Network Blueprint for Maximizing the Lifetime of Smart Devices in Low Power IoT Networks

2021 ◽  
Vol 13 (2) ◽  
pp. 21-38
Author(s):  
Sarwesh P. ◽  
K. Chandrasekaran ◽  
Thamizharasan S.
Keyword(s):  
Network Lifetime ◽  
Network Architecture ◽  
Data Transfer ◽  
Network Reliability ◽  
Smart Devices ◽  
Node Placement ◽  
The Standard Model ◽  
Device Lifetime ◽  
Placement Technique ◽  
Better Than

In the modern communication and computation era, internet of things (IoT) is developing as the key technology that satisfies the requirements of various applications. Prolonging device lifetime and maintaining network reliability is the evident objective for IoT network. Therefore, the authors come up with the network architecture that integrates node placement technique and routing technique. In the architecture, node placement is implemented by varying the density of nodes, by varying battery level of nodes, and by varying transmission range of nodes. Energy efficient and reliable path computation is addressed by routing technique. Therefore, enhancing the features of routing and node placement technique and integrating them together in network architecture can efficiently prolong the network lifetime. From the results, the authors observed that the proposed network architecture prolongs the network lifetime two times better than the standard model and also outperforms EQSR protocol and maintains the reliable data transfer.

Effective Integration of Reliable Routing Mechanism and Energy Efficient Node Placement Technique for Low Power IoT Networks

2017 ◽  
Vol 9 (4) ◽  
pp. 16-35 ◽  
Author(s):  
P. Sarwesh ◽  
N. Shekar V. Shet ◽  
K. Chandrasekaran
Keyword(s):  
Low Power ◽  
Energy Efficient ◽  
Network Architecture ◽  
Ieee 802.15.4 ◽  
Environmental Data ◽  
Relay Nodes ◽  
Node Placement ◽  
Path Computation ◽  
Routing Mechanism ◽  
Placement Technique

Internet of Things (IoT) is the emerging technology that links physical devices (sensor devices) with cyber systems and allows global sharing of information. In IoT applications, devices are operated by battery power and low power radio links, which are constrained by energy. In this paper, node placement technique and routing mechanism are effectively integrated in single network architecture to prolong the lifetime of IoT network. In proposed network architecture, sensor node and relay node are deployed, sensor nodes are responsible for collecting the environmental data and relay nodes are responsible for data aggregation and path computation. In node placement technique, densities of relay nodes are varied based on traffic area, to prevent energy hole problem. In routing technique, energy efficient and reliable path computation is done to reduce number of re transmissions. To adopt IoT scenario, we included IEEE 802.15.4 PHY/MAC radio and IPv6 packet structure in proposed network architecture. Proposed work result shows, proposed architecture prolongs network lifetime.

Effective Integration of Reliable Routing Mechanism and Energy Efficient Node Placement Technique for Low Power IoT Networks

2020 ◽  
pp. 344-363
Author(s):  
P. Sarwesh ◽  
N. Shekar V. Shet ◽  
K. Chandrasekaran
Keyword(s):  
Low Power ◽  
Energy Efficient ◽  
Network Architecture ◽  
Ieee 802.15.4 ◽  
Relay Node ◽  
Relay Nodes ◽  
Node Placement ◽  
Path Computation ◽  
Routing Mechanism ◽  
Placement Technique

Internet of Things (IoT) is the emerging technology that links physical devices (sensor devices) with cyber systems and allows global sharing of information. In IoT applications, devices are operated by battery power and low power radio links, which are constrained by energy. In this paper, node placement technique and routing mechanism are effectively integrated in single network architecture to prolong the lifetime of IoT network. In proposed network architecture, sensor node and relay node are deployed, sensor nodes are responsible for collecting the environmental data and relay nodes are responsible for data aggregation and path computation. In node placement technique, densities of relay nodes are varied based on traffic area, to prevent energy hole problem. In routing technique, energy efficient and reliable path computation is done to reduce number of re transmissions. To adopt IoT scenario, we included IEEE 802.15.4 PHY/MAC radio and IPv6 packet structure in proposed network architecture. Proposed work result shows, proposed architecture prolongs network lifetime.

scholarly journals Fighting Together against the Pandemic: Learning Multiple Models on Tomography Images for COVID-19 Diagnosis

AI ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 261-273
Author(s):  
Mario Manzo ◽  
Simone Pellino
Keyword(s):  
Network Architecture ◽  
State Of The Art ◽  
Ensemble Classification ◽  
Effective Vaccine ◽  
Rt Pcr ◽  
Neural Network Architecture ◽  
Experimental Phase ◽  
Different Types ◽  
Polymerase Chain ◽  
Better Than

COVID-19 has been a great challenge for humanity since the year 2020. The whole world has made a huge effort to find an effective vaccine in order to save those not yet infected. The alternative solution is early diagnosis, carried out through real-time polymerase chain reaction (RT-PCR) tests or thorax Computer Tomography (CT) scan images. Deep learning algorithms, specifically convolutional neural networks, represent a methodology for image analysis. They optimize the classification design task, which is essential for an automatic approach with different types of images, including medical. In this paper, we adopt a pretrained deep convolutional neural network architecture in order to diagnose COVID-19 disease from CT images. Our idea is inspired by what the whole of humanity is achieving, as the set of multiple contributions is better than any single one for the fight against the pandemic. First, we adapt, and subsequently retrain for our assumption, some neural architectures that have been adopted in other application domains. Secondly, we combine the knowledge extracted from images by the neural architectures in an ensemble classification context. Our experimental phase is performed on a CT image dataset, and the results obtained show the effectiveness of the proposed approach with respect to the state-of-the-art competitors.

