Design Of Communication Protocols Research Articles

Attention to Entropic Communication

AbstractThe concept of attention has proven to be very relevant in artificial intelligence. Relative entropy (RE, aka Kullback‐Leibler divergence) plays a central role in communication theory. Here, these concepts, attention, and RE are combined. RE guides optimal encoding of messages in bandwidth‐limited communication as well as optimal message decoding via the maximum entropy principle. In the coding scenario, RE can be derived from four requirements, namely being analytical, local, proper, and calibrated. Weighted RE, used for attention steering in communications, turns out to be improper. To see how proper attention communication can emerge, a scenario of a message sender who wants to ensure that the receiver of the message can perform well‐informed actions is analyzed. In case only the curvature of the utility function maxima are known, it becomes desirable to accurately communicate an attention function, in this case a by this curvature weighted and re‐normalized probability function. Entropic attention communication is here proposed as the desired generalization of entropic communication that permits weighting while being proper, thereby aiding the design of optimal communication protocols in technical applications and helping to understand human communication. It provides the level of cooperation expected under misaligned interests of otherwise honest communication partners.

Indoor environmental wellness index (IEW-Index): Towards intelligent building systems automation and optimization

The impact of indoor environment quality (IEQ) on occupants’ wellness and productivity is substantial. Simultaneously, due to buildings’ significant role as one of the largest energy consumers, there is a pressing need for improved energy efficiency and intelligence in building design and operation. This paper introduces a novel indoor environmental wellness index (IEW-Index) as a real-time key performance indicator (KPI) derived from controllable factors associated with wellness. The main objective of this index is to develop a universally applicable metric for IEQ, incorporate real-time data and personalized settings, and facilitate the real-time optimization of building control systems. In addition, a novel framework based on a multi-agent system (MAS) for building control systems is introduced, encompassing a detailed design of components and communication protocols. The IEW-Index’s effectiveness has been successfully demonstrated through three real-world case studies formulated using the developed multi-agent system framework. The findings indicate a direction for creating a sustainable building automation system that is intelligent and autonomous.

Efficient and Effective Directed Minimum Spanning Tree Queries

Computing directed Minimum Spanning Tree (DMST) is a fundamental problem in graph theory. It is applied in a wide spectrum of fields from computer network and communication protocol design to revenue maximization in social networks and syntactic parsing in Natural Language Processing. State-of-the-art solutions are online algorithms that compute DMST for a given graph and a root. For multi-query requirements, the online algorithm is inefficient. To overcome the drawbacks, in this paper, we propose an indexed approach that reuses the computation result to facilitate single and batch queries. We store all the potential edges of DMST in a hierarchical tree in O(n) space complexity. Furthermore, we answer the DMST query of any root in O(n) time complexity. Experimental results demonstrate that our approach can achieve a speedup of 2–3 orders of magnitude in query processing compared to the state-of-the-art while consuming O(n) index size.

Distributed Relative Localization Algorithms for Multi-Robot Networks: A Survey

For a network of robots working in a specific environment, relative localization among robots is the basis for accomplishing various upper-level tasks. To avoid the latency and fragility of long-range or multi-hop communication, distributed relative localization algorithms, in which robots take local measurements and calculate localizations and poses relative to their neighbors distributively, are highly desired. Distributed relative localization has the advantages of a low communication burden and better system robustness but encounters challenges in the distributed algorithm design, communication protocol design, local network organization, etc. This paper presents a detailed survey of the key methodologies designed for distributed relative localization for robot networks. We classify the distributed localization algorithms regarding to the types of measurements, i.e., distance-based, bearing-based, and multiple-measurement-fusion-based. The detailed design methodologies, advantages, drawbacks, and application scenarios of different distributed localization algorithms are introduced and summarized. Then, the research works that support distributed localization, including local network organization, communication efficiency, and the robustness of distributed localization algorithms, are surveyed. Finally, popular simulation platforms are summarized and compared in order to facilitate future research and experiments on distributed relative localization algorithms.

Artificial Intelligence Machine Learning in Healthcare System for improving Quality of Service

A vital element of widespread patient monitoring is consistency in transmission between the patients and the healthcare professionals not including time and position dependencies. Artificial intelligence (AI) and machine learning (ML) techniques have a vast possibility to proficiently handle the automated function of the mobile nodes distributed in the Mobile ad-hoc network (MANET). ML is a part of AI in that the computer algorithms learn themselves by improving from historical experiences. The main issues in MANET are autonomous operation, maximization of a lifetime, coverage of the network, energy utilization, connectivity issues, quality of service, high bandwidth necessity, communication protocol design, etc. ML is valuable for data aggregation, and it saves the energy of mobile nodes and enhances the network lifetime. In this paper, we propose an Artificial Intelligence Machine Learning Algorithm for improving the Quality of Service in MANET (AIMQ). ML techniques based on artificial neural networks (ANN) algorithm is helpful for data aggregation tasks. This approach formed the clusters by node mobility and connectivity. Glowworm Swarm Optimization (GSO) algorithm is applied in every cluster to choose a proficient Cluster Head (CH). Here, we choose the CH by GSO fitness function based on mobile node degree, node distance, node reliability, and energy. ANN algorithm recognizes and chooses the data aggregator with great energy and more extended stability. It updates the weight of input parameters such as node energy, node degree, packet loss ratio, and node delay to reduce the errors. It minimizes the repetitive CHs selection and member nodes’ re-affiliation in a cluster.

