Engineering Emergence: A Survey on Control in the World of Complex Networks

Berceanu, Cristian; Pătraşcu, Monica

doi:10.3390/automation3010009

Cited by 6 publications

(4 citation statements)

References 227 publications

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“…Ordinary differential equations (ODE) in [36] can approach the convergence condition of formula (20). The estimated utility will converge to the anticipated value of the known utility.…”

Section: Optimal Response Functionmentioning

confidence: 99%

“…The participants pick the stage's approach for each stage based on historical experience and observation. The participants' approach will almost certainly move towards the Nash equilibrium after engaging in long-term selection behavior [20]. This paper proposes an adaptive learning algorithm to converge to Nash equilibrium, which offers a solution to maximize the traffic utility while ensuring the optimal performance of individual vehicles.…”

Section: Introductionmentioning

confidence: 99%

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An efficient algorithm for optimal route node sensing in smart tourism Urban traffic based on priority constraints

Ding,

Yao,

Khezri

2023

Wireless Netw

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The public transportation system is now dealing with a number of problems brought on by the sharp increase in automobile ownership in cities as well as the buildup of vehicles as a result of events and accidents. However, the city's limited road network capacity cannot keep up with the increasing traffic demand, which further worsens travel conditions and results in a waste of time and money. Given that it is challenging to enhance the capacity of the road network in practice, efficient vehicle travel and evacuation using algorithms has emerged as a recent study focus. It is crucial to learn how to manage urban traffic issues during emergencies and maintain smooth and safe traffic flow. The existing studies only considers the optimized route selection for individual vehicles, signal cycle of traffic lights and deploy historical data to disperse the vehicles on alternative routes. However, such works do not consider the conflict of routes between vehicles, the customized traffic demand of each vehicle and uncertain traffic conditions. Therefore, this paper proposes a novel approach to facilitate the user to select the optimal route with real-time traffic scenario. Furthermore, the Nash equilibrium is established by mutual information swapping and self-adaptive learning method. Simulation results show that the proposed algorithm has better route selection capability in real-time personalized road traffic as compared with existing algorithms.

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“…Ordinary differential equations (ODE) in [36] can approach the convergence condition of formula (20). The estimated utility will converge to the anticipated value of the known utility.…”

Section: Optimal Response Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An efficient algorithm for optimal route node sensing in smart tourism Urban traffic based on priority constraints

Ding,

Yao,

Khezri

2023

Wireless Netw

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“…Dynamics research in complex networks offers many methods and approaches [1] for improving the controllability of dynamic systems where communication functions provide efficient connectivity links between the IoT nodes. Emergence is an essential characteristic of complex systems and networks [2]. In complex network analysis, strong and weak emergence can be considered for investigating the performance of network communication.…”

Section: Introductionmentioning

confidence: 99%

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

Thayananthan,

Albeshri,

A. Alamri

et al. 2023

Computers, Materials &Amp; Continua

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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.

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“…In the original publication [1], reference 49 (Section 2.2, Paragraph 1) was wrongly cited [2]. The correct reference that the authors intended to cite is [3] by Jia et al With this correction, the reference has been adjusted accordingly.…”

mentioning

confidence: 99%