Liang et al., 2019 - Google Patents
A novel adaptive resource allocation model based on SMDP and reinforcement learning algorithm in vehicular cloud systemLiang et al., 2019
- Document ID
- 3655275498922394722
- Author
- Liang H
- Zhang X
- Zhang J
- Li Q
- Zhou S
- Zhao L
- Publication year
- Publication venue
- IEEE Transactions on Vehicular Technology
External Links
Snippet
In this paper, we propose a novel adaptive cloud resource allocation model based on Semi- Markov Decision Process (SMDP) and Reinforcement Learning (RL) algorithm in vehicular cloud system. The issue of adaptive resource allocation for vehicular request is formed as an …
- 230000003044 adaptive 0 title abstract description 50
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic regulation in packet switching networks
- H04L47/70—Admission control or resource allocation
- H04L47/80—Actions related to the nature of the flow or the user
- H04L47/805—QOS or priority aware
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/54—Store-and-forward switching systems
- H04L12/56—Packet switching systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic regulation in packet switching networks
- H04L47/70—Admission control or resource allocation
- H04L47/82—Miscellaneous aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic regulation in packet switching networks
- H04L47/10—Flow control or congestion control
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce, e.g. shopping or e-commerce
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network-specific arrangements or communication protocols supporting networked applications
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Liang et al. | A novel adaptive resource allocation model based on SMDP and reinforcement learning algorithm in vehicular cloud system | |
Dai et al. | Task co-offloading for D2D-assisted mobile edge computing in industrial internet of things | |
Shi et al. | Priority-aware task offloading in vehicular fog computing based on deep reinforcement learning | |
Xu et al. | A method based on the combination of laxity and ant colony system for cloud-fog task scheduling | |
Chen et al. | Dependency-aware computation offloading for mobile edge computing with edge-cloud cooperation | |
Sun et al. | BARGAIN-MATCH: A game theoretical approach for resource allocation and task offloading in vehicular edge computing networks | |
Baek et al. | Managing fog networks using reinforcement learning based load balancing algorithm | |
Deng et al. | Task allocation algorithm and optimization model on edge collaboration | |
Lin et al. | Resource allocation in vehicular cloud computing systems with heterogeneous vehicles and roadside units | |
Sun et al. | Autonomous resource slicing for virtualized vehicular networks with D2D communications based on deep reinforcement learning | |
Zhao et al. | Contract-based computing resource management via deep reinforcement learning in vehicular fog computing | |
Zhang et al. | A hierarchical game framework for resource management in fog computing | |
Kim et al. | Multi-agent reinforcement learning-based resource management for end-to-end network slicing | |
Nan et al. | Cost-effective processing for delay-sensitive applications in cloud of things systems | |
Yuan et al. | Edge-enabled wbans for efficient qos provisioning healthcare monitoring: A two-stage potential game-based computation offloading strategy | |
Sun | Research on resource allocation of vocal music teaching system based on mobile edge computing | |
Xiao et al. | Consortium blockchain-based computation offloading using mobile edge platoon cloud in internet of vehicles | |
Wu et al. | Online user allocation in mobile edge computing environments: A decentralized reactive approach | |
Wu et al. | Load balance guaranteed vehicle-to-vehicle computation offloading for min-max fairness in VANETs | |
Khumalo et al. | Reinforcement learning-based resource management model for fog radio access network architectures in 5G | |
Ko et al. | Distributed device-to-device offloading system: Design and performance optimization | |
Boukerche et al. | Vehicular cloud network: A new challenge for resource management based systems | |
Du et al. | Auction-based data transaction in mobile networks: Data allocation design and performance analysis | |
Li et al. | Entropy-based reinforcement learning for computation offloading service in software-defined multi-access edge computing | |
Cui et al. | Multiagent reinforcement learning-based cooperative multitype task offloading strategy for internet of vehicles in B5G/6G network |