scholarly journals Joint V2V-Assisted Clustering, Caching, and Multicast Beamforming in Vehicular Edge Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Kan Wang ◽  
Ruijie Wang ◽  
Junhuai Li ◽  
Meng Li
Keyword(s):  
Network Performance ◽  
Vehicular Networks ◽  
Original Problem ◽  
Power Saving ◽  
Sample Average Approximation ◽  
Power Cost ◽  
Content Caching ◽  
Sample Average ◽  
Edge Networks ◽  
Multicast Beamforming

As an emerging type of Internet of Things (IoT), Internet of Vehicles (IoV) denotes the vehicle network capable of supporting diverse types of intelligent services and has attracted great attention in the 5G era. In this study, we consider the multimedia content caching with multicast beamforming in IoV-based vehicular edge networks. First, we formulate a joint vehicle-to-vehicle- (V2V-) assisted clustering, caching, and multicasting optimization problem, to minimize the weighted sum of flow cost and power cost, subject to the quality-of-service (QoS) constraints for each multicast group. Then, with the two-timescale setup, the intractable and stochastic original problem is decoupled at separate timescales. More precisely, at the large timescale, we leverage the sample average approximation (SAA) technique to solve the joint V2V-assisted clustering and caching problem and then demonstrate the equivalence of optimal solutions between the original problem and its relaxed linear programming (LP) counterpart; and at the small timescale, we leverage the successive convex approximation (SCA) method to solve the nonconvex multicast beamforming problem, whereby a series of convex subproblems can be acquired, with the convergence also assured. Finally, simulations are conducted with different system parameters to show the effectiveness of the proposed algorithm, revealing that the network performance can benefit from not only the power saving from wireless multicast beamforming in vehicular networks but also the content caching among vehicles.

scholarly journals A Nonlinear Lagrange Algorithm for Stochastic Minimax Problems Based on Sample Average Approximation Method

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Suxiang He ◽  
Yunyun Nie ◽  
Xiaopeng Wang
Keyword(s):  
Approximation Method ◽  
Original Problem ◽  
Minimax Problems ◽  
Lagrange Function ◽  
Sample Average Approximation ◽  
Second Step ◽  
Sample Average ◽  
Sample Average Approximation Method ◽  
Nonlinear Lagrange Algorithm ◽  
Average Approximation

An implementable nonlinear Lagrange algorithm for stochastic minimax problems is presented based on sample average approximation method in this paper, in which the second step minimizes a nonlinear Lagrange function with sample average approximation functions of original functions and the sample average approximation of the Lagrange multiplier is adopted. Under a set of mild assumptions, it is proven that the sequences of solution and multiplier obtained by the proposed algorithm converge to the Kuhn-Tucker pair of the original problem with probability one as the sample size increases. At last, the numerical experiments for five test examples are performed and the numerical results indicate that the algorithm is promising.

Investigating the Analysis of Power Saving Mode in IEEE 802.11 for Wi-Fi Communication

2018 ◽  
Vol 6 (3) ◽  
pp. 13-19
Author(s):  
Isam Aameer Ibrahim ◽  
Haider TH Salim ◽  
Hasan F. Khazaal
Keyword(s):  
Ieee 802.11 ◽  
Network Performance ◽  
Power Saving ◽  
Packet Delay ◽  
Access Point ◽  
Battery Life ◽  
Global Issues ◽  
Time Ratio ◽  
Power Saving Mode ◽  
Saving Mode

One of the major global issues today is energy consumption. Consequently, power management was introduced in various communication technologies. For IEEE 802.11wireless communication, there is a Power Saving Mode scheme (PSM) for increase the battery life of cell phone. In this PSM, there are two key parameters: beacon period interval (BI) and listen interval(LI). In most work these values are chosen arbitrary. Here, a scheme to determine the optimal BI and LI for accomplishing the most astounding conceivable vitality proficiency is introduced. This is implemented with the application of a numerical sample to the standard IEEE 802.11 PSM and Access Point-PSM (AP-PSM) schemes. To ensure the quality of network performance analysis on the normal and change of parcel delays is doing. The well-known queuing (M/G/I) model with bulk services are utilized. After the implementation of the proposed analysis, “maximum rest plan time ratio optimal Sleep Scheme (OSS)” which is when participate stations stay in the doze mode it can be determined. In this research shows that the optimal BI and LI produce optimal OSS time ratio scheme also achieved optimal average and variance of packet delay.

Sample Average Approximation

2017 ◽  
pp. 75-84
Author(s):  
Tingsong Wang ◽  
Shuaian Wang ◽  
Qiang Meng
Keyword(s):  
Sample Average Approximation ◽  
Sample Average ◽  
Average Approximation

Detection and Ignoring of Blackhole Attack in Vanets Networks

2016 ◽  
Vol 6 (2) ◽  
pp. 1-10
Author(s):  
Chaima Bensaid ◽  
Sofiane Boukli Hacene ◽  
Kamel Mohamed Faraoun
Keyword(s):  
Black Hole ◽  
Communication Networks ◽  
Network Performance ◽  
Vehicular Networks ◽  
Data Communication ◽  
Main Idea ◽  
Black Hole Attack ◽  
Malicious Nodes ◽  
The Future ◽  
Detailed Simulation

Vehicular networks or VANET announce as the communication networks of the future, where the mobility is the main idea. These networks should be able to interconnect vehicles. The optimal goal is that these networks will contribute to safer roads and more effective in the future by providing timely information to drivers and concerned authorities. They are therefore vulnerable to many types of attacks among them the black hole attack. In this attack, a malicious node disseminates spurious replies for any route discovery in order to monopolize all data communication and deteriorate network performance. Many studies have focused on detecting and isolating malicious nodes in VANET. In this paper, the authors present two mechanisms to detect this attack. The main goal is detecting as well as bypass cooperative black hole attack. The authors' approaches have been evaluated by the detailed simulation study with NS2 and the simulation results shows an improvement of protocol performance.

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