwards, for the heterogeneous case with both the centralized and distributed secondary users, the resource allocation problem is formulated and an iterative power water-filling scheme is proposed to achieve the optimal resource allocation for both kinds of SUs. A dynamic optimal joint transmission time and power allocation scheme for heterogeneous cognitive radio networks is proposed. The simulation results illustrate the performance of the proposed scheme and its superiority over other power control schemes.     

IGBDD: Intelligent Grid Based Data Dissemination Protocol for Mobile Sink in Wireless Sensor Networks

Lifetime and energy efficiency are important factors in the design of wireless sensor network. A critical issue during data collection is the formation of energy holes near the sink. Sensors which are located near the sink have to participate in relaying data on behalf of other sensors and thus their energy will be depleted very quickly. Mobile sink movement yields the significant performance gained by decreasing the amount of energy consumption. In this paper, we propose an Intelligent Grid Based Data Disseminating protocol for mobile sink in wireless sensor networks. We have utilized a virtual grid as the protocol’s substructure. In our proposed method, cell heads (CHs) will be selected based on the locations of virtual cross points (CPs) and CPs selection is needless to transfer any required data between neighbor nodes. We have optimized CPs selection using linear programming technique in order to increase network lifetime. By selecting the CHs based on our proposed algorithm, data will be disseminated toward the sink. Our data dissemination protocol is simple and has low overhead to construct and maintain. Also, we have presented a new method for sink location update which leads to the least cost in data transfer. Simulation results illustrate that by utilizing hierarchical functionality and selecting appropriate CPs and consequently selecting CHs, energy consumption will be decreased in comparison with other presented methods which directly lead to network lifetime increment. Also by determining an optimal cell size, packet delivery rate will be improved noticeably.     

A Weighted Feature Voting Approach for Robust and Real‐Time Voice Activity Detection

This paper concerns a robust real‐time voice activity detection (VAD) approach which is easy to understand and implement. The proposed approach employs several short‐term speech/nonspeech discriminating features in a voting paradigm to achieve a reliable performance in different environments. This paper mainly focuses on the performance improvement of a recently proposed approach which uses spectral peak valley difference (SPVD) as a feature for silence detection. The main issue of this paper is to apply a set of features with SPVD to improve the VAD robustness. The proposed approach uses a weighted voting scheme in order to take the discriminative power of the employed feature set into account. The experiments show that the proposed approach is more robust than the baseline approach from different points of view, including channel distortion and threshold selection. The proposed approach is also compared with some other VAD techniques for better confirmation of its achievements. Using the proposed weighted voting approach, the average VAD performance is increased to 89.29% for 5 different noise types and 8 SNR levels. The resulting performance is 13.79% higher than the approach based only on SPVD and even 2.25% higher than the not‐weighted voting scheme.     

Joint routing and channel assignment using online learning in cognitive radio networks

Cognitive radio networks (CRNs) are the solution for the problem of underutilizing the licensed spectrum for which there are more requests in the last couple of decades. In CRNs, Secondary users (SUs) are permitted to access opportunistically the licensed spectrum owned by primary users (PUs). In this paper, we address the problem of joint routing and channel assignment for several flows generated by source SUs to a given destination. We consider a more realistic model based on Markov modulated Poisson process for modeling the PUs traffic at each channel and the SUs try to exploit short lived spectrum holes between the PUs packets at the selected channel. The SUs want to cooperatively minimize the end-to-end delay of source SUs flows meanwhile the quality of service requirements of the PUs would be met. To consider partial observation of SUs about PUs activity at all channels and quick adaptation of SUs decisions to environment changes and cooperative interaction of SUs, we use decentralized partially observable markov decision process for modeling the problem. Then, an online learning based scheme is proposed for solving the problem. Simulation results show that the performance of the proposed method and the optimal method is close to each other. Also, simulation results show that the proposed method greatly outperforms related works at control of interference to the PUs while maintains the end-to-end delay of SU flows in a low level.

     

Engineering ATM networks for congestion avoidance

With the combination of telecommunication, entertainment and computer industries, computer networking is adopting a new method called Asynchronous Transfer Mode (ATM) networking. Congestion control plays an important role in the effective and stable operation of ATM networks. Traffic management concerns with the design of a set of mechanisms which ensure that the network bandwidth, buffer and computational resources are efficiently utilized while meeting the various Quality of Service (QoS) guarantees given to sources as part of a traffic contract. In this paper, the most widely recognized congestion control schemes for ABR service are investigated. Some of these schemes show either lack of scalability or fairness while other well‐behaved schemes may require a highly complex switch algorithm that is unsuitable for implementation in cell‐switching high‐speed ATM networks. A new and improved congestion control scheme is proposed to support the best‐effort ABR traffic. This algorithm provides the congestion avoidance ability with high throughput and low delay, in addition to achieving the max–min fairness allocation. This revised version was published online in June 2006 with corrections to the Cover Date.     

Improving Voice‐Service Support in Cognitive Radio Networks

Voice service is very demanding in cognitive radio networks (CRNs). The available spectrum in a CRN for CR users varies owing to the presence of licensed users. On the other hand, voice packets are delay sensitive and can tolerate a limited amount of delay. This makes the support of voice traffic in a CRN a complicated task that can be achieved by devising necessary considerations regarding the various network functionalities. In this paper, the support of secondary voice users in a CRN is investigated. First, a novel packet scheduling scheme that can provide the required quality of service (QoS) to voice users is proposed. The proposed scheme utilizes the maximum packet transmission rate for secondary voice users by assigning each secondary user the channel with the best level of quality. Furthermore, an analytical framework developed for a performance analysis of the system, is described in which the effect of erroneous spectrum sensing on the performance of secondary voice users is also taken into account. The QoS parameters of secondary voice users, which were obtained analytically, are also detailed. The analytical results were verified through the simulation, and will provide helpful insight in supporting voice services in a CRN.     

Reduction toxicity of Amphotericin B through loading into a novel nanoformulation of anionic linear globular dendrimer for improve treatment of leishmania major

Amphotericin B (A) as an antileishmanial drug has limited clinical application owing to severe side-effects and low-water solubility. This is the first study reported using Anionic Linear Globular Dendrimer (ALGD) as A carrier for the increase of A solubility rate, decrease its toxicity, and improve its therapeutic effects. ALGD was synthesized and A was loaded into nanoparticles for the first time with the drug-loading efficiency of 82%. Drug loading was confirmed using characterization methods. The drug solubility rate was increased by 478-folds. The results of the study showed that the A toxicity was significantly decreased by 95% in vitro and in vivo environments, which was confirmed by pathology findings and enzymatic evaluation. Furthermore, the nanodrug caused that mortality rate was reached to zero. Moreover, the nanodrug was as potent as the free drug and glucantime (GUL) in reducing the parasite burden and parasite number. These findings indicated the potency of ALGD to decrease the drug side-effects, increase the drug solubility rate, and improve the drug efficacy. Moreover, the nanoformulation was a non-toxic and cost-effective formulation. The conformity between in vitro and in vivo results suggested that the A-loaded ALGD could be considered as a promising candidate in reducing the side-effects of A in leishmaniasis treatment.

Open image in new window