Design of an IoT DDoS attack prediction system based on data mining technology
Due to the rise of the Internet of things (IoT), the threat to information security extends from general servers to IoT devices. Possible IoT security issues include all kinds of network attacks. Distributed denial-of-service (DDoS) attacks are ...
PSO-RDAL: particle swarm optimization-based resource- and deadline-aware dynamic load balancer for deadline constrained cloud tasks
Cloud computing is an Internet-provisioned computing paradigm that provides scalable resources for the execution of the end user’s tasks. The cloud users lease optimal resources that meet their demands with minimum cost and time. The cloud service ...
A smart intuitionistic fuzzy-based framework for round-robin short-term scheduler
A smart intuitionistic fuzzy-based framework is designed to facilitate adaptability by providing continuous changes in the size of time slice to scheduler at run time. The present work models a round-robin scheduler with its imprecise parameters. ...
The facial expression recognition technology under image processing and neural network
A facial expression recognition (FER) algorithm is built on the advanced convolutional neural network (CNN) to improve the current FER algorithms’ recognition rate. The advanced CNN model (the ExpressionNet model), containing two continuous ...
Automatic detection of depression symptoms in twitter using multimodal analysis
Depression is the most prevalent mental disorder that can lead to suicide. Due to the tendency of people to share their thoughts on social platforms, social data contain valuable information that can be used to identify user’s psychological ...
A deep analysis of object capabilities for intelligence considering wireless IoT devices with the DNN approach
The Internet of Things (IoT) represents a potential paradigm increase in the number of linked devices, referred to as things. Administering these things remains a difficulty. The advancement of Internet of Things technology has generated ...
Optimizing emotion–cause pair extraction task by using mutual assistance single-task model, clause position information and semantic features
The traditional emotion–cause extraction task needs to give the exact emotion annotation contained in the document before extracting the cause. Different from this, the emotion–cause pair extraction (ECPE) task, which aims to extract emotion–cause ...
A new software cache structure on Sunway TaihuLight
The Sunway TaihuLight is the first supercomputer built entirely with domestic processors in China. On Sunway Taihulight, the local data memory (LDM) of the slave core is limited, so data transmission with the main memory is frequent during ...
Discrete hybrid cuckoo search and simulated annealing algorithm for solving the job shop scheduling problem
The job shop scheduling problem (JSSP) is a popular NP-hard scheduling problem that simulates the scheduling problems of different real-world applications in fields such as manufacturing, engineering, and planning. In general, many optimization-...
Superblock-based performance optimization for Sunway Math Library on SW26010 many-core processor
The SW26010 many-core processor is based on the Sunway architecture that is composed of management and computing processing elements (MPE and CPE, respectively), each of which is equipped with a stand-alone math library. The issue is that each ...
Scalable blockchain storage mechanism based on two-layer structure and improved distributed consensus
Existing public blockchain architectures suffer from the difficulty of scaling to support large-scale networks with high TPS, low latency and security. Using the idea of network fragmentation, an improved Raft-based PBFT consensus mechanism is ...
LATOC: an enhanced load balancing algorithm based on hybrid AHP-TOPSIS and OPSO algorithms in cloud computing
Providing required level of service quality in cloud computing is one of the most significant cloud computing challenges because of software and hardware complexities, different features of tasks and computing resources and also, lack of ...
Reinforcement learning for traffic light control with emphasis on emergency vehicles
Traffic lights are an important controlling factor in traffic flows, and good policies will facilitate traffic congestion. A car's waiting time is highly related to the period in which the traffic lights are green or red; thus, a proper ...
An efficient authentication with key agreement procedure using Mittag–Leffler–Chebyshev summation chaotic map under the multi-server architecture
- Chandrashekhar Meshram,
- Rabha W. Ibrahim,
- Sarita Gajbhiye Meshram,
- Sajjad Shaukat Jamal,
- Agbotiname Lucky Imoize
The recent technological advancement and rapid development of computer networks have increased the popularity of remote password authentication protocols. Toward this end, the emphasis has shifted to protocols that apply to smart cards-empowered ...
A neural network-based approach for the performance evaluation of branch prediction in instruction-level parallelism processors
Branch prediction is essential for improving the performance of pipeline processors. As the number of pipeline stages in modern processors increases, an accurate branch prediction is important. Traditional branch predictor uses the concept of ...
Robustness improvement of component-based cloud computing systems
With the increasing popularity of Cloud computing systems, the demand for highly dependable Cloud applications has increased significantly. For this, reliability and availability of Cloud applications are two prominent issues for both the ...
Deep learning in the information service system of agricultural Internet of Things for innovation enterprise
To discuss the application of Internet of Things (IoT) in the agriculture, an agricultural product price prediction model is constructed based on the improved Elman neural network (ENN) of deep learning. Simulation experiment of pest prediction is ...
Exploring the Internet of Things sequence-structure detection and supertask network generation of temporal-spatial-based graph convolutional neural network
The study is designed to improve the efficiency of Internet of Things (IoT) structure detection and achieve the smooth operation of IoT networks. First, the connection between the IoT network structure and maxdegree is investigated based on ...
Best path in mountain environment based on parallel A* algorithm and Apache Spark
Pathfinding problem has several applications in our life and widely used in virtual environments. It has different goals such as shortest path, secure path, or optimal path. Pathfinding problem deals with a large amount of data since it considers ...
Caching-based task scheduling for edge computing in intelligent manufacturing
Tasks have high requirements for response delay and security in intelligent manufacturing. Industrial data have the characteristics of high privacy. However, cloud services are difficult to implement for low latency-sensitive applications and ...
Parallel multi-objective optimization approaches for protein encoding
One of the main challenges in synthetic biology lies in maximizing the expression levels of a protein by encoding it with multiple copies of the same gene. This task is often conducted under conflicting evaluation criteria, which motivates the ...
Handoff calls’ joining behavior and incentive mechanism in wireless cellular networks with retrial orbit
In wireless cellular networks, handoff is a key element in providing quality of service and supporting mobility for users. There is an interaction between wireless cellular networks and handoff calls which strategically act to achieve their own ...
A MapReduce-based K-means clustering algorithm
The partitioning-based k-means clustering is one of the most important clustering algorithms. However, in big data environment, it faces the problems of random selection of initial cluster centers randomly, expensive communication overhead among ...
A multi-label ensemble predicting model to service recommendation from social media contents
Consumer sentiment is one of the essential measures of predictive recommendations in travel and tourism. Nowadays, a massive amount of data is available on the online platform related to consumer sentiment, which may help draw insights into how ...
The potential of wind energy via an intelligent IoT-oriented assessment
In contemporary times, renewable energy reliability has been an important field of research that is combined with the Internet of Things (IoT) including the opportunities for improving and challenging the work. Wind energy harvesting in IoT (WHIoT)...
Performance-enhanced real-time lifestyle tracking model based on human activity recognition (PERT-HAR) model through smartphones
The identification of human actions and their representation and categorization in an automated system through training and learning is considered the human activity recognition (HAR) process. Tracking systems capture and read human actions ...
Development of a yoga posture coaching system using an interactive display based on transfer learning
Yoga is a form of exercise that is beneficial for health, focusing on physical, mental, and spiritual connections. However, practicing yoga and adopting incorrect postures can cause health problems, such as muscle sprains and pain. In this study, ...
Aerial face recognition and absolute distance estimation using drone and deep learning
Because of the rise of deep learning and neural networks, algorithms based on deep learning have also been developed and subtly applied in daily life. This paper hoped to use neural network-based face recognition with absolute distance estimation ...