Secure Computation Efficiency Resource Allocation for Massive MIMO-Enabled Mobile Edge Computing Networks

In this article,the secure computation efficiency(SCE)problem is studied in a massive multipleinput multiple-output(mMIMO)-assisted mobile edge computing(MEC)network.We first derive the secure transmission rate based on the mMIMO under imperfect channel state information.Based on this,the SCE maximization problem is formulated by jointly optimizing the local computation frequency,the offloading time,the downloading time,the users and the base station transmit power.Due to its difficulty to directly solve the formulated problem,we first transform the fractional objective function into the subtractive form one via the dinkelbach method.Next,the original problem is transformed into a convex one by applying the successive convex approximation technique,and an iteration algorithm is proposed to obtain the solutions.Finally,the stimulations are conducted to show that the performance of the proposed schemes is superior to that of the other schemes.

Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

Eccentric Computational Embodiments: Cognitive Domestication of External Entities

The emphasis on the simplification of cognitive and motor tasks by recent results of morphological computation has rendered possible the construction of appropriate“mimetic bodies”able to render accompanied computations simpler,according to a general appeal to the“simplexity”of animal embodied cognition.A new activity of what we can call“distributed computation”holds the promise of originating a new generation of robots with better adaptability and restricted number of required control parameters.The framework of distributed computation helps us see them in a more naturalized and prudent perspective,avoiding ontological or metaphysical considerations.Despite these progresses,there are still problems regarding the epistemological limitations of computational modeling remain to be solved.

Computational Experiments for Complex Social Systems:Integrated Design of Experiment System

Powered by advanced information industry and intelligent technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).And human factors have become crucial in the operations of complex social systems.Traditional mechanical analysis and social simulations alone are powerless for analyzing complex social systems.Against this backdrop,computational experiments have emerged as a new method for quantitative analysis of complex social systems by combining social simulation(e.g.,ABM),complexity science,and domain knowledge.However,in the process of applying computational experiments,the construction of experiment system not only considers a large number of artificial society models,but also involves a large amount of data and knowledge.As a result,how to integrate various data,model and knowledge to achieve a running experiment system has become a key challenge.This paper proposes an integrated design framework of computational experiment system,which is composed of four parts:generation of digital subject,generation of digital object,design of operation engine,and construction of experiment system.Finally,this paper outlines a typical case study of coal mine emergency management to verify the validity of the proposed framework.

GCAGA: A Gini Coefficient-Based Optimization Strategy for Computation Offloading in Multi-User-Multi-Edge MEC System

To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge.However,resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications.To address the difficulty of running computationally intensive applications on resource-constrained clients,a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper.Then a user benefit function EoU(Experience of Users)is proposed jointly considering energy consumption and time delay.The EoU maximization problem is decomposed into two steps,i.e.,resource allocation and offloading decision.The offloading decision is usually given by heuristic algorithms which are often faced with the challenge of slow convergence and poor stability.Thus,a combined offloading algorithm,i.e.,a Gini coefficient-based adaptive genetic algorithm(GCAGA),is proposed to alleviate the dilemma.The proposed algorithm optimizes the offloading decision by maximizing EoU and accelerates the convergence with the Gini coefficient.The simulation compares the proposed algorithm with the genetic algorithm(GA)and adaptive genetic algorithm(AGA).Experiment results show that the Gini coefficient and the adaptive heuristic operators can accelerate the convergence speed,and the proposed algorithm performs better in terms of convergence while obtaining higher EoU.The simulation code of the proposed algorithm is available:https://github.com/Grox888/Mobile_Edge_Computing/tree/GCAGA.

Two-Stage IoT Computational Task Offloading Decision-Making in MEC with Request Holding and Dynamic Eviction

The rapid development of Internet of Things(IoT)technology has led to a significant increase in the computational task load of Terminal Devices(TDs).TDs reduce response latency and energy consumption with the support of task-offloading in Multi-access Edge Computing(MEC).However,existing task-offloading optimization methods typically assume that MEC’s computing resources are unlimited,and there is a lack of research on the optimization of task-offloading when MEC resources are exhausted.In addition,existing solutions only decide whether to accept the offloaded task request based on the single decision result of the current time slot,but lack support for multiple retry in subsequent time slots.It is resulting in TD missing potential offloading opportunities in the future.To fill this gap,we propose a Two-Stage Offloading Decision-making Framework(TSODF)with request holding and dynamic eviction.Long Short-Term Memory(LSTM)-based task-offloading request prediction and MEC resource release estimation are integrated to infer the probability of a request being accepted in the subsequent time slot.The framework learns optimized decision-making experiences continuously to increase the success rate of task offloading based on deep learning technology.Simulation results show that TSODF reduces total TD’s energy consumption and delay for task execution and improves task offloading rate and system resource utilization compared to the benchmark method.

