A Survey on the Role of Complex Networks in IoT and Brain Communication

Complex networks on the Internet of Things(IoT)and brain communication are the main focus of this paper.The benefits of complex networks may be applicable in the future research directions of 6G,photonic,IoT,brain,etc.,communication technologies.Heavy data traffic,huge capacity,minimal level of dynamic latency,etc.are some of the future requirements in 5G+and 6G communication systems.In emerging communication,technologies such as 5G+/6G-based photonic sensor communication and complex networks play an important role in improving future requirements of IoT and brain communication.In this paper,the state of the complex system considered as a complex network(the connection between the brain cells,neurons,etc.)needs measurement for analyzing the functions of the neurons during brain communication.Here,we measure the state of the complex system through observability.Using 5G+/6G-based photonic sensor nodes,finding observability influenced by the concept of contraction provides the stability of neurons.When IoT or any sensors fail to measure the state of the connectivity in the 5G+or 6G communication due to external noise and attacks,some information about the sensor nodes during the communication will be lost.Similarly,neurons considered sing the complex networks concept neuron sensors in the brain lose communication and connections.Therefore,affected sensor nodes in a contraction are equivalent to compensate for maintaining stability conditions.In this compensation,loss of observability depends on the contraction size which is a key factor for employing a complex network.To analyze the observability recovery,we can use a contraction detection algorithm with complex network properties.Our survey paper shows that contraction size will allow us to improve the performance of brain communication,stability of neurons,etc.,through the clustering coefficient considered in the contraction detection algorithm.In addition,we discuss the scalability of IoT communication using 5G+/6G-based photonic technology.

Smart Communications and Networking for Future Deep-space Exploration

eight planets,various asteroids and comets in the solar system.Amount of deep-space scientific experiments promoted people to understand about the origin and evolution of the universe.With the rapid developments of equipment and spacecraft with high-accuracy detector and long-term energy,more and more ambitious deep-space exploration plans have also been scheduled or under discussion about space resources utilization and space migration,e.g.,manned landing on the Mars,guard infrastructures on the Moon and human-flight to the edge of the solar system(>100 AU),etc.

Network Evaluation and Protocol Deployment for Complex Deep-Space Networks Based on DTN

Previous research on deep-space networks based on delay-tolerant networking(DTN)has mainly focused on the performance of DTN protocols in simple networks;hence,research on complex networks is lacking.In this paper,we focus on network evaluation and protocol deployment for complex DTNbased deep-space networks and apply the results to a novel complex deep-space network based on the Universal Interplanetary Communication Network(UNICON-CDSN)proposed by the National Space Science Center(NSSC)for simulation and verification.A network evaluation method based on network capacity and memory analysis is proposed.Based on a performance comparison between the Licklider Transmission Protocol(LTP)and the Transmission Control Protocol(TCP)with the Bundle Protocol(BP)in various communication scenarios,a transport protocol configuration proposal is developed and used to construct an LTP deployment scheme for UNICON-CDSN.For the LTP deployment scheme,a theoretical model of file delivery time over complex deep-space networks is built.A network evaluation with the method proposed in this paper proves that UNICONCDSN satisfies the requirements for the 2020 Mars exploration mission Curiosity.Moreover,simulation results from a universal space communication network testbed(USCNT)designed by us show that the LTP deployment scheme is suitable for UNICON-CDSN.

THE STUDY ON DEGREE DISTRIBUTION PROPERTY OF COMPLEX NETWORK BASED ON COOPERATIVE COMMUNICATION

Complex networks have been widely studied. Recently,many results show that the degree distributions of some large networks follow the form of power-law and these networks possess better robustness against random nodes failure. As an effective technology on combating the channel fading,wireless cooperative communication is becoming one of the most important methods to improve the wireless communication performances. In this paper,the complex network models based on cooperative communication and non-cooperative communication are established; and the degree distribution properties for them are studied. The simulation results show that the degree distributions of these networks also follow the form of power-law,which means that the addition of cooperative communi-cation links will not change the property of degree distribution and then these networks will possess better robustness against random nodes failure as well.

Information-Defined Networks:A Communication Network Approach for Network Studies

The research of complex networks facilitates the progress of various disciplines,including biology,chemistry,social science,computer,and communication engineering.Recently,it is popular to utilize complex networks to study the communication networks,such as designing efficient routing strategies and robust communication networks.However,exploiting the advantages of communication networks to investigate networks in various disciplines beyond telecommunications is still in infancy.Because of this situation,this paper proposes an information-defined network(IDN)framework by which a complex network can be abstracted as a communication network associated with multiple intelligent agents.Specifically,each component and dynamic process in this framework can be defined by information.We show that the IDN framework promotes the research of unsolved problems in the current complex network field,especially for detecting new interaction types in realworld networks.