Performance Analysis of AODV Protocol in Mobile Ad Hoc Networks

2011 ◽  
Vol 403-408 ◽  
pp. 2415-2419 ◽  
Author(s):  
Yuan Ming Ding ◽  
Chang Hong Sun ◽  
Lin Song ◽  
Wan Qi Kong
Keyword(s):  
Routing Protocol ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Data Transfer ◽  
Simulation Software ◽  
Aodv Protocol ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
Aodv Routing Protocol ◽  
Better Than

Simulation environment of the mobile Ad Hoc network is built by applying NS2 simulation software. The simulation data indicates that AODV routing protocol is better than DSDV in throughput, fairness and stability. In the underwater network environment where the nodes are in Low-Speed movement, the data transfer rate of AODV routing protocol is higher than AOMDV. To a certain extent, AODV is more suitable for application in underwater environments.

Reliability Models of GSM-R Redundant Network on High-Speed Railway

2012 ◽  
Vol 198-199 ◽  
pp. 1783-1788
Author(s):  
Jun Ting Lin ◽  
Jian Wu Dang
Keyword(s):  
Network Architecture ◽  
High Speed ◽  
Failure Time ◽  
Network Reliability ◽  
Single Layer ◽  
Double Layers ◽  
High Speed Railway ◽  
Reliability Models ◽  
Single Layer Network ◽  
Wireless Architectures

As a dedicated digital mobile communication system designed for railway application, GSM-R must provide reliable bidirectional channel for transmitting security data between trackside equipments and on-train computer on high-speed railways. To ensure the safety of running trains, redundant network architecture is commonly used to guarantee the reliability of GSM-R. Because of the rigid demands of railway security, it is important to build reliability mathematical models, predict the network reliability and select a suitable one. Two common GSM-R wireless architectures, co-sited double layers network and intercross single layer network, are modeled and contrasted in this paper. By calculating the reliabilities of each reliable model, it is clear that more redundant the architecture is, more reliable the system will be, the whole system will bear a less failure time per year as the benefit. Meanwhile, as the redundancy of GSM-R system raises, its equipment and maintenance will cost much, but the reliability raise gently. From the standpoint of transmission system interruption and network equipment failure, the reliability of co-sited double layer network architecture is higher than the intercross single layer one, while the viability and cost of the intercross redundant network is better than co-sited one in natural disasters such as flood and lightning. Taking fully into account reliability, viability and cost, we suggest that intercross redundant network should be chosen on high-speed railway.

scholarly journals DeepIsoFun: a deep domain adaptation approach to predict isoform functions

2018 ◽  
Vol 35 (15) ◽  
pp. 2535-2544 ◽  
Author(s):  
Dipan Shaw ◽  
Hao Chen ◽  
Tao Jiang
Keyword(s):  
Network Architecture ◽  
Domain Adaptation ◽  
Multiple Instance Learning ◽  
Training Data ◽  
Supplementary Information ◽  
Operating Characteristics ◽  
Neural Network Architecture ◽  
Receiver Operating Characteristics Curve ◽  
Gene Functions ◽  
Better Than

AbstractMotivationIsoforms are mRNAs produced from the same gene locus by alternative splicing and may have different functions. Although gene functions have been studied extensively, little is known about the specific functions of isoforms. Recently, some computational approaches based on multiple instance learning have been proposed to predict isoform functions from annotated gene functions and expression data, but their performance is far from being desirable primarily due to the lack of labeled training data. To improve the performance on this problem, we propose a novel deep learning method, DeepIsoFun, that combines multiple instance learning with domain adaptation. The latter technique helps to transfer the knowledge of gene functions to the prediction of isoform functions and provides additional labeled training data. Our model is trained on a deep neural network architecture so that it can adapt to different expression distributions associated with different gene ontology terms.ResultsWe evaluated the performance of DeepIsoFun on three expression datasets of human and mouse collected from SRA studies at different times. On each dataset, DeepIsoFun performed significantly better than the existing methods. In terms of area under the receiver operating characteristics curve, our method acquired at least 26% improvement and in terms of area under the precision-recall curve, it acquired at least 10% improvement over the state-of-the-art methods. In addition, we also study the divergence of the functions predicted by our method for isoforms from the same gene and the overall correlation between expression similarity and the similarity of predicted functions.Availability and implementationhttps://github.com/dls03/DeepIsoFun/Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals The Science DMZ: A Network Design Pattern for Data-Intensive Science

