.png){kind=icon}
Return
Energy-aware MAC protocol for data differentiated services in sensor-cloud computing
.png){kind=icon}
OA
AI
DOI：10.1186/s13677-020-00196-5.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The energy-aware MAC protocol is the basic communication protocol for device-to-device communication in sensor-cloud computing and facilitates data sensing, computing, and sharing for applications. Transmitting high-priority data to control centers quickly to manage emergencies is essential for sensor-cloud applications. In this paper, a Dynamic Wait time-based MAC (DWT-MAC) protocol is proposed for data differentiated services of a sensor-cloud system (SCS). The DWT-MAC protocol is novel in that it changes the receiver wait time, which has been fixed in previous MAC protocols, and it reduces the delay in data transmission by dynamically adjusting the wait time. In the DWT-MAC protocol, the wait time changes according to the number of senders, which can ensure that it always approaches the optimal value. A dynamic time adjustment algorithm, which causes the wait time to always trail the optimal value, is proposed to reduce delays. While the DWT-MAC protocol cannot ensure wait times of the optimal value, it can ensure that it quickly comes close to the optimal value, which is suitable for dynamically changing networks. Extensive experiments show that the DWT-MAC protocol reduces the average delay in the transmission of data of the highest priority by 49.3%.
Keywords:
Edge cloud
Energy-aware
DWT-MAC protocol
Delay differentiated services
Lifetime
Journal
J
IF:
4.3
Papers:
764
Citations:
2.2K
Organization
Cited Papers
Performance Improvement of QoS-Enabled WLANs Using Adaptive Contention Window Backoff Algorithm
PREAI
ShareSaveVehicles joint UAVs to acquire and analyze data for topology discovery in large-scale IoT systems
PREAI
ShareSaveShareSaveResource Management at the Network Edge: A Deep Reinforcement Learning Approach.png)
IEEE NETWORK
IEEE NETWORKIF6.3
PREAI
ShareSaveShareSaveShareSave
View more