A5065757920- Cloud Computing and Resource Management
- Scheduling and Timetabling Solutions
- Scheduling and Optimization Algorithms
- IoT and Edge/Fog Computing
- Vehicle Routing Optimization Methods
- Transportation and Mobility Innovations
- Network Security and Intrusion Detection
- Advanced Manufacturing and Logistics Optimization
- Spam and Phishing Detection
- Energy Efficient Wireless Sensor Networks
- Constraint Satisfaction and Optimization
- Sleep and Work-Related Fatigue
- Maritime Navigation and Safety
- Consumer Market Behavior and Pricing
- Water Quality Monitoring Technologies
- Auction Theory and Applications
- Industrial Engineering and Technologies
- Advanced Neural Network Applications
- Optimization and Search Problems
- Electric Power Systems and Control
- IoT-based Smart Home Systems
- Internet Traffic Analysis and Secure E-voting
- Metaheuristic Optimization Algorithms Research
- Blockchain Technology Applications and Security
- Distributed and Parallel Computing Systems
University of Regina
2021-2024
Qazvin Islamic Azad University
2019
Sensor nodes spend the most of their limited energy on communicating with environmental information gathered in receivers. Hence, it is important to determine optimal monitoring sensor and flow paths destination sink order survive networks. Additionally, heavy traffic load for transferring packets closer increases consumption reduces battery life. It desirable reduce between sink. The main goal extend network lifetime through extending operating sensors as well data from super node In this...
Abstract The cloud computing systems are sorts of shared collateral structure which has been in demand from its inception. In these systems, clients able to access existing services based on their needs and without knowing where the service is located how it delivered, only pay for used. Like other there challenges system. Because a wide array variety available this system, can be said that issue scheduling and, course, energy consumption essential challenge Therefore, should properly...
In a real manufacturing environment, the set of tasks that should be scheduled is changing over time, which means scheduling problems are dynamic. Also, in order to adapt systems with fluctuations, such as machine failure and create bottleneck machines, various flexibilities considered this system. For first research, we consider operational flexibility due Parallel Machines (PM) non-uniform speed Dynamic Job Shop (DJS) field Flexible Job-Shop (FDJSPM) model. After modeling problem, an...
One of the most applicable versions Vehicle Routing Problem (VRP) which has been widely studied in logistic services is Capacitated (CVRP). There are many algorithms to solve CVRP minimize total travelled distance. Some recent and efficient metaheuristic capable generating solutions within 0.5% 1% gap from optimum for instance problems adopted literature considering hundreds or thousands demand points. In this contribution, a novel hybrid algorithm proposed based on Gravitational Emulation...
Mobile devices are used by numerous applications that continuously need computing power to grow. Due limited resources for complex computing, offloading, a service offered mobile devices, is commonly in cloud computing. In Cloud Computing (MCC), offloading decides where execute the tasks efficiently maximize benefits. Hence, we represent as Task Scheduling Problem (TSP). This latter Multi-Objective Optimization (MOO) problem goal find best schedule processing source tasks, while minimizing...
The Multi-Depot Vehicle Routing Problem (MD-VRP) is a known routing problem whose goal to minimize the total cost while visiting set of routes from their respective depots. We consider particular application MDVRP, called Electricity Technician Dispatch (ETDP), in which we look for optimal tours technicians provide services customers. To overcome inherent exponential time this NP-hard problem, propose hybrid method structured two stages. In first phase, rely on clustering algorithm identify...