Introduction to the Special Issue on Computational Intelligent Systems for Solving Complex Engineering Problems: Principles and Applications

Computational Intelligent(CI)systems represent a pivotal intersection of cutting-edge technologies and complex engineering challenges aimed at solving real-world problems.This comprehensive body of work delves into the realm of CI,which is designed to tackle intricate and multifaceted engineering problems through advanced computational techniques.The history of CI systems is a fascinating journey that spans several decades and has its roots in the development of artificial intelligence and machine learning techniques.Through a wide array of practical examples and case studies,this special issue bridges the gap between theoretical concepts and practical implementation,shedding light on how CI systems can optimize processes,design solutions,and inform decisions in complex engineering landscapes.This compilation stands as an essential resource for both novice learners and seasoned practitioners,offering a holistic perspective on the potential of CI in reshaping the future of engineering problem-solving.

Computational Intelligence Determines Effective Rationality

Rationality is a fundamental concept in economics. Most researchers will accept that human beings are not fully rational. Herbert Simon suggested that we are ＂bounded rational＂. However, it is very difficult to quantify ＂bounded rationality＂, and therefore it is difficult to pinpoint its impact to all those economic theories that depend on the assumption of full rationality. Ariel Rubinstein proposed to model bounded rationality by explicitly specifying the decision makers＇ decision-making procedures. This paper takes a computational point of view to Rubinstein＇s approach. From a computational point of view, decision procedures can be encoded in algorithms and heuristics. We argue that, everything else being equal, the effective rationality of an agent is determined by its computational power - we refer to this as the computational intelligence determines effective rationality （CIDER） theory. This is not an attempt to propose a unifying definition of bounded rationality. It is merely a proposal of a computational point of view of bounded rationality. This way of interpreting bounded rationality enables us to （computationally） reason about economic systems when the full rationality assumption is relaxed.

Employing Computational Intelligence to Generate More Intelligent and Energy Efficient Living Spaces

Our living environments are being gradually occupied with an abundant number of digital objects that have networking and computing capabilities. After these devices are plugged into a network, they initially advertise their presence and capabilities in the form of services so that they can be discovered and, if desired, exploited by the user or other networked devices. With the increasing number of these devices attached to the network, the complexity to configure and control them increases, which may lead to major processing and communication overhead. Hence, the devices are no longer expected to just act as primitive stand-alone appliances that only provide the facilities and services to the user they are designed for, but also offer complex services that emerge from unique combinations of devices. This creates the necessity for these devices to be equipped with some sort of intelligence and self-awareness to enable them to be self-configuring and self-programming. However, with this ＂smart evolution＂, the cognitive load to configure and control such spaces becomes immense. One way to relieve this load is by employing artificial intelligence （AI） techniques to create an intelligent ＂presence＂ where the system will be able to recognize the users and autonomously program the environment to be energy efficient and responsive to the user＇s needs and behaviours. These AI mechanisms should be embedded in the user＇s environments and should operate in a non-intrusive manner. This paper will show how computational intelligence （CI）, which is an emerging domain of AI, could be employed and embedded in our living spaces to help such environments to be more energy efficient, intelligent, adaptive and convenient to the users.

Joint Resource Allocation and Coordinated Computation Offloading for Fog Radio Access Networks

The cloud radio access network(C-RAN) and the fog computing have been recently proposed to tackle the dramatically increasing traffic demands and to provide better quality of service(QoS) to user equipment(UE).Considering the better computation capability of the cloud RAN(10 times larger than that of the fog RAN) and the lower transmission delay of the fog computing,we propose a joint resource allocation and coordinated computation offloading algorithm for the fog RAN(F-RAN),which takes the advantage of C-RAN and fog computing.Specifically,the F-RAN splits a computation task into the fog computing part and the cloud computing part.Based on the constraints of maximum transmission delay tolerance,fronthaul and backhaul capacity limits,we minimize the energy cost and obtain optimal computational resource allocation for multiple UE,transmission power allocation of each UE and the event splitting factor.Numerical results have been proposed with the comparison of existing methods.

