[go: up one dir, main page]

Xu et al., 2019 - Google Patents

An energy-aware computation offloading method for smart edge computing in wireless metropolitan area networks

Xu et al., 2019

Document ID
15973167453379675201
Author
Xu X
Li Y
Huang T
Xue Y
Peng K
Qi L
Dou W
Publication year
Publication venue
Journal of Network and Computer Applications

External Links

Snippet

Currently, the booming popularity and growth of mobile devices in urban cities leads to the surge of various computation-intensive mobile applications, such as virtual reality and online video, which are strict with the computing capability and battery life of the mobile devices. To …
Continue reading at www.sciencedirect.com (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]
    • G06F9/5061—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
    • G06F9/5088—Techniques for rebalancing the load in a distributed system involving task migration
    • 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]
    • G06F9/5094—Allocation of resources, e.g. of the central processing unit [CPU] where the allocation takes into account power or heat criteria
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—INDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00—Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/10—Energy efficient computing
    • Y02B60/14—Reducing energy-consumption by means of multiprocessor or multiprocessing based techniques, other than acting upon the power supply
    • Y02B60/142—Resource allocation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—INDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00—Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/10—Energy efficient computing
    • Y02B60/16—Reducing energy-consumption in distributed systems
    • Y02B60/167—Resource sharing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a programme unit and a register, e.g. for a simultaneous processing of several programmes
    • 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"
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—INDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00—Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/50—Techniques for reducing energy-consumption in wireless communication networks

Similar Documents

Publication Publication Date Title
Xu et al. An energy-aware computation offloading method for smart edge computing in wireless metropolitan area networks
Qi et al. A QoS-aware virtual machine scheduling method for energy conservation in cloud-based cyber-physical systems
Chen et al. Multitask offloading strategy optimization based on directed acyclic graphs for edge computing
Lu et al. Optimization of lightweight task offloading strategy for mobile edge computing based on deep reinforcement learning
Xu et al. An IoT-oriented data placement method with privacy preservation in cloud environment
US8144590B2 (en) Distributed resource allocation in stream processing systems
Chen et al. Deploying data-intensive applications with multiple services components on edge
CN113918240B (en) Task offloading method and device
CN114741191B (en) A multi-resource allocation method for computationally intensive task correlation
Ren et al. Collaborative edge computing and caching with deep reinforcement learning decision agents
Wen et al. Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computing
CN113867843B (en) Mobile edge computing task unloading method based on deep reinforcement learning
Tong et al. Response time and energy consumption co-offloading with SLRTA algorithm in cloud–edge collaborative computing
CN117112207A (en) A hybrid resource scheduling method based on deep reinforcement learning
Zhang et al. Energy minimization task offloading mechanism with edge-cloud collaboration in IoT networks
Xu et al. A meta reinforcement learning-based virtual machine placement algorithm in mobile edge computing
CN114745386A (en) A neural network segmentation and unloading method in multi-user edge intelligence scenarios
Chen et al. Tensor-based Lyapunov deep neural networks offloading control strategy with cloud-fog-edge orchestration
Zhang et al. Resource scheduling of green communication network for large sports events based on edge computing
Reddy et al. A Dependency-Aware task offloading in IoT-based Edge Computing system using an Optimized Deep Learning Approach
Yu et al. Drag-JDEC: A deep reinforcement learning and graph neural network-based job dispatching model in edge computing
Xu et al. Towards risk-averse edge computing with deep reinforcement learning
Huang et al. Computation offloading for multimedia workflows with deadline constraints in cloudlet-based mobile cloud
Yang et al. An energy-efficient virtual machine placement and route scheduling scheme in data center networks
CN107092339A (en) The task shunt method of mobile cloud computing node isomery