scholarly journals Multi-Connectivity Enhanced Communication-Incentive Distributed Computation Offloading in Vehicular Networks

Electronics ◽  
2021 ◽  
Vol 10 (20) ◽  
pp. 2466
Author(s):  
Kangjie Zhang ◽  
Xiaodong Xu ◽  
Jingxuan Zhang ◽  
Shujun Han ◽  
Bizhu Wang ◽  
...  
Keyword(s):  
Vehicular Networks ◽  
Vehicular Network ◽  
Distributed Computation ◽  
System Level ◽  
Computation Offloading ◽  
System Throughput ◽  
Scheduling Scheme ◽  
Computing Unit ◽  
System Level Simulation ◽  
Flexible Resource

Flexible resource scheduling and network forecast are crucial functions to enhance mobile vehicular network performances. However, BaseStations (BSs) and their computing unit which undertake the functions cannot meet the delay requirement because of limited computation capability. Offloading the time-sensitive functions to User Equipment (UE) is believed to be an effective method to tackle this challenge. The disadvantage of the method is offloading occupies communication resources, which deteriorate the system capability. To better coordinate offloading and communication, a multi-connectivity enhanced joint scheduling scheme for distributed computation offloading and communication resources allocation in vehicular networks is proposed in this article. Computation tasks are divided into many slices and distributed to UEs to aggregate the computation capability. A communication-incentive mechanism is provided for involving UEs to compensate the loss of UEs, while multi-connectivity is adopted to enhance the system throughput. We also defined offloading failure ratio as a conclusive condition for offloading size by analyzing the movement of UEs. By a two-step optimization, the co-scheduling of offloading size and throughput is solved. The system-level simulation results show that the offloading size and throughput of the proposed scheme are larger than comparisons when the time constraint is tight.

A New Congestion Control Algorithm of CDMA Systems

2011 ◽  
Vol 255-260 ◽  
pp. 2220-2223
Author(s):  
Peng Liu
Keyword(s):  
Congestion Control ◽  
Control Algorithm ◽  
Optimal Solution ◽  
System Level ◽  
System Throughput ◽  
System Level Simulation ◽  
Congestion Control Algorithm ◽  
Non Linear ◽  
Set Up ◽  
Code Division Multiple

A new congestion control algorithm of code division multiple access (CDMA) is developed to reduce the cost of system. Firstly,the paper defines the utility function of resource throughout,and then set up the mathematics model according to the wireless resource characteristic. In the approach only the non-linear compensating term, solution of a sequence of adjoint vector differential equations, is required iteration. By taking the finite iteration of non-linear compensating term of optimal solution sequence, a suboptimal congestion control algorithm of CDMA can be obtained. It is proved by analysis in theory and system level simulation that the congestion control algorithm can enlarge system throughput while controlling system load.

scholarly journals System Level Simulation of Microgrid Power Electronic Systems

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 644
Author(s):  
Michal Frivaldsky ◽  
Jan Morgos ◽  
Michal Prazenica ◽  
Kristian Takacs
Keyword(s):  
Smart Grid ◽  
Simulation Model ◽  
Real Time ◽  
Power Converter ◽  
System Level ◽  
Time Behavior ◽  
Operational Parameters ◽  
System Level Simulation ◽  
Time Operation ◽  
The Impact

In this paper, we describe a procedure for designing an accurate simulation model using a price-wised linear approach referred to as the power semiconductor converters of a DC microgrid concept. Initially, the selection of topologies of individual power stage blocs are identified. Due to the requirements for verifying the accuracy of the simulation model, physical samples of power converters are realized with a power ratio of 1:10. The focus was on optimization of operational parameters such as real-time behavior (variable waveforms within a time domain), efficiency, and the voltage/current ripples. The approach was compared to real-time operation and efficiency performance was evaluated showing the accuracy and suitability of the presented approach. The results show the potential for developing complex smart grid simulation models, with a high level of accuracy, and thus the possibility to investigate various operational scenarios and the impact of power converter characteristics on the performance of a smart gird. Two possible operational scenarios of the proposed smart grid concept are evaluated and demonstrate that an accurate hardware-in-the-loop (HIL) system can be designed.

scholarly journals Gem5-X

2021 ◽  
Vol 18 (4) ◽  
pp. 1-27
Author(s):  
Yasir Mahmood Qureshi ◽  
William Andrew Simon ◽  
Marina Zapater ◽  
Katzalin Olcoz ◽  
David Atienza
Keyword(s):  
Visual Recognition ◽  
Energy Savings ◽  
Video Encoding ◽  
System Level ◽  
Heterogeneous Architecture ◽  
Video Analytics ◽  
Smart Systems ◽  
System Level Simulation ◽  
Many Core ◽  
New Applications

The increasing adoption of smart systems in our daily life has led to the development of new applications with varying performance and energy constraints, and suitable computing architectures need to be developed for these new applications. In this article, we present gem5-X, a system-level simulation framework, based on gem-5, for architectural exploration of heterogeneous many-core systems. To demonstrate the capabilities of gem5-X, real-time video analytics is used as a case-study. It is composed of two kernels, namely, video encoding and image classification using convolutional neural networks (CNNs). First, we explore through gem5-X the benefits of latest 3D high bandwidth memory (HBM2) in different architectural configurations. Then, using a two-step exploration methodology, we develop a new optimized clustered-heterogeneous architecture with HBM2 in gem5-X for video analytics application. In this proposed clustered-heterogeneous architecture, ARMv8 in-order cluster with in-cache computing engine executes the video encoding kernel, giving 20% performance and 54% energy benefits compared to baseline ARM in-order and Out-of-Order systems, respectively. Furthermore, thanks to gem5-X, we conclude that ARM Out-of-Order clusters with HBM2 are the best choice to run visual recognition using CNNs, as they outperform DDR4-based system by up to 30% both in terms of performance and energy savings.

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