Aircraft noise and its nearfield propagation computations

Noise generated by civil transport aircraft during take-off and approach-to-land phases of operation is an environmental problem. The aircraft noise problem is firstly reviewed in this article. The review is followed by a description and assessment of a number of sound propagation methods suitable for applications with a background mean flow field pertinent to aircraft noise. Of the three main areas of the noise problem, i.e. generation, propagation, and ra- diation, propagation provides a vital link between near-field noise generation and far-field radiation. Its accurate assessment ensures the overall validity of a prediction model. Of the various classes of propagation equations, linearised Euler equations are often casted in either time domain or frequency domain. The equations are often solved numerically by computational aeroacoustics techniques, bur are subject to the onset of Kelvin-Helmholtz （K-H） instability modes which may ruin the solutions. Other forms of linearised equations, e.g. acoustic perturbation equations have been proposed, with differing degrees of success.

What can computational modeling offer for studying the Ca^(2+) dysregulation in Alzheimer's disease:current research and future directions

Ca^2＋ dysregulation is an early event observed in Alzheimer＇s disease（AD） patients preceding the presence of its clinical symptoms.Dysregulation of neuronalCa^2＋ will cause synaptic loss and neuronal death,eventually leading to memory impairments and cognitive decline.Treatments targetingCa^2＋ signaling pathways are potential therapeutic strategies against AD.The complicated interactions make it challenging and expensive to study the underlying mechanisms as to how Ca^2＋ signaling contributes to the pathogenesis of AD.Computational modeling offers new opportunities to study the signaling pathway and test proposed mechanisms.In this mini-review,we present some computational approaches that have been used to study Ca^2＋ dysregulation of AD by simulating Ca^2＋signaling at various levels.We also pointed out the future directions that computational modeling can be done in studying the Ca^2＋ dysregulation in AD.

COMPUTATIONAL FLUID DYNAMICS RESEARCH ON PRESSURE LOSS OF CROSS-FLOW PERFORATED MUFFLER

The pressure loss of cross-flow perforated of physical modeling, simulation and data processing. muffler has been computed with the procedure Three-dimensional computational fluid dynamics （CFD） has been used to investigate the relations of porosities, flow velocity and diameter of the holes with the pressure loss. Accordingly, some preliminary results have been obtained that pressure loss increases with porosity descent as nearly a hyperbolic trend, rising flow velocity of the input makes the pressure loss increasing with parabola trend, diameter of holes affects little about pressure loss of the muffler. Otherwise, the holes on the perforated pipes make the air flow gently and meanly, which decreases the air impact to the wall and pipes in the muffler. A practical perforated muffler is used to illustrate the available of this method for pressure loss computation, and the comparison shows that the computation results with the method of CFD has reference value for muffler design.

Computational simulation of convective flow in the Earth crust under consideration of dynamic crust-mantle interactions

The finite element method was used to solve fluid dynamic interaction problems between the crust and mantle of the Earth. To consider different mechanical behaviours, the lithosphere consisting of the crust and upper mantle was simulated as fluid-saturated porous rocks, while the upper aesthenospheric part of the mantle was simulated as viscous fluids. Since the whole lithosphere was computationally simulated, the dynamic interaction between the crust and the upper mantle was appropriately considered. In particular, the mixing of mantle fluids and crustal fluids was simulated in the corresponding computational model. The related computational simulation results from an example problem demonstrate that the mantle fluids can flow into the crust and mix with the crustal fluids due to the resulting convective flows in the crust-mantle system. Likewise, the crustal fluids can also flow into the upper mantle and mix with the mantle fluids. This kind of fluids mixing and exchange is very important to the better understanding of the governing processes that control the ore body formation and mineralization in the upper crust of the Earth.

Replacement of annular domain with trapezoidal domain in computational modeling of nonaqueous-phase-liquid dissolution-front propagation problems

