Nothing Special   »   [go: up one dir, main page]

Huang et al., 2014 - Google Patents

When backpressure meets predictive scheduling

Huang et al., 2014

View PDF
Document ID
4443430053832049985
Author
Huang L
Zhang S
Chen M
Liu X
Publication year
Publication venue
Proceedings of the 15th ACM international symposium on Mobile ad hoc networking and computing

External Links

Snippet

Motivated by the increasing popularity of learning and predicting human user behavior in communication and computing systems, in this paper, we investigate the fundamental benefit of predictive scheduling, ie, predicting and pre-serving arrivals, in controlled …
Continue reading at arxiv.org (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
    • G06F9/48—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
    • G06F9/50—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
    • 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
    • G06F17/50—Computer-aided design
    • 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
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • 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
    • 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
    • H04L67/32—Network-specific arrangements or communication protocols supporting networked applications for scheduling or organising the servicing of application requests, e.g. requests for application data transmissions involving the analysis and optimisation of the required network resources
    • H04L67/322—Network-specific arrangements or communication protocols supporting networked applications for scheduling or organising the servicing of application requests, e.g. requests for application data transmissions involving the analysis and optimisation of the required network resources whereby quality of service [QoS] or priority requirements are taken into account
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
    • 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
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F2209/00—Indexing scheme relating to G06F9/00
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application

Similar Documents

Publication Publication Date Title
Huang et al. When backpressure meets predictive scheduling
Guo et al. Dynamic performance optimization for cloud computing using M/M/m queueing system
Jiang et al. Optimal cloud resource auto-scaling for web applications
Lu et al. RVLBPNN: A workload forecasting model for smart cloud computing
Vakilinia et al. Modeling of the resource allocation in cloud computing centers
Chiang et al. Profit Optimization in SLA‐Aware Cloud Services with a Finite Capacity Queuing Model
Bi et al. SLA-based optimisation of virtualised resource for multi-tier web applications in cloud data centres
Alam et al. A reliability-based resource allocation approach for cloud computing
Dou et al. An energy‐aware virtual machine scheduling method for service QoS enhancement in clouds over big data
Cheng et al. Proscale: Proactive autoscaling for microservice with time-varying workload at the edge
Rahmani et al. Burst‐aware virtual machine migration for improving performance in the cloud
Khazaei Performance modeling of cloud computing centers
Chang et al. Reward-based Markov chain analysis adaptive global resource management for inter-cloud computing
Carvalho et al. Edge servers placement in mobile edge computing using stochastic Petri nets
Durga et al. Context-aware adaptive resource provisioning for mobile clients in intra-cloud environment
Zhang et al. Proactive serving decreases user delay exponentially: The light-tailed service time case
Zohrati et al. Flexible approach to schedule tasks in cloud‐computing environments
Swain et al. Efficient straggler task management in cloud environment using stochastic gradient descent with momentum learning-driven neural networks
Luo et al. An enhanced workflow scheduling strategy for deadline guarantee on hybrid grid/cloud infrastructure
Huang The value-of-information in matching with queues
Yang et al. Performance Prediction Based EX-QoS Driven Approach for Adaptive Service Composition.
Chen et al. Dynamic service request scheduling for mobile edge computing systems
Zhang et al. Two-level task scheduling with multi-objectives in geo-distributed and large-scale SaaS cloud
Nethaji et al. Differential Grey Wolf Load‐Balanced Stochastic Bellman Deep Reinforced Resource Allocation in Fog Environment
Shan et al. Modeling and performance analysis of a multiserver multiqueue system on the grid