Efficient Route Selection Scheme in MANET Using Enhanced AODV Protocol

Mobile Ad Hoc network comprises of mobile nodes communicating over wireless medium. Due to ease of communication and flexibility, MANET has become an active area of research in wireless communication. However, issues such as limited battery capacity, dynamic topology and node mobility cause frequent link breakage due to which reroute discovery process is required to be initiated resulting in increase in latency and routing overheads. Many research works have been carried out for improvement of an existing routing scheme, however they do not scale-up well to provide stable and energy efficient route. This paper introduces a novel routing algorithm ENH-AODV (Enhanced AODV) that focuses on selection of an efficient route on the basis of quality of both links and nodes impending during route discovery process. In addition, each node maintains a list, consisting of details of nearby nodes with good energy level through hello mechanism. Simulation is carried out over network simulator and results prove that the proposed scheme is more effective and advantageous than AODV in terms of normalized routing load, end to end delay, packet delivery ratio and throughput.

     

Decision Tree-Based Entries Reduction scheme using multi-match attributes to prevent flow table overflow in SDN environment

The software-defined networking is used extensively in data centers that provide centralized control for the widely deployed networking resources. The traffic is shaped by rules created by the controller dynamically without modifying the individual switch. The key component that stores rules which are used to process the flows is the flow table which resides in the ternary content addressable memory. The current commercial OpenFlow appliances accommodate limited entries up to 8000 due to its high cost and high power consumption. There are two issues to be considered, where (1) flow table's inability to provide rules during flow table overflow leads to dropping of incoming packets and (2) the significant amount of rule replacement occurs when the traffic in data centers increases which creates massive route requests to controller creating overhead. The proposed scheme prevents flow table overflow using the robust machine learning algorithm called decision tree (Iterative Dichotomiser 3) that allows the flow table to learn its high prioritized fine-grained entries by means of multiple matching attributes. The entries are classified, and the usual eviction process is replaced by pushing the low important entries into counting bloom filter which acts as a cache to prevent flow entry miss. The simulations were carried out using real-time network traffic datasets, and the comparisons with the various existing schemes prove that the proposed approach reduces 99.99% of the controller's overhead and the entries are minimized to 99% providing extra space for new flows.     

Insider attack mitigation in a smart metering infrastructure using reputation score and blockchain technology

International Journal of Information Security - The increasing use of smart metering infrastructure invites security threats through trusted insiders in spite of the devices’ authentication...     

Current Technology of Supercapacitors: A Review

A supercapacitor is a solid-state device that can store electrical energy in the form of charges. It represents an advancement in the field of energy storage, as it overcomes many of the shortcomings of batteries. This paper presents an overview of the various types of supercapacitors, electrode materials, and electrolytes, and the future of supercapacitors. Due to their high storage capacity, supercapacitors are commonly used in portable electronic devices such as MP3 players and mobile phones, and in hybrid vehicles and other applications. In electrical and hybrid vehicles, supercapacitors are increasingly used as provisional energy storage for regenerative braking. Various materials are used in electrodes to boost the performance of the supercapacitor. This review presents details regarding the materials and electrolyte, and the improvements in the field of supercapacitors.     

Inhibitory effect of TiO2 NPs on symbiotic arbuscular mycorrhizal fungi in plant roots

While nanoparticles (NPs) are known to exhibit antimicrobial properties, their effects on symbiotic arbuscular mycorrhizal fungi (AMF) in plant roots has to be carefully examined as NPs particularly of titanium dioxide (TiO₂) reach plant roots through varied sources such as fertilisers, plant protection products and other nanoproducts. The objective of the present study is to assess the effect of TiO₂ NPs on the symbiotic behaviour of AMF colonising rice (Oryza sativa L.) plants. Using sol–gel method, TiO₂ NPs with three different sizes were successfully synthesised employing doping. Characterisation of the prepared material was done by X‐ray powder diffraction and scanning electron microscopy. The synthesised materials were applied at 0, 25, 50 and 100 mg plant–1 to the rhizosphere of mycorrhizal rice plants maintained in pots. The study revealed that the prepared NPs had an inhibitory effect on arbuscular mycorrhizal symbiosis in plant roots. Development of AMF structures such as vesicles and arbuscules was significantly reduced in TiO₂ ‐doped NPs with a relatively more inhibition in 2% TiO₂ ‐doped NPs. Among the concentrations of TiO₂ NPs applied to different treatments, %F was significantly (P < 0.001) affected at medium to higher levels of application.Inspec keywords: nanoparticles, titanium compounds, antibacterial activity, sol‐gel processing, X‐ray diffraction, scanning electron microscopy, microorganisms, cellular biophysics, nanomedicineOther keywords: symbiotic arbuscular mycorrhizal fungi, plant roots, nanoparticles, antimicrobial properties, fertilisers, plant protection, nanoproducts, AMF colonising rice, sol‐gel method, X‐ray powder diffraction, scanning electron microscopy, mycorrhizal rice plants, rhizosphere, arbuscular mycorrhizal symbiosis, soil biota, TiO₂      

Wireless sensor networks: a survey on recent developments and potential synergies

Wireless sensor network (WSN) has emerged as one of the most promising technologies for the future. This has been enabled by advances in technology and availability of small, inexpensive, and smart sensors resulting in cost effective and easily deployable WSNs. However, researchers must address a variety of challenges to facilitate the widespread deployment of WSN technology in real-world domains. In this survey, we give an overview of wireless sensor networks and their application domains including the challenges that should be addressed in order to push the technology further. Then we review the recent technologies and testbeds for WSNs. Finally, we identify several open research issues that need to be investigated in future. Our survey is different from existing surveys in that we focus on recent developments in wireless sensor network technologies. We review the leading research projects, standards and technologies, and platforms. Moreover, we highlight a recent phenomenon in WSN research that is to explore synergy between sensor networks and other technologies and explain how this can help sensor networks achieve their full potential. This paper intends to help new researchers entering the domain of WSNs by providing a comprehensive survey on recent developments.     

