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Current networks are providing plenty of services that users can access and use. These services are more and more pervasive and deployed in different networks distributed across an environment. This raises the problem of managing such environments in order to grant access to services from anywhere and to adapt the environment’s networks to dynamic changes. Also, there is a need of an autonomous behavior to reduce human intervention and assure environment’s consistency. This autonomous and distributed behavior leads to the definition and integration of existing and new technologies to enable autonomous distributed management. This is fulfilled by providing paradigms that bring awareness about the surroundings and enabled tools to manage and adapt the environment’s resources. The main problem is to dynamically provide auto‐configuration of networks to deal with the frequent changes which results from users’ roaming, changing services constraints, and changing services themselves, and adding, upgrading or removing policies. The outcome of these issues is a dynamic system with complex management. Hence, this paper proposes the integration of different techniques to provide an autonomous, distributed, and secure management including auto‐configuration, adaptation, and auto‐protection of pervasive environments. Then, policies control the behavior of the environment, devices configuration and the enforcement of security mechanisms to protect sensitive data. Also, mobile agents are employed to distribute management tasks across the distributed environment. In order to provide auto‐protection capabilities, the autonomous behavior of the environment have to be secured. Actually, this security issue is addressed by defining an agent‐based Public Key Infrastructure (PKI) with X.509 certificates. The agent ensures then that the security functions are applied across all the distributed networks, where specific agents are responsible for conveying necessary information and certificates to local environments. Finally, the paper proposes a semantic‐based privacy management approach using ontologies to decide how privacy information is handled in the environment.

In the last a few years a number of highly publicized incidents of Distributed Denial of Service (DDoS) attacks against high‐profile government and commercial websites have made people aware of the importance of providing data and services security to users. A DDoS attack is an availability attack, which is characterized by an explicit attempt from an attacker to prevent legitimate users of a service from using the desired resources. This paper introduces the vulnerability of web applications to DDoS attacks, and presents an active distributed defense system that has a deployment mixture of sub‐systems to protect web applications from DDoS attacks. According to the simulation experiments, this system is effective in that it is able to defend web applications against attacks. It can avoid overall network congestion and provide more resources to legitimate web users.

The purpose of this paper is to concern the design of a robust model predictive controller for distributed networked systems with transmission delays.

The overall system is composed of a number of interconnected nonlinear subsystems with time-varying transmission delays. A distributed networked system with transmission delays is modeled as a nonlinear system with a time-varying delay. Time delays appear in distributed systems due to the information transmission in the communication network or transport of material between the sub-plants. In real applications, the states may not be available directly and it could be a challenge to address the control problem in interconnected systems using a centralized architecture because of the constraints on the computational capabilities and the communication bandwidth. The controller design is characterized as an optimization problem of a “worst-case” objective function over an infinite moving horizon.

The aim is to propose control synthesis approach that depends on nonlinearity and time varying delay characteristics. The MPC problem is represented in a time varying delayed state feedback structure. Then the synthesis sufficient condition is provided in the form of a linear matrix inequality (LMI) optimization and is solved online at each time instant. In the rest, an LMI-based decentralized observer-based robust model predictive control strategy is proposed.

The authors develop RMPC strategies for a class of distributed networked systems with transmission delays using LMI-Based technique. To evaluate the applicability of the developed approach, the control design of a networked chemical reactor plant with two sub-plants is studied. The simulation results show the effectiveness of the proposed method.

It is proposed that future work should move on from existing network and system management methodologies to consider enhancing the management methodology for ATM and other networking technologies to meet existing and future requirements. This paper outlines an area where significant potential for further research exists and proposes a component‐based management architecture. The discussion indentifies the technological limitations and architectural drawbacks of current solutions and proposes the extension of existing services and an enhanced management framework to overcome the current restrictions.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

The authors of this paper aim to describe the design of distributed architectures for the remote control of multirobot systems. A very good example of remote robot programming in order to validate these architectures is in fact the remote visual servoing control. It uses sequences of camera inputs in order to bring the robots to the desired position, in an iterative way. In fact, in this paper, we enabled the students and scientists in our university to experiment with their remote visual servoing algorithms through a remote real environment instead of using simulation tools.

