[go: up one dir, main page]

Mekala et al., 2020 - Google Patents

Resource offload consolidation based on deep-reinforcement learning approach in cyber-physical systems

Mekala et al., 2020

View PDF
Document ID
4242686831996465361
Author
Mekala M
Jolfaei A
Srivastava G
Zheng X
Anvari-Moghaddam A
Viswanathan P
Publication year
Publication venue
IEEE Transactions on Emerging Topics in Computational Intelligence

External Links

Snippet

In cyber-physical systems, it is advantageous to leverage cloud with edge resources to distribute the workload for processing and computing user data at the point of generation. Services offered by cloud are not flexible enough against variations in the size of underlying …
Continue reading at core.ac.uk (PDF) (other versions)

Classifications

    • 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]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
    • 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]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/5044—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering hardware capabilities
    • 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]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
    • 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]
    • G06F9/5061—Partitioning or combining of resources
    • 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]
    • G06F9/5083—Techniques for rebalancing the load in a distributed system
    • 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
    • G06F9/48—Programme initiating; Programme switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
    • 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
    • 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
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • 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
    • 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
    • H04L67/10—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network

Similar Documents

Publication Publication Date Title
Mekala et al. Resource offload consolidation based on deep-reinforcement learning approach in cyber-physical systems
Shen et al. Dependency-aware task offloading and service caching in vehicular edge computing
Liu et al. Multiobjective optimization for computation offloading in fog computing
Mishra et al. A collaborative computation and offloading for compute-intensive and latency-sensitive dependency-aware tasks in dew-enabled vehicular fog computing: A federated deep Q-learning approach
Kim et al. Collaborative task scheduling for IoT-assisted edge computing
Tang et al. Joint computation offloading and resource allocation under task-overflowed situations in mobile-edge computing
Hasan et al. A krill herd behaviour inspired load balancing of tasks in cloud computing
Yu et al. Efficient task sub-delegation for crowdsourcing
Zhou et al. Digital twin-empowered network planning for multi-tier computing
Amer et al. An optimized collaborative scheduling algorithm for prioritized tasks with shared resources in mobile-edge and cloud computing systems
Pacini et al. Dynamic scheduling based on particle swarm optimization for cloud-based scientific experiments
Xu et al. Energy or accuracy? Near-optimal user selection and aggregator placement for federated learning in MEC
Duan et al. Resource management for intelligent vehicular edge computing networks
Consul et al. FLBCPS: Federated learning based secured computation offloading in blockchain-assisted cyber-physical systems
Siar et al. An effective game theoretic static load balancing applied to distributed computing
Nguyen et al. Flexible computation offloading in a fuzzy-based mobile edge orchestrator for IoT applications
Kumar et al. Deadline-aware cost and energy efficient offloading in mobile edge computing
Tennakoon et al. Cloud-based load balancing using double Q-learning for improved Quality of Service
Xu et al. Online learning algorithms for offloading augmented reality requests with uncertain demands in MECs
Xu et al. Learning-driven algorithms for responsive AR offloading with non-deterministic rewards in metaverse-enabled MEC
Dechouniotis et al. A control‐theoretic approach towards joint admission control and resource allocation of cloud computing services
CN114466023B (en) Computing service dynamic pricing method and system for large-scale edge computing system
Sreelatha et al. Hybrid Electro search beetle optimization based task scheduling and game theory SOA based resource allocation in multi cloud computing
Rao et al. A Flawless QoS Aware Task Offloading in IoT Driven Edge Computing System using Chebyshev Based Sand Cat Swarm Optimization
Li et al. Delay-aware resource allocation for data analysis in cloud-edge system