Stream-Based Authentication Strategy Using IoT Sensor Data in Multi-homing Sub-aqueous Big Data Network

Big data analytics has addressed many in-place and remote network issues in a sub-aqueous distributed computing environment. Recently, a new phenomenon is introduced in the data analytics clusters that focus on multi-homing network connectivity procedures among off-ground multiple nodes of the large-scale on-running wireless industrial applications. In this way, the clusters perform multi-layer cross-connected task processing among various networks simultaneously and perform stream based data block placement over multiple nodes in a sequential order. This satisfies the procedural performance of the cluster; however, security remains an open issue in it because of unavailability of inter-network data block processing authorization. In this paper, we propose a stream based authentication mechanism, that specifically addresses security concerns of multi-homing sub-aqueous big data networks and presents a key authorization infrastructure that performs a proper handing taking among multiple off-ground Datanodes before an inter-network data block exchange. The simulation results depict that our approach increases multi-homing network compatibility and reliability while processing a data block in the sub-aqueous distributed computing environment

QoS analysis of the MANET routing protocols with respect to delay, throughput, & network load: Challenges and open issues

Mobile Ad Hoc Networks (MANETs) are types of wireless networks that communicate with mobile devices without centralized infrastructures. MANET networks are established through interconnected devices that communicate wirelessly within a relatively small, shared area. In MANET every single mobile node is presumed to travel in all directions at different speeds with challenges and open issues. Hence there is no guaranteed long-term path from one node to the next. This work proposes testing the three most common ad hoc routing protocols Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Optimized Link State Routing Protocol (OLSR) using Optimized Network Engineering Tool (OPNET) Modeler simulations using the performance metrics of Throughput, Delay, and Network loading to find an effective routing protocol for routing. The traffic network is used by the File Transfer Protocol (FTP), Digital Education, Battlefield, Surveillance and Security Agencies may benefit from the research work. MANETs reduced the costs of installation, maintenance and operation of such facilities as base stations and also reduced the risk to a minimum such as pollution. The outcome of the simulation shows that: according to the AODV and DSR, the lowest delay in 50 nodes was around 31.25 seconds respectively. And OLSR also had a high throughput performance of around 80 per cent compared with AODV and DSR. And it can be concluded that OLSR is the most suitable routing protocol for MANET, based on the routing protocols suggested

Mutations with pathogenic potential in proteins located in or at the composite junctions of the intercalated disk connecting mammalian cardiomyocytes: a reference thesaurus for arrhythmogenic cardiomyopathies and for Naxos and Carvajal diseases

In the past decade, an avalanche of findings and reports has correlated arrhythmogenic ventricular cardiomyopathies (ARVC) and Naxos and Carvajal diseases with certain mutations in protein constituents of the special junctions connecting the polar regions (intercalated disks) of mature mammalian cardiomyocytes. These molecules, apparently together with some specific cytoskeletal proteins, are components of (or interact with) composite junctions. Composite junctions contain the amalgamated fusion products of the molecules that, in other cell types and tissues, occur in distinct separate junctions, i.e. desmosomes and adherens junctions. As the pertinent literature is still in an expanding phase and is obviously becoming important for various groups of researchers in basic cell and molecular biology, developmental biology, histology, physiology, cardiology, pathology and genetics, the relevant references so far recognized have been collected and are presented here in the following order: desmocollin-2 (Dsc2, DSC2), desmoglein-2 (Dsg2, DSG2), desmoplakin (DP, DSP), plakoglobin (PG, JUP), plakophilin-2 (Pkp2, PKP2) and some non-desmosomal proteins such as transmembrane protein 43 (TMEM43), ryanodine receptor 2 (RYR2), desmin, lamins A and C, striatin, titin and transforming growth factor-β3 (TGFβ3), followed by a collection of animal models and of reviews, commentaries, collections and comparative studies

IMPLEMENTATION OF MOBILE IP SMOOTH HANDOFF IN WIRELESS NETWORKS

This paper describes implementation of mobile IP services in two separate wireless LANs based on IEEE 802.11b standards, located in two distant buildings of a university campus. The purpose of the project was to achieve smooth handoff when a mobile node moves between the two LANs. During our experimentation we have identified some of the limitations of IEEE 8O2.11b that affects mobile IP smooth handoff. We have also proposed an algorithm to solve this problem when the mobility is within a limited number of separate wireless LANs

Development of a smart instrumentation for analyzing railway track health monitoring using forced vibration

Harmonic responses play a prominent role in determining metallic faults in railways. Therefore, it is useful to develop some instrumentation governed by the principles of forced vibration to evaluate the health condition of a railway track. The conventional systems developed to identify track damage have large deviations in measurements and are not reliable for examining track faults such as track drainage faults and surface damaged faults. This study focuses on the development of an instrument that analyzes track damage wirelessly in real time. Based on forced vibration, the relation between the harmonic response with the amplitude is demonstrated. The developed instrument was validated on an actual railway track. The result shows that, the developed instrument can be used to determine the serviceability of the railway track, thus avoiding any potential catastrophic events

Future mobile technology: Channel access mechanism for LTE-LAA using deep learning

The exponential increase of future mobile phone users is resulting in growth of data traffic which is creating a shortage of the licensed spectrum. The scarcity led to the idea of using the unlicensed channel along with the licensed channel in Long Term Evolution (LTE), known as License Assisted Access (LAA). However, the unlicensed spectrum is already utilized by Wi-Fi and in order to deploy Small Base Stations (SBSs) that will also utilize the same band there is a need for a fair coexistence mechanism which will allow the SBS to be operational without degrading the performance of Wi-Fi. By adopting a deep learning approach, we can train SBSs to predict wireless traffic ahead of time. To forecast future time sequences, we use LSTM models which have already proven to be competent for time series predictions. We tested the LSTM models with high load datasets and a low load dataset that we were able to generate using a 2.4 GHz band. We obtained a RMSE of 0.041463 at the lowest for trace 3 and an MSE of 0.0017192. These results demonstrate the precision of LSTM networks for recognizing wireless traffic patterns. This concept incorporated in LTE-LAA infrastructures can result in better overall service and prove to be energy efficient than the traditional techniques such as LBT or CAA