Mission-based PTR triangle for multi-UAV systems flight planning

The Unmanned Aerial Vehicle (UAV) domain, especially the design of UAV cooperative systems, is one of the most important research and applied fields nowadays. The multi-UAV system design is a wealth of research points under the flight planning umbrella, including the design of communication protocols for the Flying Ad-hoc Network (FANET) connecting UAVs, and the inevitable flight design aspects which are the mission planning and path planning. With the fact that topology and routing are the communication design parts most affected by FANET's highly dynamic 3D movement, this paper introduces a design concept for multi-UAV system flight plan that has been named mission-based PTR triangle to indicate the importance of joint optimization of the three design pillars: Path planning, Topology control, and Routing strategy based on mission requirements. These aspects are very interconnected; they determine the UAV positions and relative placement and how the UAVs are connected; any of them can influence or be influenced by the other. They can be regarded as a single process and the trade-off between their parameters controls their influence. In addition, most of the flight planning operations are confined to a PTR triangle its edges represent cross-layer or joint optimization associations, results in different optimization cases to support adaptive optimality suitable to the dynamic nature of FANET, design constraints, and variety in mission scenarios. To this end, this paper sheds light on and reviews the work done on each process and on the mission analysis, including classifications, approaches, and examples of separate and cross-layered optimization. The paper drew a roadmap for flight planning employing the mission-based PTR triangle design approach with a proof-of-concept to the PTR joint optimization ideas. The paper serves as an entry point to the interested researchers in the field of UAV systems design.

Enhancing Heterogeneous Wireless Sensor Networks Using Swarm Intelligence –Based Routing Protocols

The design of efficient communication protocols for wireless sensor networks has aroused great interest in the research community, especially in the face of the limited energy of sensor nodes and the frequent change in network topology. Routing remains a challenging problem in wireless communications, as deploying or replacing sensor nodes in hazardous environments is difficult. Many studies have been devoted to alleviate certain limitations, such as clustering to maintain network connectivity, injecting heterogeneity to avoid the rapid death of nodes, or incorporating evolution-based optimization methods to find the best network configuration. This work combined heterogeneity and swarm-based optimization to efficiently balance energy consumption between nodes to increase network reliability. Specifically, this work employed the binary particle swarm optimizer and the binary artificial bees colony optimizer to find approximately the optimal set of cluster heads (CHs) with their optimal number. Based on the probabilistic principle of the heterogeneous protocols: SEP, EDEEC, and BEENISH, a new refined formulation of CHs selection using swarm optimization is proposed. The swarm flight is guided towards the best CHs with an objective function representing a good balance between the initial and residual energy of nodes. Compared to the standard heterogeneous protocols SEP, EDEEC, and BEENISH, the developed protocols significantly perform better in terms of stability (FND), the round of half nodes' death (HND), the network lifetime (LND), and energy saving. Indeed, the BABC-SEP was found 31,66% better than SEP in terms of remaining energy percentage, and CHs selection in EDEEC and BEENISH using BABC improved them by more than 20% in the percentage of remaining energy.

A Distributed Clustering Based Energy Management Scheme for Heterogenous Wireless Sensor Network

The Internet of Things (IoT) is an emerging paradigm that offers a wide array of benefits for real-world applications. An IoT system is supported by a network of heterogeneous sensor nodes that collect information about the environment over time. The non-rechargeable batteries and energy constraints limit the network's lifespan. For this reason, controlling energy dissipation is one of the most important considerations when designing communication protocols for sensor networks. The clustering scheme is one of the most efficient ways to help networks be more energy-efficient. However, the majorities of existing protocols do not handle energy distribution among heterogeneous sensor nodes well and are inappropriate. The purpose of this paper is to emphasize cluster head selection criteria and to propose an energy management clustering mechanism that takes heterogeneity into account. A dense deployment of heterogeneous multi-level nodes is considered in the proposed scheme to improve the nodes' stability and power efficiency. The threshold probability for selecting optimal CH nodes is determined by an energy-balanced weighted parameter. The proposed scheme is implemented on a numerical computing tool MatLab. In terms of alive nodes, dead nodes, packets sent to the base station, and processing time, the simulation provides efficient results. When compared to similar existing approaches, the proposed scheme was more successful in terms of network lifetime, stability, delay, and packet delivery.