In order to simulate the instability phenomenon of a nonaqueous phase liquid(NAPL) dissolution front in a computational model, the intrinsic characteristic length is commonly used to determine the length scale at which the instability of the NAPL dissolution front can be initiated. This will require a huge number of finite elements if a whole NAPL dissolution system is simulated in the computational model. Even though modern supercomputers might be used to tackle this kind of NAPL dissolution problem, it can become prohibitive for commonly-used personal computers to do so. The main purpose of this work is to investigate whether or not the whole NAPL dissolution system of an annular domain can be replaced by a trapezoidal domain, so as to greatly reduce the requirements for computer efforts. The related simulation results have demonstrated that when the NAPL dissolution system under consideration is in a subcritical state, if the dissolution pattern around the entrance of an annulus domain is of interest, then a trapezoidal domain cannot be used to replace an annular domain in the computational simulation of the NAPL dissolution system.However, if the dissolution pattern away from the vicinity of the entrance of an annulus domain is of interest, then a trapezoidal domain can be used to replace an annular domain in the computational simulation of the NAPL dissolution system. When the NAPL dissolution system under consideration is in a supercritical state, a trapezoidal domain cannot be used to replace an annular domain in the computational simulation of the NAPL dissolution system.

Review:Recent Development of High⁃Order⁃Spectral Method Combined with Computational Fluid Dynamics Method for Wave⁃Structure Interactions

The present paper reviews the recent developments of a high⁃order⁃spectral method(HOS)and the combination with computational fluid dynamics(CFD)method for wave⁃structure interactions.As the numerical simulations of wave⁃structure interaction require efficiency and accuracy,as well as the ability in calculating in open sea states,the HOS method has its strength in both generating extreme waves in open seas and fast convergence in simulations,while computational fluid dynamics(CFD)method has its advantages in simulating violent wave⁃structure interactions.This paper provides the new thoughts for fast and accurate simulations,as well as the future work on innovations in fine fluid field of numerical simulations.

Multi-Scale Analysis of Fretting Fatigue in Heterogeneous Materials Using Computational Homogenization

This paper deals with modeling of the phenomenon of fretting fatigue in heterogeneous materials using the multi-scale computational homogenization technique and finite element analysis(FEA).The heterogeneous material for the specimens consists of a single hole model(25% void/cell,16% void/cell and 10% void/cell)and a four-hole model(25%void/cell).Using a representative volume element(RVE),we try to produce the equivalent homogenized properties and work on a homogeneous specimen for the study of fretting fatigue.Next,the fretting fatigue contact problem is performed for 3 new cases of models that consist of a homogeneous and a heterogeneous part(single hole cell)in the contact area.The aim is to analyze the normal and shear stresses of these models and compare them with the results of the corresponding heterogeneous models based on the Direct Numerical Simulation(DNS)method.Finally,by comparing the computational time and%deviations,we draw conclusions about the reliability and effectiveness of the proposed method.

Computational Nutrition: An Algorithm to Generate a Diet Plan to Meet Specific Nutritional Requirements

Many methods have been proposed to generate meal plans, but most of them only consider proximates. However, the human body requires a combination of proximates and several macronutrients, micronutrients, vitamins, and minerals. Furthermore, the models designed to generate these meal plans do not take into account an individual’s specific nutritional needs. These needs are often expressed as a combination of lower bound amount (LBA), ideal amount (IA), and upper bound amount (UBA) necessary for the human body to thrive. The aim of this project is to generate an algorithm to produce a list of food items that will meet specific nutritional requirements. With the proposed algorithm, each nutrient receives a score based on the amount of nutrient contained in the food list in relation to the LBA, IA, and UBA. These scores are aggregated to give the meal plan an overall score.

Computation Partitioning in Mobile Cloud Computing: A Survey

Mobile devices are increasingly interacting with clouds,and mobile cloud computing has emerged as a new paradigm.An central topic in mobile cloud computing is computation partitioning,which involves partitioning the execution of applications between the mobile side and cloud side so that execution cost is minimized.This paper discusses computation partitioning in mobile cloud computing.We first present the background and system models of mobile cloud computation partitioning systems.We then describe and compare state-of-the-art mobile computation partitioning in terms of application modeling,profiling,optimization,and implementation.We point out the main research issues and directions and summarize our own works.

Lax Pair and Darboux Transformation for a Variable-Coefficient Fifth-Order Korteweg-de Vries Equation with Symbolic Computation

In this paper, we put our focus on a variable-coe^cient fifth-order Korteweg-de Vries （fKdV） equation, which possesses a great number of excellent properties and is of current importance in physical and engineering fields. Certain constraints are worked out, which make sure the integrability of such an equation. Under those constraints, some integrable properties are derived, such as the Lax pair and Darboux transformation. Via the Darboux transformation, which is an exercisable way to generate solutions in a recursive manner, the one- and two-solitonic solutions are presented and the relevant physical applications of these solitonic structures in some fields are also pointed out.