Chen et al., 2019 - Google Patents
TOFFEE: Task offloading and frequency scaling for energy efficiency of mobile devices in mobile edge computingChen et al., 2019
View PDF- Document ID
- 9867765465834048543
- Author
- Chen Y
- Zhang N
- Zhang Y
- Chen X
- Wu W
- Shen X
- Publication year
- Publication venue
- IEEE Transactions on Cloud Computing
External Links
Snippet
As an emerging computing paradigm, mobile edge computing (MEC) can improve users' service experience by provisioning the cloud resources close to the mobile devices. With MEC, computation-intensive tasks can be processed on the MEC servers, which can greatly …
- 235000015149 toffees 0 title 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W72/00—Local resource management, e.g. wireless traffic scheduling or selection or allocation of wireless resources
- H04W72/12—Dynamic Wireless traffic scheduling; Dynamically scheduled allocation on shared channel
- H04W72/1205—Schedule definition, set-up or creation
- H04W72/1221—Schedule definition, set-up or creation based on age of data to be sent
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W52/00—Power Management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W52/00—Power Management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0203—Power saving arrangements in the radio access network or backbone network of wireless communication networks
- H04W52/0206—Power saving arrangements in the radio access network or backbone network of wireless communication networks in access points, e.g. base stations
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W4/00—Mobile application services or facilities specially adapted for wireless communication networks
- H04W4/06—Selective distribution or broadcast application services; Mobile application services to user groups; One-way selective calling services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W72/00—Local resource management, e.g. wireless traffic scheduling or selection or allocation of wireless resources
- H04W72/04—Wireless resource allocation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W28/00—Network traffic or resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
-
- 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
-
- 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 |
---|---|---|
Chen et al. | TOFFEE: Task offloading and frequency scaling for energy efficiency of mobile devices in mobile edge computing | |
Chen et al. | Energy efficient dynamic offloading in mobile edge computing for internet of things | |
Wang et al. | Energy-efficient computation offloading and resource allocation for delay-sensitive mobile edge computing | |
Zhang et al. | Distributed energy management for multiuser mobile-edge computing systems with energy harvesting devices and QoS constraints | |
Chen et al. | Dynamic computation offloading in edge computing for internet of things | |
Yang et al. | Communication-constrained mobile edge computing systems for wireless virtual reality: Scheduling and tradeoff | |
Guo et al. | Energy-efficient dynamic computation offloading and cooperative task scheduling in mobile cloud computing | |
Guo et al. | Online learning based computation offloading in MEC systems with communication and computation dynamics | |
Masoudi et al. | Device vs edge computing for mobile services: Delay-aware decision making to minimize power consumption | |
Liu et al. | Delay-optimal computation task scheduling for mobile-edge computing systems | |
Huang et al. | A dynamic offloading algorithm for mobile computing | |
Li et al. | Energy-efficient mobile edge computing under delay constraints | |
Li et al. | On efficient offloading control in cloud radio access network with mobile edge computing | |
Sun et al. | Energy-efficient multimedia task assignment and computing offloading for mobile edge computing networks | |
Liu et al. | Joint task offloading and resource allocation for obtaining fresh status updates in multi-device MEC systems | |
Jian et al. | Joint computation offloading and resource allocation in C-RAN with MEC based on spectrum efficiency | |
Chang et al. | Offloading decision in edge computing for continuous applications under uncertainty | |
Wei et al. | Optimal offloading in fog computing systems with non-orthogonal multiple access | |
Li | Multi-task offloading and resource allocation for energy-efficiency in mobile edge computing | |
Okegbile et al. | A multi-user tasks offloading scheme for integrated edge-fog-cloud computing environments | |
Li et al. | Joint subcarrier and power allocation for OFDMA based mobile edge computing system | |
Zhang et al. | Delay minimized task scheduling in fog-enabled IoT networks | |
Yuchong et al. | Task scheduling in mobile edge computing with stochastic requests and m/m/1 servers | |
Long et al. | Socially-aware energy-efficient task partial offloading in MEC networks with d2d collaboration | |
Li et al. | A trade-off task-offloading scheme in multi-user multi-task mobile edge computing |