Research on IOT Control module for Smart Kitchen Based on AIOT Technology

In the Internet of Things, the smart kitchen field has broad market prospects and development potential. In order to solve the problems of wireless kitchen electric system in smart kitchen, such as lack of universality, poor autonomy and controllability, vulnerability to network attacks which lead to illegal data theft. In this paper, an IOT control module for smart kitchen based on AIOT is proposed. Through the design of module hardware and MQTT communication protocol, problems such as few wireless links supported by the IOT control module and no national security algorithm for security authentication can be solved. It can connect various smart kitchen appliances in the smart kitchen system and ensure the security of data.

Research on Remote Online Firmware Upgrade System for Embedded Devices

<p>To effectively reduce the cost of firmware upgrade and maintenance of embedded devices, according to the requirement of a remote firmware update of embedded devices, this paper proposes a remote online firmware upgrade technology based on ZigBee. Combined with the requirements of remote online firmware upgrade application of tower-mounted amplifier, this paper analyzes and studies the system requirements, ZigBee module selection and design, software design and implementation (communication protocol design of host and slave program, breakpoint continuation function), fault analysis and other aspects. Designed experiments and tested the ZigBee connection success rate under the device startup state and normal operation state, the relationship between transmission firmware size and transmission success rate, system CPU resource consumption, transmission distance, transmission rate, the success rate, data reuse rate and acceleration ratio of breakpoint continuation function, and other performance indicators. The experimental results show that the remote online firmware upgrade technology based on ZigBee for embedded devices can better meet the system’s performance requirements in all aspects and improve the data reuse rate and acceleration ratio in the process of data transmission. The experimental results show that this scheme has the advantages of simplicity, low cost, high reliability, and broad application prospects.</p> <p> </p>

Edge Intelligence Enabled Heterogeneous Multi-Robot Networks: Hybrid Framework, Communication Issues, and Potential Solutions

Heterogeneous multi-robot systems have been increasingly employed to collaboratively execute tasks in harsh and unknown environments. High-quality collaboration requires robots to efficiently communicate with each other and have ample intelligence to deal with uncertainties and emergencies. However, these demands are still difficult to be satisfied under existing single-mode networking architectures and onboard computing paradigms. Therefore, this article first develops a hybrid edge-aided framework for multi-robot collaboration, where the centralized and decentralized modes are elegantly combined to support a robust and efficient network, while an edge intelligence platform with powerful servers and base stations is employed to provide abundant intelligence. Under this framework, we discuss three critical communication issues that keep robots coordinated and guarantee efficient information sharing. The issues include network construction among heterogenous robots, bandwidth-efficient communication protocol design, and link transmission adaption. For each issue, potential solutions are provided and the challenges that need to be further explored are also discussed.

Guest Editorial Special Issue on Antenna Array Enabled Space/Air/Ground Communications and Networking

With the rapid development of electronic and information technologies, the Internet of Everything (IoE) has become one of the trendiest topics in both academia and industry. Therein, many types of space/air/ground platforms need to be connected to networks for breaking down the isolation of information islands and providing various services. Space/air/ground platforms, such as satellites, unmanned aerial vehicles (UAVs), airships, balloons, terrestrial vehicles, and high-speed trains (HSTs) have emerged for accomplishing various complex tasks. Wireless communication is one of the most important technologies to support the real-time delivery of control commands and mission-related data. On the other hand, the space-air-ground integrated network has become a promising paradigm for the six-generation (6G) mobile communication network, where the aerospace and terrestrial vehicles may need to connect to existing mobile cellular networks or act as base stations (BSs) or relays to assist terrestrial wireless communications. To meet the ever-increasing demands of high capacity, wide coverage, low latency, and strong robustness for communications, it is promising to adopt large-scale antenna arrays at the transceivers to obtain considerable array gains and improve the channel quality. Antenna array-enabled beamforming technologies can facilitate spectrum reuse, interference mitigation, coverage enhancement, and physical-layer security. Antenna arrays can also be used to promote the sensing capability of space/air/ground networks, where the sensing information may be carefully processed to assist communications. However, enabling antenna array for space/air/ground communication networks poses specific, distinctive, and tricky challenges in antenna array design, physical layer, multiple access control layer, and network layer. As a result, numerous new research issues require to be addressed, which cover a wide range of disciplines including communication theory, network theory, antenna theory, signal processing, protocol design, resource allocation, optimization, hardware implementation, and experimentation.