Understanding the pathogenesis of endometriosis through proteomics: Recent advances and future prospects

Endometriosis is a complex gynecological disease, characterized by the presence and growth of endometrial tissue outside the uterus, resulting in pelvic pain and infertility. It occurs in 10% of women in their reproductive age. The viable endometrial cells enter the peritoneal cavity by retrograde menstruation, implant, and cause lesions ectopically; depending on their ability to survive, attach, grow, and invade. These “normal” endometrial cells turn “endometriotic” apparently because of inherent abnormalities present in them. Information on these molecular abnormalities is now being sought through proteomic approaches. Recent proteome-based comparisons between the eutopic endometrium from normal women and patients with endometriosis have revealed several proteins (many of which are shown to have a role in several cancers), of which a few have been validated as potential players in the etiology of endometriosis. After an initial in-flow of information from these proteome studies of eutopic endometrium, focus now needs to be expanded to the changes in the various protein PTMs and their upstream effectors present in these tissues. Early diagnosis of endometriosis through noninvasive means is the need of the hour as well—which would require the use of the presently existing immunoassays, along with the advancing MS-based proteomics. In this review, we aim to discuss these future thrust areas of human endometriosis proteomics and also present the proteomic advances made so far in understanding the molecular basis of endometriosis.     

Structural characterization of carboxyl cellulose nanofibers extracted from underutilized sources

Two different chemical methods, TEMPO-oxidation and nitro-oxidation, were used to extract carboxyl cellulose nanofibers(CNFs) from non-wood biomass sources(i.e., jute, soft and hard spinifex grasses). The combined TEMPO-oxidation and homogenization approach was very efficient to produce CNFs from the cellulose component of biomass; however, the nitrooxidation method was also found to be effective to extract CNFs directly from raw biomass even without mechanical treatment.The effect of these two methods on the resulting cross-section dimensions of CNFs was investigated by solution small-angle Xray scattering(SAXS), transmission electron microscopy(TEM) and atomic force microscopy(AFM). The UV-Vis spectroscopic data from 0.1 wt% TEMPO-oxidized nanofiber(TOCNF) and nitro-oxidized nanofiber(NOCNF) suspensions showed that TOCNF had the highest transparency( 95%) because of better dispersion, resulted from the highest carboxylate content(1.2 mmol/g). The consistent scattering and microscopic results indicated that TOCNFs from jute and spinifex grasses possessed rectangular cross-sections, while NOCNFs exhibited near square cross-sections. This study revealed that different oxidation methods can result in different degrees of biomass exfoliation and different CNF morphology.     

mRNA and miRNA Profiles of Exosomes from Cultured Tumor Cells Reveal Biomarkers Specific for HPV16-Positive and HPV16-Negative Head and Neck Cancer

Human papillomavirus (HPV)(+) and HPV(−) head and neck cancer (HNC) cells’ interactions with the host immune system are poorly understood. Recently, we identified molecular and functional differences in exosomes produced by HPV(+) vs. HPV(−) cells, suggesting that genetic cargos of exosomes might identify novel biomarkers in HPV-related HNCs. Exosomes were isolated by size exclusion chromatography from supernatants of three HPV(+) and two HPV(−) HNC cell lines. Paired cell lysates and exosomes were analyzed for messenger RNA (mRNA) by qRT-PCR and microRNA (miR) contents by nanostring analysis. The mRNA profiles of HPV(+) vs. HPV(−) cells were distinct, with EGFR, TP53 and HSPA1A/B overexpressed in HPV(+) cells and IL6, FAS and DPP4 in HPV(−) cells. The mRNA profiles of HPV(+) or HPV(−) exosomes resembled the cargo of their parent cells. miR expression profiles in cell lysates identified 8 miRs expressed in HPV(−) cells vs. 14 miRs in HPV(+) cells. miR-205-5p was exclusively expressed in HPV(+) exosomes, and miR-1972 was only detected in HPV(−) exosomes. We showed that HPV(+) and HPV(−) exosomes recapitulated the mRNA expression profiles of their parent cells. Expression of miRs was dependent on the HPV status, and miR-205-5p in HPV(+) and miR-1972 in HPV(−) exosomes emerge as potential discriminating HPV-associated biomarkers.     

Efficient Metal-Free Catalytic Reduction of Nitro to Amine Over Carbon Sheets Doped with Nitrogen

Catalysis Letters - A highly efficient nitrogen-doped carbon sheet-like material (NCS) is developed via simple pyrolysis of β-cyclodextrin and urea at different temperatures. The effect of the...