Intelligent Microservice Based on Blockchain for Healthcare Applications

Nowadays,the blockchain,Internet of Things,and artificial intelligence technology revolutionize the traditional way of data mining with the enhanced data preprocessing,and analytics approaches,including improved service platforms.Nevertheless,one of the main challenges is designing a combined approach that provides the analytics functionality for diverse data and sustains IoT applications with robust and modular blockchain-enabled services in a diverse environment.Improved data analytics model not only provides support insights in IoT data but also fosters process productivity.Designing a robust IoT-based secure analytic model is challenging for several purposes,such as data from diverse sources,increasing data size,and monolithic service designing techniques.This article proposed an intelligent blockchain-enabled microservice to support predictive analytics for personalized fitness data in an IoT environment.The designed system support microservice-based analytic functionalities to provide secure and reliable services for IoT.To demonstrate the proposed model effectiveness,we have used the IoT fitness application as a case study.Based on the designed predictive analytic model,a recommendation model is developed to recommend daily and weekly diet and workout plans for improved body fitness.Moreover,the recommendation model objective is to help trainers make future health decisions of trainees in terms of workout and diet plan.Finally,the proposed model is evaluated using Hyperledger Caliper in terms of latency,throughput,and resource utilization with varying peers and orderer nodes.The experimental result shows that the proposed model is applicable for diverse resourceconstrained blockchain-enabled IoT applications and extensible for several IoT scenarios.

SDN Based DDos Mitigating Approach Using Traffic Entropy for IoT Network

The Internet of Things(IoT)has been widely adopted in various domains including smart cities,healthcare,smart factories,etc.In the last few years,the fitness industry has been reshaped by the introduction of smart fitness solutions for individuals as well as fitness gyms.The IoT fitness devices collect trainee data that is being used for various decision-making.However,it will face numerous security and privacy issues towards its realization.This work focuses on IoT security,especially DoS/DDoS attacks.In this paper,we have proposed a novel blockchain-enabled protocol(BEP)that uses the notion of a self-exposing node(SEN)approach for securing fitness IoT applications.The blockchain and SDN architectures are employed to enhance IoT security by a highly preventive security monitoring,analysis and response system.The proposed approach helps in detecting the DoS/DDoS attacks on the IoT fitness system and then mitigating the attacks.The BEP is used for handling Blockchain-related activities and SEN could be a sensor or actuator node within the fitness IoT system.SEN provides information about the inbound and outbound traffic to the BEP which is used to analyze the DoS/DDoS attacks on the fitness IoT system.The SENcalculates the inbound and outbound traffic features’entropies and transmits them to the Blockchain in the form of transaction blocks.The BEP picks the whole mined blocks’transactions and transfers them to the SDN controller node.The controller node correlates the entropies data of SENs and decides about the DoS or DDoS attack.So,there are two decision points,one is SEN,and another is the controller.To evaluate the performance of our proposed system,several experiments are performed and results concerning the entropy values and attack detection rate are obtained.The proposed approach has outperformed the other two approaches concerning the attack detection rate by an increase of 11%and 18%against Approach 1 and Approach 2 respectively.

Intelligent Transmission Control for Efficient Operations in SDN

Although the Software-Defined Network(SDN)is a well-controlled and efficient network but the complexity of open flow switches in SDN causes multiple issues.Many solutions have been proposed so far for the prevention of errors and mistakes in it but yet,there is still no smooth transmission of pockets from source to destination specifically when irregular movements follow the destination host in SDN,the errors include packet loss,data compromise etc.The accuracy of packets received at their desired destination is possible if networks for pockets and hosts are monitored instead of analysis of network snapshot statistically for the state,as these approaches with open flow switches,discover bugs after their occurrence.This article proposes a design to achieve the said objective by defining the Intelligent Transmission Control Layer(ITCL)layer.It monitors all the connections of end hosts at their specific locations and performs necessary settlements when the connection state changes for one or multiple hosts.The layer informs the controller regarding any state change at one period and controller collects information of end nodes reported via ITCL.Then,updates flow tables accordingly to accommodate a location-change scenario with a routechange policy.ICTL is organized on prototype-based implementation using the popular POX platform.In this paper,it has been discovered that ITCL produces efficient performance in the trafficking of packets and controlling different states of SDN for errors and packet loss.

Complex Problems Solution as a Service Based on Predictive Optimization and Tasks Orchestration in Smart Cities

Smart cities have different contradicting goals having no apparent solution.The selection of the appropriate solution,which is considered the best compromise among the candidates,is known as complex problem-solving.Smart city administrators face different problems of complex nature,such as optimal energy trading in microgrids and optimal comfort index in smart homes,to mention a few.This paper proposes a novel architecture to offer complex problem solutions as a service(CPSaaS)based on predictive model optimization and optimal task orchestration to offer solutions to different problems in a smart city.Predictive model optimization uses a machine learning module and optimization objective to compute the given problem’s solutions.The task orchestration module helps decompose the complex problem in small tasks and deploy them on real-world physical sensors and actuators.The proposed architecture is hierarchical and modular,making it robust against faults and easy to maintain.The proposed architecture’s evaluation results highlight its strengths in fault tolerance,accuracy,and processing speed.

