Transmission Control Method to Realize Efficient Data Retention in Low Vehicle Density Environments

Author(s):  
Ichiro Goto ◽  
Daiki Nobayashi ◽  
Kazuya Tsukamoto ◽  
Takeshi Ikenaga ◽  
Myung Lee
2021 ◽  
Vol E104.D (4) ◽  
pp. 508-512
Author(s):  
Ichiro GOTO ◽  
Daiki NOBAYASHI ◽  
Kazuya TSUKAMOTO ◽  
Takeshi IKENAGA ◽  
Myung LEE

Author(s):  
Shumpei YAMASAKI ◽  
Daiki NOBAYASHI ◽  
Kazuya TSUKAMOTO ◽  
Takeshi IKENAGA ◽  
Myung J. LEE

2018 ◽  
Vol 30 (4) ◽  
pp. 14-31 ◽  
Author(s):  
Suyel Namasudra ◽  
Pinki Roy

This article describes how nowadays, cloud computing is one of the advanced areas of Information Technology (IT) sector. Since there are many hackers and malicious users on the internet, it is very important to secure the confidentiality of data in the cloud environment. In recent years, access control has emerged as a challenging issue of cloud computing. Access control method allows data accessing of an authorized user. Existing access control schemes mainly focus on the confidentiality of the data storage. In this article, a novel access control scheme has been proposed for efficient data accessing. The proposed scheme allows reducing the searching cost and accessing time, while providing the data to the user. It also maintains the security of the user's confidential data.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Weimin Zheng ◽  
Yanxin Li ◽  
Xiaowen Jing ◽  
Shangkun Liu

The issue of adaptive practical finite-time (FT) congestion control for the transmission control protocol/active queue management (TCP/AQM) network with unknown hysteresis and external disturbance is considered in this paper. A finite-time congestion controller is designed by the backstepping technique and the adaptive neural control method. This controller guarantees that the queue length tracks the desired queue in finite-time, and it is semiglobally practical finite-time stable (SGPFS) for all the signals of the closed-loop system. At last, the simulation results show that the control strategy is effective.


2020 ◽  
Author(s):  
Harsh Maheshwari ◽  
Shreyas Shetty ◽  
Nayana Bannur ◽  
Srujana Merugu

AbstractShaping an epidemic with an adaptive contact restriction policy that balances the disease and socioeconomic impact has been the holy grail during the COVID-19 pandemic. Most of the existing work on epidemiological models [40, 11, 17, 7] focuses on scenario-based forecasting via simulation but techniques for explicit control of epidemics via an analytical framework are largely missing. In this paper, we consider the problem of determining the optimal policy for transmission control assuming SIR dynamics [28], which is the most widely used epidemiological paradigm. We first demonstrate that the SIR model with infectious patients and susceptible contacts (i.e., product of transmission rate and susceptible population) interpreted as predators and prey respectively reduces to a Lotka-Volterra (LV) predator-prey model [8]. The modified SIR system (LVSIR) has a stable equilibrium point, an “energy” conservation property, and exhibits bounded cyclic behaviour similar to an LV system. This mapping permits a theoretical analysis of the control problem supporting some of the recent simulation-based studies [16, 29] that point to the benefits of periodic interventions. We use a control-Lyapunov approach to design adaptive control policies (CoSIR) to nudge the SIR model to the desired equilibrium that permits ready extensions to richer compartmental models. We also describe a practical implementation of this transmission control method by approximating the ideal control with a finite, but a time-varying set of restriction levels and provide simulation results to demonstrate its efficacy.


Author(s):  
Kanika Monga ◽  
Kunal Harbhajanka ◽  
Arush Srivastava ◽  
Nitin Chaturvedi ◽  
S. Gurunarayanan

Most of today’s IoT-based computing systems offer an opportunity to build smarter systems for application areas such as healthcare monitoring and wireless sensor nodes. Since these systems are energy limited and remain idle for most of the time, they suffer from large leakage power dissipation. Another problem faced by such computing systems is sporadic power failures when employed with energy harvesters where the system loses its current state and needs long reinitialization time. To address these problems, this work combines asynchronous design techniques with nonvolatility to achieve ultra-low power operation during active mode and data retention during power failure. This paper first presents a detailed analysis of different implementations of volatile c-element and compares their performance in terms of power and delay. Then one of the implementations is selected for nonvolatile design of a hybrid c-element using emerging spin transfer torque–magnetic tunnel junction (STT–MTJ) technology which allows energy-efficient data retention during idle mode/power-off mode and during sudden power failures. Using this hybrid c-element, we design a novel nonvolatile weak conditioned half-buffer. The extensive analysis of these designs with different design metrics is performed at the circuit level using Synopsys HSPICE circuit simulator.


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