Xu et al., 2019 - Google Patents
Multiobjective computation offloading for workflow management in cloudlet‐based mobile cloud using NSGA‐IIXu et al., 2019
- Document ID
- 3595272071251976198
- Author
- Xu X
- Fu S
- Yuan Y
- Luo Y
- Qi L
- Lin W
- Dou W
- Publication year
- Publication venue
- Computational Intelligence
External Links
Snippet
Cloudlet is a novel computing paradigm, introduced to the mobile cloud service framework, which moves the computing resources closer to the mobile users, aiming to alleviate the communication delay between the mobile devices and the cloud platform and optimize the …
- 238000005265 energy consumption 0 abstract description 62
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
- G06F9/48—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
-
- 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
- G06F9/485—Task life-cycle, e.g. stopping, restarting, resuming execution
-
- 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
- G06Q10/06—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
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Xu et al. | Multiobjective computation offloading for workflow management in cloudlet‐based mobile cloud using NSGA‐II | |
Peng et al. | Intelligent computation offloading and resource allocation in IIoT with end-edge-cloud computing using NSGA-III | |
Gao et al. | Com-DDPG: Task offloading based on multiagent reinforcement learning for information-communication-enhanced mobile edge computing in the internet of vehicles | |
Gao et al. | Task partitioning and offloading in DNN-task enabled mobile edge computing networks | |
Dai et al. | A probabilistic approach for cooperative computation offloading in MEC-assisted vehicular networks | |
Zhao et al. | Offloading tasks with dependency and service caching in mobile edge computing | |
Chen et al. | Computation offloading and task scheduling for DNN-based applications in cloud-edge computing | |
Deng et al. | User-centric computation offloading for edge computing | |
Abd Elaziz et al. | IoT workflow scheduling using intelligent arithmetic optimization algorithm in fog computing | |
Li et al. | Performance evaluation and optimization of a task offloading strategy on the mobile edge computing with edge heterogeneity | |
Chen et al. | Cache-assisted collaborative task offloading and resource allocation strategy: A metareinforcement learning approach | |
Sufyan et al. | Computation offloading for smart devices in fog-cloud queuing system | |
Iturriaga et al. | Multiobjective evolutionary algorithms for energy and service level scheduling in a federation of distributed datacenters | |
Biswas et al. | A novel scheduling with multi-criteria for high-performance computing systems: an improved genetic algorithm-based approach | |
Li et al. | Task computation offloading for multi-access edge computing via attention communication deep reinforcement learning | |
Wu et al. | Request dispatching for minimizing service response time in edge cloud systems | |
Peng et al. | Energy‐and Resource‐Aware Computation Offloading for Complex Tasks in Edge Environment | |
Qin et al. | User‐Edge Collaborative Resource Allocation and Offloading Strategy in Edge Computing | |
Gao et al. | Com-DDPG: A multiagent reinforcement learning-based offloading strategy for mobile edge computing | |
Huang et al. | Computation offloading for multimedia workflows with deadline constraints in cloudlet-based mobile cloud | |
Yang et al. | Perllm: Personalized inference scheduling with edge-cloud collaboration for diverse llm services | |
Huang et al. | Mobility-aware computation offloading with load balancing in smart city networks using mec federation | |
Li et al. | A multi-objective task offloading based on BBO algorithm under deadline constrain in mobile edge computing | |
Talha et al. | A chaos opposition‐based dwarf mongoose approach for workflow scheduling in cloud | |
Liu et al. | Energy‐aware virtual machine consolidation based on evolutionary game theory |