Since 2001, the authors have been using the UJI‐TeleLab as a tool to allow students and scientists to program remotely several vision‐based network robots. During this period it has been learnt that multithread remote programming combined with a distributed multirobot architecture, as well as advanced multimedia user interfaces, are very convenient, flexible and profitable for the design of a Tele‐Laboratory. The distributed system architecture permits any external algorithm to have access to almost every feature of several network robots.

Presents the multirobot system architecture and its performance by programming two closed loop experiments using the Internet as communication media between the user algorithm and the remote robots (i.e. remote visual servoing). They show which conditions of Internet latencies and bandwidth are appropriate for the visual servoing loop. We must take into account that the real images are taken from the remote robot scenario and the experiment algorithm is executed from the client side at the user place. Moreover, the distributed multirobot architecture is validated by performing a multirobot programming example using two manipulators and a mobile robot.

Future work will pursue the development of more sophisticated visual servoing loops using external cameras, pan/tilt and also stereo cameras. Indeed, the stereo cameras control introduces an interesting difficulty related to their synchronization during the loop, which introduces the need to implement Real Time Streaming Protocol (RTSP) based camera monitoring. By using camera servers that support RTSP (e.g. Helix Producer, etc.) it means sending the differences between the frames instead of sending the whole frame information for every iteration.

The distributed multirobot architecture has been validated since 2003 within the education and training scenario. Students and researchers are able to use the system as a tool to rapidly implement complex algorithms in a simple manner. The distributed multirobot architecture is being applied as well within the industrial robotics area in order to program remotely two synchonized robots.

This paper is an original contribution to the network robots field, since it presents a generic architecture to program remotelly a set of heterogeneous robots. The concept of network robot recently came up at the Workshop “network robots” within the IEEE ICRA 2005 World Congress.

The purpose of this work is to bridge FL and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. FL is an emerging collaborative machine learning technique that trains a model across multiple devices or servers holding private data samples without exchanging their data. The locally trained results are aggregated by a centralized server in a privacy-preserving way. However, there is an assumption where the centralized server is trustworthy, which is impractical. Fortunately, blockchain technology has opened a new era of data exchange among trustless strangers because of its decentralized architecture and cryptography-supported techniques.

In this study, the author proposes a novel design of a smart agent inspired by the smart contract concept. Specifically, based on the proposed smart agent, a fully decentralized, privacy-preserving and fair deep learning blockchain-FL framework is designed, where the agent network is consistent with the blockchain network and each smart agent is a participant in the FL task. During the whole training process, both the data and the model are not at the risk of leakage.

A demonstration of the proposed architecture is designed to train a neural network. Finally, the implementation of the proposed architecture is conducted in the Ethereum development, showing the effectiveness and applicability of the design.

The author aims to investigate the feasibility and practicality of linking the three areas together, namely, multi-agent system, FL and blockchain. A blockchain-FL framework, which is based on a smart agent system, has been proposed. The author has made several contributions to the state-of-the-art. First of all, a concrete design of a smart agent model is proposed, inspired by the smart contract concept in blockchain. The smart agent is autonomous and is able to disseminate, verify the information and execute the supported protocols. Based on the proposed smart agent model, a new architecture composed by these agents is formed, which is a blockchain network. Then, a fully decentralized, privacy-preserving and smart agent blockchain-FL framework has been proposed, where a smart agent acts as both a peer in a blockchain network and a participant in a FL task at the same time. Finally, a demonstration to train an artificial neural network is implemented to prove the effectiveness of the proposed framework.

Presents a review on implementing finite element methods on supercomputers, workstations and PCs and gives main trends in hardware and software developments. An appendix included at the end of the paper presents a bibliography on the subjects retrospectively to 1985 and approximately 1,100 references are listed.