2014 ◽  
Vol 22 (2) ◽  
pp. 173-185 ◽  
Author(s):  
Eli Dart ◽  
Lauren Rotman ◽  
Brian Tierney ◽  
Mary Hester ◽  
Jason Zurawski
Keyword(s):  
Network Design ◽  
Network Architecture ◽  
Design Patterns ◽  
Data Transfer ◽  
Scientific Discovery ◽  
High Capacity ◽  
Scientific Progress ◽  
Scientific Data ◽  
Data Intensive ◽  
And Performance

The ever-increasing scale of scientific data has become a significant challenge for researchers that rely on networks to interact with remote computing systems and transfer results to collaborators worldwide. Despite the availability of high-capacity connections, scientists struggle with inadequate cyberinfrastructure that cripples data transfer performance, and impedes scientific progress. The ScienceDMZparadigm comprises a proven set of network design patterns that collectively address these problems for scientists. We explain the Science DMZ model, including network architecture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercomputing centers and research laboratories, highlighting the effectiveness of the Science DMZ model in diverse operational settings. In all, the Science DMZ model is a solid platform that supports any science workflow, and flexibly accommodates emerging network technologies. As a result, the Science DMZ vastly improves collaboration, accelerating scientific discovery.

scholarly journals Theoretical challenges for flavor physics

2021 ◽  
Vol 136 (9) ◽  
Author(s):  
Yuval Grossman ◽  
Zoltan Ligeti
Keyword(s):  
Standard Model ◽  
Flavor Physics ◽  
Beyond The Standard Model ◽  
Physics Program ◽  
The Standard Model ◽  
Nonperturbative Qcd ◽  
Near Future ◽  
Better Than

AbstractWe discuss some highlights of the FCC-$$ee$$ ee flavor physics program. It will help to explore various aspects of flavor physics: to test precision calculations, to probe nonperturbative QCD methods, and to increase the sensitivity to physics beyond the standard model. In some areas, FCC-$$ee$$ ee will do much better than current and near-future experiments. We briefly discuss several probes that can be relevant for maximizing the gain from the FCC-$$ee$$ ee flavor program.

scholarly journals A Multi-User Schedule Method for Non-Orthogonal Multiple Access in 5G Heterogeneous Network

2019 ◽  
Vol 37 (2) ◽  
pp. 337-343
Author(s):  
Yi Xie
Keyword(s):  
Heterogeneous Network ◽  
Network Architecture ◽  
Multiple Access ◽  
Average Rate ◽  
Small Cells ◽  
Fifth Generation ◽  
Scheduling Method ◽  
New Type ◽  
Multiuser Scheduling ◽  
Better Than

Heterogeneous network is supposed to be the dominant network architecture of the fifth generation (5G) cellular network, which means small cells are overlaid on the macrocell. The beamforming (BF) and cell expansion are two important approaches to serve users in small cells. Furthermore, non-orthogonal multiple access (NOMA) is a new type of multiple access multiplexing which improves system performance without taking up extra spectrum resources. Therefore, it becomes one promising technique in 5G. In this paper, NOMA is applied in a 5G heterogeneous network with biased small cells. The BF strategy and the multiuser scheduling method are proposed. The main user in NOMA is scheduled inside the original coverage of the small cell while the side user is chosen from the biased expansion area. The BF strategy that is executed depends on the channel of main user. The multiuser scheduling method is to maximize the rate performance. The proposed method can provide performance benefits. Simulation results show that the proposed methods can be well applied in heterogeneous networks. The achieved performance gain is approximately twice better than traditional OMA and has 10% improvement to the stochastic schedule method. In addition, the average rate of cell edge users is improved.

FBMC OQAM: novel variant of OFDM

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shiv Om Tiwari ◽  
Rajeev Paulus
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Data Transfer ◽  
Average Power ◽  
Hybrid Technique ◽  
Filter Bank Multicarrier ◽  
Novel Variant ◽  
Good Technique ◽  
Pass Through ◽  
Papr Performance ◽  
Better Than

Abstract Orthogonal frequency division multiplexing (OFDM) revolutionizes the transmission technologies, including, optical as well as wireless communication. In OFDM the orthogonal nature of carriers makes it very good technique for data transfer. Still the out-of-band (OOB) radiation in OFDM leads to inter symbol interference (ISI) and bit error rate (BER) goes down. Moreover amplitude variations of the subcarriers lead to power variations and peak-to-average power ratio (PAPR) problem. To overcome these issues a novel filter bank multicarrier (FBMC) scheme is proposed, where each carrier is allowed to pass through to a separate filter and orthogonality among subcarriers is relaxed. Thus FBMC has better OOB and PAPR performance. In this work, we also have evaluated the PAPR performance by the simulation results. For the improvement of PAPR nonlinear companding scheme along with clipping is presented. The hybrid technique (clipping + companding) parameters are set in such a way that PAPR is reduced while signal power remains constant. Results are also compared with recent methods and it has been found that the proposed technique preforms better than other chosen techniques.

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