Optimal Energy Efficiency Data Dissemination Strategy Based on Optimal Stopping Theory in Mobile Network

2018 ◽  
pp. 41-52 ◽  
Author(s):  
Gaocai Wang ◽  
Ying Peng ◽  
Qifei Zhao
Keyword(s):  
Energy Efficiency ◽  
Optimal Stopping ◽  
Data Dissemination ◽  
Mobile Network ◽  
Dissemination Strategy ◽  
Optimal Energy ◽  
Optimal Stopping Theory ◽  
Efficiency Data

scholarly journals A Data Transmission Strategy with Energy Minimization Based on Optimal Stopping Theory in Mobile Cloud Computing

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Xin Zheng ◽  
Yu Nan ◽  
Fangsu Wang ◽  
Ruiqing Song ◽  
Gang Zheng ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Optimal Stopping ◽  
Data Transmission ◽  
Mobile Cloud Computing ◽  
Rapid Development ◽  
Average Energy ◽  
Mobile Cloud ◽  
Mobile Terminals ◽  
Optimal Stopping Theory

Considering the widespread use of mobile devices and the increased performance requirements of mobile users, shifting the complex computing and storage requirements of mobile terminals to the cloud is an effective way to solve the limitation of mobile terminals, which has led to the rapid development of mobile cloud computing. How to reduce and balance the energy consumption of mobile terminals and clouds in data transmission, as well as improve energy efficiency and user experience, is one of the problems that green cloud computing needs to solve. This paper focuses on energy optimization in the data transmission process of mobile cloud computing. Considering that the data generation rate is variable, because of the instability of the wireless connection, combined with the transmission delay requirement, a strategy based on the optimal stopping theory to minimize the average transmission energy of the unit data is proposed. By constructing a data transmission queue model with multiple applications, an admission rule that is superior to the top candidates is proposed by using secretary problem of selecting candidates with the lowest average absolute ranking. Then, it is proved that the rule has the best candidate. Finally, experimental results show that the proposed optimization strategy has lower average energy per unit of data, higher energy efficiency, and better average scheduling period.

scholarly journals OEDDBOS: An Efficient Data Distributing Strategy with Energy Saving in Sensor-Cloud Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Qifei Zhao ◽  
Gaocai Wang ◽  
Ying Peng ◽  
Yuting Lu
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Optimal Stopping ◽  
Data Distribution ◽  
Average Energy ◽  
Maximization Problem ◽  
Cloud Systems ◽  
Channel Quality ◽  
Optimal Stopping Theory ◽  
Sensor Cloud

Sensor-cloud is a developing technology and popular paradigm for various applications. It integrates wireless sensor into a cloud computing environment. On the one hand, the cloud offers extensive data storage and analytical and processing capabilities not available in sensor nodes. On the other hand, data distribution (such as time synchronization and configuration files) is always an important topic in such sensor-cloud systems, which leads to a rapid increase in energy consumption by sensors. In this paper, we aim to reduce the energy consumption of data dissemination in sensor-cloud systems and study the optimization of energy consumption with time-varying channel quality when multiple nodes use the same channel to transmit data. Suppose that there is a certain probability that the nodes send data for competing channel. And then, they decide to distribute data in terms of channel quality for saving energy after getting the channel successfully whether or not. Firstly, we construct the maximization problem of average energy efficiency for distributing data with delay demand. Then, this maximization problem transferred an optimal stopping problem which generates the optimal stopping rule. At last, the thresholds of the optimal transmission rate in each period are solved by using the optimal stopping theory, and the optimal energy efficiency for data distribution is achieved. Simulation results indicate that the strategy proposed in this paper can to some extent improve average energy efficiency and delivery ratio and enhance energy optimization effect and network performance compared with other strategies.

scholarly journals Towards Optimal Energy Efficiency in Cell-Free Massive MIMO Systems

2021 ◽  
pp. 1-1
Author(s):  
A. Papazafeiropoulos ◽  
H. Q. Ngo ◽  
P. Kourtessis ◽  
S. Chatzinotas ◽  
J. M. Senior
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Optimal Energy

A Note on a Lower Bound for the Multiplicative Odds Theorem of Optimal Stopping

2014 ◽  
Vol 51 (03) ◽  
pp. 885-889 ◽  
Author(s):  
Tomomi Matsui ◽  
Katsunori Ano
Keyword(s):  
Lower Bound ◽  
Optimal Stopping ◽  
Secretary Problem ◽  
Bernoulli Trials ◽  
Optimal Stopping Problem ◽  
Maximum Probability ◽  
Optimal Stopping Rule ◽  
Optimal Probability ◽  
Optimal Stopping Theory ◽  
Special Case

In this note we present a bound of the optimal maximum probability for the multiplicative odds theorem of optimal stopping theory. We deal with an optimal stopping problem that maximizes the probability of stopping on any of the last m successes of a sequence of independent Bernoulli trials of length N, where m and N are predetermined integers satisfying 1 ≤ m < N. This problem is an extension of Bruss' (2000) odds problem. In a previous work, Tamaki (2010) derived an optimal stopping rule. We present a lower bound of the optimal probability. Interestingly, our lower bound is attained using a variation of the well-known secretary problem, which is a special case of the odds problem.

scholarly journals Learn From Optimal Energy-Efficiency Beamforming for SWIPT-Enabled Sensor Cloud System Based on DNN

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Zhe Wang ◽  
Taoshen Li ◽  
Lina Ge ◽  
Yongquan Zhou ◽  
Guifen Zhang ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Cloud System ◽  
Optimal Energy ◽  
Sensor Cloud

scholarly journals An Effective and Efficient Adaptive Probability Data Dissemination Protocol in VANET

Data ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 1 ◽  
Author(s):  
John Sospeter ◽  
Di Wu ◽  
Saajid Hussain ◽  
Tesfanesh Tesfa
Keyword(s):  
Data Dissemination ◽  
Probabilistic Approach ◽  
Mobile Network ◽  
Delivery Ratio ◽  
Network Resources ◽  
Network Resource ◽  
V2v Communication ◽  
End To End Delay ◽  
End To End ◽  
Road Segments

Mobile network topology changes dynamically over time because of the high velocity of vehicles. Therefore, the concept of the data dissemination scheme in a VANET environment has become an issue of debate for many research scientists. The main purpose of VANET is to ensure passenger safety application by considering the critical emergency message. The design of the message dissemination protocol should take into consideration effective data dissemination to provide a high packet data ratio and low end-to-end delay by using network resources at a minimal level. In this paper, an effective and efficient adaptive probability data dissemination protocol (EEAPD) is proposed. EEAPD comprises a delay scheme and probabilistic approach. The redundancy ratio (r) metric is used to explain the correlation between road segments and vehicles’ density in rebroadcast probability decisions. The uniqueness of the EEAPD protocol comes from taking into account the number of road segments to decide which nodes are suitable for rebroadcasting the emergency message. The last road segment is considered in the transmission range because of the probability of it having small vehicle density. From simulation results, the proposed protocol provides a better high-packet delivery ratio and low-packet drop ratio by providing better use of the network resource within low end-to-end delay. This protocol is designed for only V2V communication by considering a beaconless strategy. the simulations in this study were conducted using Ns-3.26 and traffic simulator called “SUMO”.

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