scholarly journals Distributed Energy-Efficient and Secure Offloading in Air-to-Ground MEC Networks

2021 ◽  
Author(s):  
Wanning Liu ◽  
Yitao Xu ◽  
Ducheng Wu ◽  
Haichao Wang ◽  
Xueqiang Zheng ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Nonlinear Programming ◽  
Energy Efficient ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Distributed Energy ◽  
Integer Nonlinear Programming ◽  
Minlp Problem ◽  
System Energy ◽  
Simulation Results

Abstract This paper mainly investigates the energy-efficient and secure offloading problem in air-to-ground MEC networks. The proposed efficient offloading mechanism is as per the requirements of the heterogeneous tasks of ground users. Further, the optimizing offloading rate, offloading object, and channel access jointly formulate system energy consumption and eavesdropping rate minimization. A distributed two-stage offloading scheme is proposed for achieving the sub-optimal solution for the Mixed-integer Nonlinear Programming (MINLP) problem. Finally, simulation results demonstrate that the proposed scheme is superior to several benchmark schemes.

scholarly journals Distributed energy-efficient and secure offloading in air-to-ground MEC networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Wanning Liu ◽  
Yitao Xu ◽  
Ducheng Wu ◽  
Haichao Wang ◽  
Xueqiang Zheng ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Mobile Edge Computing ◽  
Distributed Energy ◽  
Integer Nonlinear Programming ◽  
Minlp Problem ◽  
System Energy ◽  
Simulation Results

AbstractThis paper mainly investigates the energy-efficient and secure offloading problem in air-to-ground Mobile Edge Computing (MEC) networks. The proposed efficient offloading mechanism is as per the requirements of the heterogeneous tasks of ground users. Further, the optimizing offloading rate, offloading object, and channel access jointly formulate system energy consumption and eavesdropping rate minimization. A distributed two-stage offloading scheme is proposed for achieving the sub-optimal solution for the Mixed-integer Nonlinear Programming (MINLP) problem. Finally, simulation results demonstrate that the proposed scheme is superior to several benchmark schemes.

scholarly journals Optimization of Distillation Sequences with Nonsharp Separation Columns

Processes ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 323 ◽  
Author(s):  
Xi Wang ◽  
Zengzhi Du ◽  
Yunlu Zhang ◽  
Jingde Wang ◽  
Jianhong Wang ◽  
...  
Keyword(s):  
Nonlinear Programming ◽  
Solution Space ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Separation Processes ◽  
Integer Nonlinear Programming ◽  
Minlp Problem ◽  
Separation Sequence ◽  
Computationally Intensive ◽  
Separation Columns

Nonsharp distillation sequences are widely used in industrial separation processes; however, most current research has not discussed this topic, except in sequences with heat integration under special operating conditions, including complex columns. The sequence with nonsharp separation has the features of general distillation sequences, which are usually optimized by adjusting the separation sequence and the design/operation parameters of each column in the sequence, making the optimization a mixed integer nonlinear programming (MINLP) problem, which is usually hard to solve. With inclusion of nonsharp separation columns, the sequence optimization becomes even more complicated and computationally intensive. This work aimed to optimize the distillation sequence, including nonsharp distillation alongside simple columns and dividing wall columns. Inspired by the dynamic programing method for sharp distillation sequence, a framework for automatic optimization is proposed to decompose the MINLP problem into integer programming (IP) and nonlinear programming (NLP) problems. The optimization processes of sharp and nonsharp distillation sequences are compared and the solution space in terms of the possible number of distillation sequences with nonsharp separation is discussed. Two optimization cases, including an industrial one, are included to validate the proposed framework.

Joint Energy-Efficient Resource Allocation Scheme for AF-Based Multi-Relay OFDM Networks

2014 ◽  
Vol 610 ◽  
pp. 783-788
Author(s):  
Zhi Kang Zhou ◽  
Qi Zhu
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Allocation Scheme ◽  
Joint Resource Allocation ◽  
The Optimizing Model ◽  
Minlp Problem ◽  
Resource Allocation Scheme ◽  
Optimizing Model

In this paper, a joint resource allocation scheme for energy-efficient communication in cooperative orthogonal frequency division multiple (OFDM) networks based on subcarrier pairing (SP) is studied. The problem aimed at maximizing the system energy efficiency (EE) is formulated into a mixed-integer nonlinear programming (MINLP) problem. To solve the complex MINLP problem, we simplify the optimizing model as a typical fractional programming problem by defining the equivalent channel gain, thus Dinkelbach’s method consisting of outer iterations and inner iterations can be used to find the optimal solution to the MINLP problem proposed in polynomial time. Simulation results show that the proposed scheme can improve the system EE and ensure the quality of service (QoS) of users.

Analyse of the Mixed-Integer Nonlinear Programming Method for the Application in the Cellular Network

2013 ◽  
Vol 347-350 ◽  
pp. 2352-2359
Author(s):  
Shan Zong ◽  
Bing Liu
Keyword(s):  
Nonlinear Programming ◽  
Cellular Network ◽  
Data Rate ◽  
Mixed Integer Nonlinear Programming ◽  
Programming Method ◽  
Mixed Integer ◽  
Integer Nonlinear Programming ◽  
Simulation Results ◽  
Nonlinear Programming Method

This paper discussed several methods to maximize the sum of the data rate. After the analysis of the graphic algorithm, we found the difficulty of the determination of the variables. To solve the problem, we propose a new idea to operate the variable and proved it to be efficient in the simulation results.

Optimal Retrofitting of Structures Using Braces

2014 ◽  
Vol 553 ◽  
pp. 807-812
Author(s):  
Sawekchai Tangaramvong ◽  
Francis Tin-Loi
Keyword(s):  
Nonlinear Programming ◽  
Mixed Integer ◽  
Design Domain ◽  
Ground Structure ◽  
Binary Variables ◽  
Integer Nonlinear Programming ◽  
Initial Basis ◽  
Minlp Problem ◽  
Multiple Load ◽  
Bounded System

The paper presents a mathematical programming based approach for the efficient retrofitting, with braces, of structures subjected to multiple load cases and serviceability limitations, simultaneously. The method is based on a simple ground structure concept that generates within a design domain all possible cross braces, and then automates the decision as to which brace members are retained or eliminated using unknown 0-1 variables. The optimization minimizes simultaneously the total number and volume of design braces. The governing problem takes the form of a disjunctive and combinatorial optimization program, cast as a mixed integer nonlinear programming (MINLP) problem. We propose a two-step optimization algorithm to solve the MINLP, in which the first step processes a standard nonlinear programming (NLP) problem by relaxing the binary variables to a continuous bounded system, the results of which form an initial basis for the second and final solve of the MINLP problem with binary variables.

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