The immense increase in multimedia-on-demand traffic that refers to audio, video, and images, has drastically shifted the vision of the Internet of Things (IoT) from scalar to Multimedia Internet of Things (M-IoT). IoT devices are constrained in terms of energy, computing, size, and storage memory. Delay-sensitive and bandwidth-hungry multimedia applications over constrained IoT networks require revision of IoT architecture for M-IoT. This paper provides a comprehensive survey of M-IoT with an emphasis on architecture, protocols, and applications. This article starts by providing a horizontal overview of the IoT. Then, we discuss the issues considering the characteristics of multimedia and provide a summary of related M-IoT architectures. Various multimedia applications supported by IoT are surveyed, and numerous use cases related to road traffic management, security, industry, and health are illustrated to show how different M-IoT applications are revolutionizing human life. We explore the importance of Quality-of-Experience (QoE) and Quality-of-Service (QoS) for multimedia transmission over IoT. Moreover, we explore the limitations of IoT for multimedia computing and present the relationship between the M-IoT and emerging technologies including event processing, feature extraction, cloud computing, Fog/Edge computing and Software-Defined-Networks (SDNs). We also present the need for better routing and Physical-Medium Access Control (PHY-MAC) protocols for M-IoT. Finally, we present a detailed discussion on the open research issues and several potential research areas related to emerging multimedia communication in IoT.

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Multimedia Internet of Things: A Comprehensive Survey

In this paper, the fixed-time synchronization control problem of memristive multidirectional associative memory neural networks (MMAMNNs) is considered. Based on the nonlinear and chaos characteristics of memristor, a chaotic model is constructed. And then, utilizing the Lyapunov stability theory, two appropriate controllers are constructed and different activation functions are used. This control method ensures that drive system and response system can achieve synchronization within a fixed time. So, compared with previous studies, it has more practical value. In addition, we present a fixed-time synchronization chaotic encryption method, the chaos characteristic of the model is used to encrypt plaintext, and the decryption of ciphertext is realized based on the synchronization control theories. Finally, several numerical simulations are given to demonstrate the validity of the theories and the chaotic secure communication scheme.

Fixed-time synchronization control of memristive MAM neural networks with mixed delays and application in chaotic secure communication

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rnc.4388

Finite‐time stability of linear fractional‐order time‐delay systems

A new Lyapunov functional for stability analysis of neutral-type Hopfield neural networks with multiple delays

In this paper, new control scheme is considered for exponential synchronization of coupled neutral-type neural networks (NTNNs) with both bounded discrete-time delay and unbounded distributed delay (mixed delays). It is assumed that only the measured output can be utilized to design the controller. Quantized output controllers (QOCs) are considered to save the bits rate of communication channels and the bandwidth. The main difficulty in solving this problem is to cope with the neutral terms, the delays, and the uncertainties induced by the quantization simultaneously. By designing new Lyapunov–Krasovskii functionals and proposing novel analytical techniques, sufficient conditions are derived to ensure the exponential synchronization of the interested NTNNs. The control gains are given by solving a set of linear matrix inequalities (LMIs), which are not necessarily to be negative-definite matrices. Numerical examples are provided to verify the effectiveness and merits of the proposed approach.

Exponential synchronization of coupled neutral-type neural networks with mixed delays via quantized output control

The Internet of Things (IoT) has attracted extensive attention in the information field. Its rapid development has promoted several monitoring application domains. However, the resource constraint of sensor nodes and the security of data transmission have emerged as significant issues. In this paper, an image communication system for IoT monitoring applications is exploited to solve the above-mentioned problems simultaneously. The proposed system can satisfy the requirements of sensor nodes for low computational complexity, low-energy consumption, and low storage overhead. We also present a new compressed sensing (CS) model, as well as the corresponding parallel reconstruction algorithm, which help to reduce the image encryption/decryption time. Based on chaotic systems, we integrate the quantization and diffusion operations into the system to further enhance the transmission security. The simulations are executed to demonstrate the feasibility and the effectiveness of the proposed method. Compared with the traditional CS, our numerical results indicate that the proposed model reduces 413 ms computation time and 3.13 × 10
 6
 elements stored for large-scale images. Besides, we verify the flexibility and the diversity of choosing two submatrices for different-sized images. Experimental results also show the proposed system performs well in terms of security performance. Particularly the key space reaches 2253.

Efficient and Secure Image Communication System Based on Compressed Sensing for IoT Monitoring Applications

In this paper, we mainly investigate the finite-time generalized projective lag synchronization of neutral-type neural network with delay. With the help of the definition of finite-time generalized projective lag synchronization and Gronwall–Bellman inequality, the generalized projective lag synchronization is achieved between drive-response neural networks via a nonlinear feedback controller. Some novel and easily verifiable sufficient conditions are obtained. Many existing works can be regarded as special cases of our conclusions. Finally, we provide two simulation examples to verify the correctness of main results.

Zeming Wang

Papers

Efficient and Secure Image Communication System Based on Compressed Sensing for IoT Monitoring Applications

Finite-time generalized projective lag synchronization criteria for neutral-type neural networks with delay