Degree distribution and robustness of cooperative communication network with scale-free model

With the requirements of users enhanced for wireless communication, the cooperative communication will become a development trend in future. In this paper, a model based on complex networks with both preferential attachment is researched to solve an actual network CCN （Cooperative Communication Network）. Firstly, the evolution of CCN is given by four steps with different probabilities. At the same time, the rate equations of nodes degree are presented to analyze the evolution of CCN. Secondly, the degree distribution is analyzed by calculating the rate equation and numerical simulation. Finally, the robustness of CCN is studied by numerical simulation with random attack and intentional attack to analyze the effects of degree distribution and average path length. The results of this paper are more significant for building CCN to programme the resource of communication.

Enabling Efficient Data Transmission in Wireless Sensor Networks-Based IoT Application

The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure domains like oil and gas supply,intelligent transportation,power grids,and autonomous agriculture,it is essential to guarantee the confidentiality,integrity,and authenticity of data collected and exchanged.However,the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques.Consequently,designing a lightweight secure data transmission scheme is becoming essential.In this article,we propose lightweight secure data transmission(LSDT)scheme for IoT environments.LSDT consists of three phases and utilizes an effective combination of symmetric keys and the Elliptic Curve Menezes-Qu-Vanstone asymmetric key agreement protocol.We design the simulation environment and experiments to evaluate the performance of the LSDT scheme in terms of communication and computation costs.Security and performance analysis indicates that the LSDT scheme is secure,suitable for IoT applications,and performs better in comparison to other related security schemes.

Complex field network-coded cooperation based on multi-user detection in wireless networks

Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is proposed.Theoretic analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time slots.Moreover,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.

Complex Cyber-Physical Networks： From Cybersecurity to Security Control

Complex cyber-physical network refers to a new generatio~ of complex networks whose normal functioning significantly relies on tight interactions between its physical and cyber compo- nents. Many modern critical infrastructures can be appropriately modelled as complex cyber-physical networks. Typical examples of such infrastructures are electrical power grids, WWW, public trans- portation systems, state financial networks, and the Interact. These critical facilities play important roles in ensuring the stability of society as well as the development of economy. Advances in informa- tion and communication technology open opportunities for malicious attackers to launch coordinated attacks on cyber-physical critical facilities in networked infrastructures from any Interact-accessible place. Cybersecurity of complex cyber-physical networks has emerged as a hot topic within this con- text. In practice, it is also very crucial to understand the interplay between the evolution of underlying network structures and the collective dynamics on these complex networks and consequently to design efficient security control strategies to protect the evolution of these networks. In this paper, cybersecu- rity of complex cyber-physical networks is first outlined and then some security enhancing techniques, with particular emphasis on safety communications, attack detection and fault-tolerant control, are suggested. Furthermore, a new class of efficient secure the achievement of desirable pinning synchronization control strategies are proposed for guaranteeing behaviors in complex cyber-physical networks against malicious attacks on nodes. The authors hope that this paper motivates to design enhanced security strategies for complex cyber-physical network systems, to realize resilient and secure critical infrastructures.

On Almost Controllability of Dynamical Complex Networks with Noises

This paper discusses the controllability problem of complex networks.It is shown that almost any weighted complex network with noise on the strength of communication links is controllable in the sense of Kalman controllability.The concept of almost controllability is elaborated by both theoretical discussions and experimental verifications.

复杂网络电输运性能与通信序列熵之间的关联

网络的电输运性能优化,不仅有助于理解网络的结构与功能关系,而且对于提升电气工程技术也有着非常重要的意义.从信息的角度看待网络,寻求影响网络电输运性能的信息结构测度是解决这一问题的有效途径.最近的研究表明,复杂网络的通信序列熵可以有效地量化网络的整体结构信息.本文将探讨其表征网络电输运性能的能力,其中主要研究了小世界网络、无标度网络、关联无标度网络、社团网络以及IEEE57等节点网络的通信序列熵和电输运性能之间的关联特性.研究结果表明,对于以上这些网络,它们的电输运性能是关于通信序列熵的单调递增函数,与通信序列熵成正关联特性.该规律的发现为设计高传输效率的电力网络提供了一个有效的策略,即可以通过提高网络的通信序列熵来优化其电输运性能.

