Performance Of Internet Of Things Research Articles

An efficient intrusion detection systems in fog computing using forward selection and BiLSTM

Intrusion detection systems (IDS) play a pivotal role in network security and anomaly detection and are significantly impacted by the feature selection (FS) process. As a significant task in machine learning and data analysis, FS is directed toward pinpointing a subset of pertinent features that primarily influence the target variable. This paper proposes an innovative approach to FS, leveraging the forward selection search algorithm with hybrid objective/fitness functions such as correlation, entropy, and variance. The approach is evaluated using the BoT-IoT and TON_IoT datasets. By employing the proposed methodology, our bidirectional long-short term memory (BiLSTM) model achieved an accuracy of 98.42% on the TON_IoT dataset and 98.7% on the BoT-IoT dataset. This superior classification accuracy underscores the efficacy of the synergized BiLSTM deep learning model and the innovative FS approach. The study accentuates the potency of the proposed hybrid approach in FS for IDS and highlights its substantial contribution to achieving high classification performance in internet of things (IoT) network traffic analysis.

Design and Development of Multi-Objective Hybrid Clustering Framework for Smart City in India Using Internet of Things

The drastic growth of smart city has considerably gained attention around the world in the international policies and systematic literature. Numerous specialists should include diverse opinions owing to the hurdles to the design of smart cities in India. Thus, these experts have also offered their opinions regarding public, agriculture, industry and academia-fields, which help in developing the smart cities. Generally, more limitations have to be faced with offering energy optimisation and superior performance in Internet of Things (IoT)-enabled smart cities. In wireless sensor networks (WSNs) and IoT, the sensors or IoT devices or nodes are often grouped into clusters that result in selecting the cluster head, which gathers information from the entire nodes in cluster and plainly transmits with the base station. This paper makes an attempt on the development of smart cities in India using the hybrid meta-heuristic-based multi-objective cluster head selection model. The proposed model focusses on the design and development of new smart city model applicable for India by considering a multi-objective function using the constraints like distance, delay, energy, load and temperature of the IoT devices. The optimisation of these variables during the smart city development model by IoT is accomplished by a new hybrid Deer Hunting-Tunicate Swarm Optimisation (DH-TSO) algorithm. The performance of the proposed model is verified through a comparative analysis using various state-of-the-art optimisation models by concerning the number of alive nodes, and normalised energy, and thus ensures the overall lifetime of the network.

Dynamic Lightweight Mechanism for Security and Performance in Internet of Things

Communication between machines has become commonplace in recent years, and the Internet of Things (IoT) is gaining notoriety. Congestion control is a prevalent issue in the transportation system, and GPS devices, which drivers and traffic authorities alike utilise, are well-suited to the job. Traffic density is expanding at an alarming rate, making it impossible for drivers to see and handle all of the possible scenarios in a traffic area they are ready to enter. It's also becoming increasingly difficult to maintain security and integrity due to a growing number of assaults by hackers that send harmful code or bogus packets. There are a few new technologies that have yet to be put into practise under the Internet of Things umbrella, including ubiquitous computing (IoT).

Efficient routing algorithm for improving the network performance in Internet of Things

Efficient routing algorithm for improving the network performance in Internet of Things

Efficient Routing Algorithm for improving the Network performance in Internet of Things

Efficient Routing Algorithm for improving the Network performance in Internet of Things

On the Secrecy for Relay-Aided SWIPT Internet of Things System With Cooperative Eavesdroppers

In this paper, the secrecy performance in internet of things (IoTs) networks with cooperative eavesdroppers has been investigated, where simultaneous wireless information and power transfer (SWIPT) nodes perform as relay nodes. The secrecy energy efficiency (SEE) maximization problem for single relay node has been introduced to extend the life-time for IoT nodes without power supply. The optimization problem is firstly transformed into two sub-problems, and then each sub-problem is solved by bisection method. Furthermore, the model has been extended into multiple relay nodes and a novel relay selection algorithm for SEE maximization has been proposed. Finally, the advantage of the proposed algorithm has been verified from simulations.

Cyber-Physical System-based Real-Time Monitoring, Industrial Big Data Analytics, and Smart Factory Performance in Sustainable Manufacturing Internet of Things

Cyber-Physical System-based Real-Time Monitoring, Industrial Big Data Analytics, and Smart Factory Performance in Sustainable Manufacturing Internet of Things

Uplink Power-Domain Non-Orthogonal Multiple Access (NOMA)

Non-orthogonal multiple access (NOMA) has been proposed as a promising multiple access (MA) technique in order to meet the requirements for fifth generation (5G) communications and to enhance the performance in internet of things (IoT) networks by enabling massive connectivity, high throughput, and low latency. This paper investigates the bit error rate (BER) performance of two-user uplink power-domain NOMA with a successive interference cancellation (SIC) receiver and taking into account channel estimation errors. The analysis considers two scenarios: perfect (ideal) channel estimation and a channel with estimation errors for various modulations schemes, BPSK, QPSK, and 16-QAM. The simulation results show that, as expected, increasing of the modulation level increases the SIC receiver BER. For example, at a signal-to-noise ratio (SNR) of 5 dB for perfect channel estimation and QPSK modulation, the user that is detected first has a BER of 0.005 compared to 0.14 for the user that is detected with the aid of the SIC receiver. Similarly, the BER of QPSK, assuming 0.25 channel estimation error of user 1, is equal to 0.06 at SNR = 15 dB compared to 0.017 for perfect estimation.

Research on the Framework of High Performance the Internet of Things Based on Multilevel Disaster Recovery

The ability of disaster recovery and fast response is the key elements to measure the internet of things performance. With studying these technology, including load dispatching, composite gateway, cluster, data mirroring, and so on, round-robin dispatching, address mapping, load balancing cluster, and virtual private network technology are integrated. Thus, multilevel disaster recovery network, which is that business services and business processing system are processed independently, is built successfully. Therefore, distributed and synchronous data transmission of the internet of things and efficient access are solved. These targets of cross region disaster recovery of the internet of things and fast response of a large number of concurrent access are realized. The safety and continuity of the internet of things data service and application service are improved.