scholarly journals Presenting a Reliable Routing Approach in IoT Healthcare Using the Multiobjective-Based Multiagent Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Saeed Javid ◽  
A. Mirzaei
Keyword(s):  
Multiobjective Optimization ◽  
Secure Communication ◽  
Information Transfer ◽  
Data Transfer ◽  
Vital Signs ◽  
Daily Routine ◽  
Optimization Approach ◽  
Healthcare Applications ◽  
Reliable Routing ◽  
Optimal Paths

Developments in information and related technologies have led to a wider use of the Internet of things (IoT). By integrating both virtual and physical worlds, IoT creates an integrated communication framework of interrelated things and operating systems. With the advent of IoT systems based on digital remote care, transferring medical data is becoming a daily routine. Healthcare is one of the most popular IoT applications and tries to monitor patients’ vital signs during the day for weeks and to eliminate the need for hospitalization. In a healthcare system, many sensors are installed to collect the patient’s information, including environmental monitoring sensors and vital and unstructured message sensors in order to reduce the patients’ expenses. The IoT network contains flexible sensors in dynamically changing environments where sensors collect environmental information and send it to nursing stations for healthcare applications. Due to the wireless nature of IoT networks, secure data transmission in the healthcare context is very important. Data collected from sensors embedded in healthcare devices may be lost for various reasons along the transmission path. Therefore, establishing a secure communication path in IoT networks in the context of healthcare is of great importance. In this paper, in order to provide a reliable data transfer protocol in the context of healthcare, a reliable routing using multiobjective genetic algorithm (RRMOGA) method is presented. The contribution of this paper can be summarized in two steps: (i) using a multiobjective optimization approach to find near-optimal paths and (ii) using reliable agents in the network to find backup paths. The simulation outcomes reveal that the proposed approach, based on the use of the multiobjective optimization approach, tries to find optimal paths for information transfer that improve the main parameters of the network. Also, the use of secure agents leads to a secure information transfer in the network in the context of healthcare. Experimental results show that the proposed method has achieved reliability and data delivery rates, 99% and 99.9%, respectively. The proposed method has improved network lifetime, delivery rate, and delay by 14%, 2%, and 5.6%, respectively.

scholarly journals DNA Based Cryptography Techniques with Applications and Limitations

2019 ◽  
Vol 8 (6) ◽  
pp. 3997-4004
Keyword(s):  
Genetic Information ◽  
Secure Communication ◽  
Information Transfer ◽  
Large Scale ◽  
Storage Capacity ◽  
Data Transfer ◽  
Low Power Consumption ◽  
Dna Cryptography ◽  
Modern Cryptography ◽  
Very High

Cryptography techniques and systems have been developed for data security.DNA cryptography techniques are much better as compared to Quantum cryptography techniques and modern cryptography techniques. This type's cryptography is a fresh and growing paradigm in the field of cryptography for secure communication on a different application. DNA cryptography is based on genetic information transfer from one generation to the next generation. This type of cryptography uses DNA molecules which have very high dense storage capacity and large scale parallelism. So, this technique provides fast and secure data transfer from one end to another end with low power consumption. In this paper, many approaches based on DNA cryptography have been discussed with applications and limitations.

A Joint Multicast Optimization Approach for QoS Provisioning in Optical Label Switching (OLS) Networks

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Yassine Khlifi ◽  
Majid Alotaibi
Keyword(s):  
Traffic Management ◽  
Network Performance ◽  
Data Transfer ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Wavelength Converter ◽  
Label Switching ◽  
Link Capacity ◽  
Two Stages ◽  
Logical Topology

AbstractOptical label switching is introduced for ensuring fast data transfer, quality of service (QoS) support, and better resource management. However, the important issue is how to optimize resource usage and satisfy traffic constraints for improving network performance and design. This paper proposes a dynamic approach that optimizes the resource in terms of link capacity and FDL (fiber delay line) buffering as well as a wavelength converter. The proposed approach decreases the resources usage and guarantees QoS support for various traffic demands. The optimization strategy consists of two stages: path building and traffic management. The path building assures logical topology making using the cumulative cost of available resource and traffic requirements including unicast and multicast. The traffic management solves the resource formulation problem during the traffic transfer by guaranteeing the required loss and blocking delay. Simulation work is conducted for validating the proposed approach and evaluating its performances and effectiveness. Simulation results show that our proposal minimizes effectively the use of link capacity of lightpath and light-tree. Moreover, our approach optimizes the use of buffering capacity and wavelength converter and guarantees QoS support according to traffic requirements.

An Evolutionary Multi-Objective Optimization Approach to the Topology Optimization of Auxetic Structures

2002 ◽  
Author(s):  
Ashraf O. Nassef
Keyword(s):  
Topology Optimization ◽  
Elastic Modulus ◽  
Finite Elements ◽  
Multiobjective Optimization ◽  
Poisson Ratio ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Finite Elements Analysis ◽  
Multi Objective ◽  
Auxetic Structures

Auxetic structures are ones, which exhibit an in-plane negative Poisson ratio behavior. Such structures can be obtained by specially designed honeycombs or by specially designed composites. The design of such honeycombs and composites has been tackled using a combination of optimization and finite elements analysis. Since, there is a tradeoff between the Poisson ratio of such structures and their elastic modulus, it might not be possible to attain a desired value for both properties simultaneously. The presented work approaches the problem using evolutionary multiobjective optimization to produce several designs rather than one. The algorithm provides the designs that lie on the tradeoff frontier between both properties.