Modeling the RTT of bundle protocol over asymmetric deep-space channels

Delay/disruption-tolerant networking communications rely heavily on BP(Bundle Protocol),which uses the well-known approach of store-and-forward with optional custody transfer to deal with stressed communication environments.The use of BP and its performance in deep-space communication has been the subject of debate.The accurate estimate of file delivery latency(i.e.,RTT(Round Trip Time))is essential for efficient transmission control,reliable delivery,and bandwidth usage optimization of a protocol.In this paper,we present a performance analysis of BP running over UDPCL/UDP over deep-space channels,focusing on the RTT estimate,in the presence of highly asymmetric channel rates.Analytical models are built for the RTT estimate of the BP/UDPCL transmissions considering the effect of delay caused by space channel-rate asymmetry,and,channel impairment.The models are validated by file transfer experiments using a PC-based testbed.It is found that a smaller bundle size(if smaller than a calculated threshold)results in a longer delay in custody acknowledgment transmission,and thus,a longer RTT.

基于复杂网络理论的健康相关行为与慢性非传染性疾病关系研究进展

近年来,有关健康相关行为(健康行为)与慢性非传染性疾病(慢性病)的研究视角从专注多种健康行为与某个慢性病间“多因单果”的独立效应,逐渐转向多个健康行为与慢性病“多因多果”的复杂相互作用。复杂网络理论是系统科学的重要板块,该理论考虑了众多因素在同一网络中的博弈关系,可通过一系列复杂网络模型、指标,揭示健康行为与慢性病多个因素间如何相互作用。本文对复杂网络理论定义、发展及其在健康行为与慢性病领域的常用模型和指标、案例内容进行综述,旨在打开复杂网络理论在健康领域更广阔的运用场景,为后续健康行为与慢性病关系的研究提供可参考的思路和工具。

Statistical properties of random clique networks

In this paper, a random clique network model to mimic the large clustering coefficient and the modular structure that exist in many real complex networks, such as social networks, artificial networks, and protein interaction networks, is introduced by combining the random selection rule of the ErdSs and Rényi （ER） model and the concept of cliques. We find that random clique networks having a small average degree differ from the ER network in that they have a large clustering coefficient and a power law clustering spectrum, while networks having a high average degree have similar properties as the ER model. In addition, we find that the relation between the clustering coefficient and the average degree shows a non-monotonic behavior and that the degree distributions can be fit by multiple Poisson curves; we explain the origin of such novel behaviors and degree distributions.

复杂网络模型在传染病预防控制中的应用

为探讨复杂网络模型在传染病预防控制中的应用，根据复杂网络的基本属性，利用网络模型和常用软件分析传染病传播过程。相对于传统的流行病学方法，复杂网络的理论不仅能描述传染病动态传播过程，也能进行传染病预测。通过复杂网络的理论来研究疾病的传播，能深入理解到网络的拓扑结构对疾病传播有重要影响，从而找到控制疾病传播的更有效的方法。

随机派系生长网络模型及其传输能力研究

本文提出一种基于随机选择的派系生长网络模型,该网络从一个a-派系模体开始,每个时间步t,在网络中随机选择m个节点构建一个新的a-派系,由此网络生长演化.模拟研究表明:该网络具有高的聚类系数和短的平均路径长度是一个小世界网络,并且比值ρ=m/a越小,聚类系数越大.而度分布则呈指数分布,这些特征与许多交通系统的复杂网络的实证研究结果相符.该网络的聚类系数与节点度呈幂律变化,显示网络具有模块化层次结构的特征,这一特征与近年来人们研究的大多数复杂网络具有模块化层次结构特征的实证研究结果相符.我们还研究了该网络的传输能力,研究表明该网络的传输能力随着比值ρ=m/a的减小而增大.这些研究结果对城市公共交通网络的构建具有一定的指导意义.

基于通信序列熵的复杂网络信息度量研究

从信息的角度看待网络系统并构建蕴含网络整体信息的测度是网络信息理论的关键问题,基于节点对通信能力的通信序列熵被考虑为量化网络信息的候选测度.为了探讨其表征网络整体信息的能力,首先研究模型网络的拓扑结构对通信序列熵的影响.结果表明,异质性强、度-度关联性强以及具有社团结构的网络均具有相对较小的通信序列熵.其次,对比研究一些真实网络和它们对应的随机化网络模型的通信序列熵,可以得到随机化网络模型的阶数越高,通信序列熵越小,且越接近真实网络的通信序列熵.这些研究结果表明,网络的通信序列熵敏感地依赖于网络的基本拓扑结构,而且随着网络有序程度的递增,通信序列熵呈减小趋势.本文的研究结论为通信序列熵具有量化网络整体信息的能力提供了证据.