An efficient task scheduling and resource allocation in cloud computing by using particle swarm optimization

 Cloud computing offers on-demand availability of computing resources over the Internet. To attract users, cloud providers offer their resources as services at reasonable prices and provide various price models to reflect higher level of quality of service (QoS), which are referred as pricing schemes. k-times anonymous authentication (k-TAA) is an a...

Cloud Computing Cost Optimization Resource Schduling SAAS PAYG

QUANTUM-INSPIRED MACHINE LEARNING FOR 6G FUNDAMENTALS, SECURITY, RESOURCE ALLOCATIONS, CHALLENGES, AND FUTURE RESEARCH DIRECTIONS

 Quantum computing is envisaged as an evolving paradigm for solving computationally complex optimization problems with a large-number factorization and exhaustive search.Recently, there has been a proliferating growth of the size of multi-dimensional datasets, the input-output space dimensionality, and data structures. Hence, the conventional machin...

MACHINE LEARNING 6G FUNDAMENTALS

Deep Reinforcement Learning Based Resource Allocation in Cooperative UAV-Assisted Wireless Networks

 We consider the downlink of an unmanned aerial vehicle (UAV) assisted cellular network consisting of multiple cooperative UAVs, whose operations are coordinated by a central ground controller using wireless fronthaul links, to serve multiple ground user equipments (UEs). A problem of jointly designing UAVs’ positions, transmit beamforming, as well ...

Distributed Resource Allocation for SWIPT-based Cognitive Ad-Hoc Networks

 Energy supplies, spectrum resources, and transmission overheads of wireless nodes are the bottlenecks in decentralized networks (e.g., device-to-device communication networks). In this paper, we study the total power minimization problem of secondary users (SUs) for a multiuser simultaneous wireless information and power transfer-based cognitive ad...

Joint Resource Allocation and Trajectory Optimization with QoS in UAV-based NOMA Wireless Networks

 Replacing base stations with unmanned aerial vehicles (UAVs) to serve the communication of ground users has attracted a lot of attention recently. In this paper, we study the joint resource allocation and UAV trajectory optimization for maximizing the total energy efficiency in UAV-based non-orthogonal multiple access (NOMA) downlink wireless netwo...

Quantum Neural Networks for Resource Allocation in Wireless Communications

 This study exploits a quantum neural network (QNN) for resource allocation in wireless communications. A QNN is presented to reduce time complexity while still maintaining performance. Moreover, a reinforcement-learning-inspired QNN (RL-QNN) is presented to improve the performance. Quantum circuit design of the QNN is presented to ensure the practi...

Multi-Agent DRL for Task Offloading and Resource Allocation in Multi-UAV Enabled IoT Edge Network

 The Internet of Things (IoT) edge network has connected lots of heterogeneous smart devices, thanks to unmanned aerial vehicles (UAVs) and their groundbreaking emerging applications. Limited computational capacity and energy availability have been major factors hindering the performance of edge user equipment (UE) and IoT devices in IoT edge networ...

NPRACH-Aware Link Adaptation and Uplink Resource Allocation in NB-IoT Cellular Networks

 In narrowband Internet of Things (NB-IoT), a link adaptation technique can be performed, considering multiple resource unit types, repetition numbers, and modulation-coding schemes, to enhance transmission reliability. Then, a base station should allocate downlink and uplink resources for each device using the link adaptation decision to transmit d...

Fog-enabled Joint Computation, Communication and Caching Resource Sharing for Energy-Efficient IoT Data Stream Processing

 Fog/edge computing has been recently regarded as a promising approach for supporting emerging mission-critical Internet of Things (IoT) applications on capacity and battery constrained devices. By harvesting and collaborating a massive crowd of devices in close proximity for computation, communication and caching resource sharing (i.e., 3C resource...

Resource Allocation in Uplink NOMA-IoT Networks A Reinforcement-Learning Approach

 Non-orthogonal multiple access (NOMA) exploits the potential of power domain to enhance the connectivity for Internet of Things (IoT). Due to time-varying communication channels, dynamic user clustering is a promising method to increase the throughput of NOMA-IoT networks. This paper develops an intelligent resource allocation scheme for uplink NOM...

Computation Migration Oriented Resource Allocation in Mobile Social Clouds

 The rapid growth of mobile device (e.g., smart phone and bracelet) has spawned a lot of new applications, during which the requirements of applications are increasing, while the capacities of some mobile devices are still limited. Such contradiction drives the emergency of computation migration among mobile edge devices, which is a lack of research...

Robust Optimization Model for Primary and Backup Resource Allocation in Cloud Providers

 This paper proposes a backup resource allocation model that provides a probabilistic protection for primary physical machines in a cloud provider to minimize the required total capacity. When any random failure occurs, workloads are transferred to preplanned and dedicated backup physical machines for prompt recovery. In the proposed model, a probab...

Charge-Then-Cooperate Secure Resource Allocation for Wireless-Powered Relay Networks with Wireless Energy Transfer

 This correspondence studies resource allocation for a wireless-powered relay network, where a hybrid relay with constant energy supply assists an energy-constrained source to send confidential information to a destination in the presence of an eavesdropper. We propose a novel transmission protocol termed charge-then-cooperate to support secure comm...

A Machine Learning Resource Allocation Solution to Improve Video Quality in Remote Education

 The current global pandemic crisis has unquestionably disrupted the higher education sector, forcing educational institutions to rapidly embrace technology-enhanced learning. However, the COVID-19 containment measures that forced people to work or stay at home, have determined a significant increase in the Internet traffic that puts tremendous pres...

Coordinates-based Resource Allocation Through Supervised Machine Learning

 Appropriate allocation of system resources is essential for meeting the increased user-traffic demands in the next generation wireless technologies.Traditionally, the system relies on channel state information (CSI) of the users for optimizing the resource allocation, which becomes costly for fast-varying channel conditions.Considering that future ...

A Cooperative Coevolution Genetic Programming Hyper-Heuristic Approach for On-line resource Allocation in Container based Clouds

 Containers are lightweight and provide the potential to reduce more energy consumption of data centers than Virtual Machines (VMs) in container-based clouds. The on-line resource allocation is the most common operation in clouds. However, the on-line Resource Allocation in Container-based clouds (RAC) is new and challenging because of its two-level...