Hybrid Renewable Energy Resources Management for Optimal Energy Operation in Nano-Grid

Renewable energy resources are deemed a potential energy production source due to their cost efficiency and harmless reaction to the environment,unlike non-renewable energy resources.However,they often fail to meet energy requirements in unfavorable weather conditions.The concept of Hybrid renewable energy resources addresses this issue by integrating both renewable and non-renewable energy resources to meet the required energy load.In this paper,an intelligent cost optimization algorithm is proposed to maximize the use of renewable energy resources and minimum utilization of non-renewable energy resources to meet the energy requirement for a nanogrid infrastructure.An actual data set comprising information about the load and demand of utility grids is used to evaluate the performance of the proposed nanogrid energy management system.The objective function is formulated to manage the nanogrid operation and implemented using a variant of Particle Swarm Optimization(PSO)named recurrent PSO(rPSO).Firstly,rPSO algorithm minimizes the installation cost for nanogrid.Thereafter,the proposed NEMS ensures cost efficiency for the post-installation period by providing a daily operational plan and optimizing renewable resources.State-of-the-art optimization models,including Genetic Algorithm(GA),bat and different Mathematical Programming Language(AMPL)solvers,are used to evaluate the model.The study’s outcomes suggest that the proposed work significantly reduces the use of diesel generators and fosters the use of renewable energy resources and beneficiates the eco-friendly environment.

Blockchain Based Secured Load Balanced Task Scheduling Approach for Fitness Service

In recent times,the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security features.The IoT has shown wide adoption in various applications including smart cities,healthcare,trade,business,etc.Among these applications,fitness applications have been widely considered for smart fitness systems.The users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness facilities.Thus,scheduling such a huge number of requests for fitness exercise is a big challenge.Secondly,the user fitness data is critical thus securing the user fitness data from unauthorized access is also challenging.To overcome these issues,this work proposed a blockchain-based load-balanced task scheduling approach.A thorough analysis has been performed to investigate the applications of IoT in the fitness industry and various scheduling approaches.The proposed scheduling approach aims to schedule the requests of the fitness users in a load-balanced way that maximize the acceptance rate of the users’requests and improve resource utilization.The performance of the proposed task scheduling approach is compared with the state-of-the-art approaches concerning the average resource utilization and task rejection ratio.The obtained results confirm the efficiency of the proposed scheduling approach.For investigating the performance of the blockchain,various experiments are performed using the Hyperledger Caliper concerning latency,throughput,resource utilization.The Solo approach has shown an improvement of 32%and 26%in throughput as compared to Raft and Solo-Raft approaches respectively.The obtained results assert that the proposed architecture is applicable for resource-constrained IoT applications and is extensible for different IoT applications.

Effectively Handling Network Congestion and Load Balancing in Software-Defined Networking

The concept of Software-Defined Networking(SDN)evolves to overcome the drawbacks of the traditional networks with Internet Protocol(I.P.)packets sending and packets handling.The SDN structure is one of the critical advantages of efficiently separating the data plane from the control plane tomanage the network configurations and network management.Whenever there aremultiple sending devices inside the SDNnetwork,theOpenFlow switches are programmed to handle the limited number of requests for their interface.When the recommendations are exceeded from the specific threshold,the load on the switches also increases.This research article introduces a new approach named LBoBS to handle load balancing by adding the load balancing server to the SDN network.Besides,it is used to maximize SDN’s reliability and efficiency.It also works in coordination with the controller to effectively handle the load balancing policies.The load balancing server is implemented to manage the switches load effectively.Results are evaluated on the NS-3 simulator for packet delivery,bandwidth utilization,latency control,and packet decision ratios on the OpenFlow switches.It has been found that the proposed method improved SDN’s load balancing by 70%compared to the previous state-of-the-art methods.

Towards a Dynamic Virtual IoT Network Based on User Requirements

The data being generated by the Internet of Things needs to be stored,monitored,and analyzed for maximum IoT resource utilization.Software Defined Networking has been extensively utilized to address issues such as heterogeneity and scalability.However,for small-scale IoT application,sometimes it is considered an inefficient approach.This paper proposes an alternate lightweight mechanism to the design and implementation of a dynamic virtual network based on user requirements.The key idea is to provide users a virtual interface that enables them to reconfigure the communication flow between the sensors and actuators at runtime.The throughput of the communication flow depends on the data traffic load and optimal routing.Users can reconfigure the communication flow,and virtual agents find the optimal route to handle the traffic load.The virtual network provides a user-friendly interface to allow physical devices to be mapped with the corresponding virtual agents.The proposed network is applicable for all systems that lie in the Internet of Things domain.Results conclude that the proposed network is efficient,reliable,and responsive to network reconfiguration at runtime.