Design of Electrooptic Modulators Using a Multiobjective Optimization Approach

2008 ◽  
Vol 26 (16) ◽  
pp. 2969-2976 ◽  
Author(s):  
Ademar Muraro ◽  
Angelo Passaro ◽  
Nancy Mieko Abe ◽  
Airam Jonatas Preto ◽  
Stephan Stephany
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Approach ◽  
Electrooptic Modulators

scholarly journals A MultiObjective Optimization Approach for Integrated Timetabling and Vehicle Scheduling with Uncertainty

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yindong Shen ◽  
Wenliang Xie ◽  
Jingpeng Li
Keyword(s):  
Multiobjective Optimization ◽  
Planning Process ◽  
Service Level ◽  
Vehicle Scheduling ◽  
Neighborhood Search ◽  
Optimization Approach ◽  
Transit Planning ◽  
Integrated Optimization ◽  
Link Cost ◽  
Integrated Approaches

The timetabling problem (TTP) and vehicle scheduling problem (VSP) are two indispensable problems in public transit planning process. They used to be solved in sequence; hence, optimality of resulting solutions is compromised. To get better results, some integrated approaches emerge to solve the TTP and VSP as an integrated problem. In the existing integrated approaches, the passenger comfort on bus and the uncertainty in the real world are rarely considered. To provide better service for passengers and enhance the robustness of the schedule to be compiled, we study the integrated optimization of TTP and VSP with uncertainty. In this paper, a novel multiobjective optimization approach with the objectives of minimizing the passenger travel cost, the vehicle scheduling cost, and the incompatible trip-link cost is proposed. Meanwhile, a multiobjective hybrid algorithm, which is a combination of the self-adjust genetic algorithm (SGA), large neighborhood search (LNS) algorithm, and Pareto separation operator (PSO), is applied to solve the integrated optimization problem. The experimental results show that the approach outperforms existing approaches in terms of service level and robustness.

scholarly journals Integrated civilian–military pre-positioning of emergency supplies: A multiobjective optimization approach

2017 ◽  
Vol 58 ◽  
pp. 732-741 ◽  
Author(s):  
Yu-Jun Zheng ◽  
Yue Wang ◽  
Hai-Feng Ling ◽  
Yu Xue ◽  
Sheng-Yong Chen
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Approach

A fast multiobjective optimization approach to S-duct scoop inlets design with both inflow and outflow

2018 ◽  
Vol 233 (9) ◽  
pp. 3381-3394
Author(s):  
Lifang Zeng ◽  
Dingyi Pan ◽  
Shangjun Ye ◽  
Xueming Shao
Keyword(s):  
Multiobjective Optimization ◽  
Total Pressure ◽  
Optimization Method ◽  
Navier Stokes ◽  
Integral Model ◽  
Optimization Approach ◽  
Navier Stokes Equation ◽  
Cross Sectional ◽  
Design Variables ◽  
Computational Fluid Dynamics Analysis

A fast multiobjective optimization method for S-duct scoop inlets considering both inflow and outflow is developed and validated. To reduce computation consumption of optimization, a simplified efficient model is proposed, in which only inflow region is simulated. Inlet pressure boundary condition of the efficient model is specified by solving an integral model with both inflow and outflow. An automated optimization system integrating the computational fluid dynamics analysis, nonuniform rational B-spline geometric representation technique, and nondominated sorting genetic algorithm II is developed to minimize the total pressure loss and distortion at the exit of diffuser. Flow field is numerically simulated by solving the Reynolds-averaged Navier–Stokes equation coupled with k–ω shear stress transport turbulence model, and results are validated to agree well with previous experiment. S-duct centreline shape and cross-sectional area distribution are parameterized as the design variables. By analyzing the results of a suggested optimal inlet chosen from the obtained Pareto front, total pressure recovery has increased from 97% to 97.4%, and total pressure distortion DC60 has decreased by 0.0477 (21.7% of the origin) at designed Mach number 0.7. The simplified efficient model has been validated to be reliable, and by which the time cost for the optimization project has been reduced by 70%.

scholarly journals Radar-Based Non-Contact Continuous Identity Authentication

2020 ◽  
Vol 12 (14) ◽  
pp. 2279 ◽  
Author(s):  
Shekh Md Mahmudul Islam ◽  
Olga Borić-Lubecke ◽  
Yao Zheng ◽  
Victor M. Lubecke
Keyword(s):  
Doppler Radar ◽  
Vital Signs ◽  
Identity Authentication ◽  
Future Research ◽  
Great Promise ◽  
Healthcare Applications ◽  
Privacy Concerns ◽  
Vital Signs Monitoring ◽  
Wide Range ◽  
Physiological Sensing

Non-contact vital signs monitoring using microwave Doppler radar has shown great promise in healthcare applications. Recently, this unobtrusive form of physiological sensing has also been gaining attention for its potential for continuous identity authentication, which can reduce the vulnerability of traditional one-pass validation authentication systems. Physiological Doppler radar is an attractive approach for continuous identity authentication as it requires neither contact nor line-of-sight and does not give rise to privacy concerns associated with video imaging. This paper presents a review of recent advances in radar-based identity authentication systems. It includes an evaluation of the applicability of different research efforts in authentication using respiratory patterns and heart-based dynamics. It also identifies aspects of future research required to address remaining challenges in applying unobtrusive respiration-based or heart-based identity authentication to practical systems. With the advancement of machine learning and artificial intelligence, radar-based continuous authentication can grow to serve a wide range of valuable functions in society.

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