A Novel Chaotic Shark Smell Optimization With LSTM for Spatio-Temporal Analytics in Clustered WSN

Wireless sensor networks (WSN) include massive deployment of sensor nodes to observe the physical environment. At the same time, the spatial and temporal correlations that come with the collaborative characteristics of the WSN pose considerable benefits in the design of effective communication protocols designed for the WSN environment. At the same time, energy efficiency is considered a vital challenge in WSN and can be solved by the use of clustering techniques. In this aspect, this study presents a new chaotic shark smell optimization (CSSO) with long short-term memory (LSTM), called the CSSO-LSTM technique for spatiotemporal analytics in clustered WSN. Primarily, a chaotic shark smell optimization (CSSO) based clustering technique is derived, which is based on the spatial correlation that exists among the sensor nodes. The CSSO algorithm derives an objective function involving different input parameters to select cluster heads (CHs) and construct clusters.

Cantor Pairing lightweight key generation for wireless body area networks

Wireless Body Area Networks (WBAN) are getting grandness due to the low-cost digital sensor communication devices. Implantable tiny sensor nodes and wearable sensor nodes are getting membership in a WBAN network. The characteristics of these member nodes are hugely different in terms of processing power and communication technology. Therefore, the nature of a WBAN network comes under heterogeneous category. Combining different types of nodes under one roof with a communication protocol is one of the perplexed tasks of WBAN. Security and Power consumption are the prime concerns in WBAN networks. High security communication protocols consume more power whereas low power consuming protocols lack some security. Equilibrating the balance between power, performance and security is an inevitable chore while designing communication protocols for WBAN. This work named as Cantor Pairing Light Weight Key Generation (CPLKG) is targeted to improve the security without impacting the performance in terms of Throughput, End-to-End delay, Packet Delivery Ratio, Memory and Power consumption. Device ID Hash Function (DHF), Cantor Pairing Key Generation (CPKG) and Cantor Pairing Key Revocation (CPKR) are the contributed functional blocks used to construct the proposed CPLKG method.

Message exchange dynamics in wireless biological nanonetworks

SummaryDiffusive biological nanonetworks have been established as a communication physical layer option and are envisaged to govern the development of future nanonetwork communications. Being the major communication paradigm in biological environments, it allows biological nanomachines to communicate through exchanging pulses of molecules in an aqueous medium being endogenous to these dimensions and following the requirements for biocompatibility and interoperability. The peculiarities of this nanoscale level, related mostly to the channel and the message carriers, hinder the performance of communication protocols. Therefore, in this work, parameters that affect the communication at the lowest level are being analyzed bringing new insights in the sector. Analyzing the major components that take part in the reception process, the dynamics of message transfer between nanonodes are revealed by a plethora of simulation scenarios. By entering into the equation the dynamics of chemotaxis, the behavior of such a system is scrutinized pertaining to the communication performance and stability. The proposed analysis revealed that unlike electromagnetic nanonetworks and due to the nature of the medium, there are factors that should be foreseen in the design of biological communication protocols. These significant deductions are supplementary to the established work, by shedding light on the special characteristics of biological communication entities and the way they affect the information exchange.

Design and Implementation of an Underwater Information Acquisition System Prototype Based on Optical Fiber Communication

Ocean observation plays an important role in many areas, such as marine scientific research, environmental expedition, and resource exploitation. Traditional observation generally acquires periodical marine information and lacks real-time performances. To realize underwater observation of multi-information in real-time, an information acquisition system is designed in this study based on optical fiber communication. A multichannel interface between the diverse sensors and the slave computer is designed. It shields discrepancies of different sensor data and allows collecting information of various types, including conductivity, temperature, depth (CTD), attitudes, and images. At the same time, the full communication link is designed by constructing an optical fiber channel in collaboration with RS485 and USB. It provides a higher-rate link for real-time data transmission from underwater to overwater. Then, software procedures are, respectively, developed for the slave computer and the master computer based on the designed communication protocol. Additionally, a PC-based user interface is designed to realize data receipt, file saving, information display, and image restoration. Finally, an acquisition prototype is developed, and an underwater experiment is conducted to evaluate its performance. The results show that the underwater CTD, attitudes, and images can be collected and transmitted in real time. From its higher transmission rate and lower packet loss rate, the accuracy and the stability of the prototype are verified. The implementation of the acquisition prototype follows the trends of laying and networking submarine optical fiber cables. Therefore, its application can be expanded for ocean observation in information collecting, transmitting, and processing.

LoRaWAN Communication Protocols: A Comprehensive Survey under an Energy Efficiency Perspective

Long range wide area networks (LoRaWANs) have recently received intense scientific, research, and industrial interest. LoRaWANs play a pivotal role in Internet of Things (IoT) applications due to their capability to offer large coverage without sacrificing the energy efficiency and, thus the battery life, of end-devices. Most published contributions assume that LoRaWAN gateways (GWs) are plugged into the energy grid; thus, neglecting the network lifetime constraint due to power storage limitations. However, there are several verticals, including precision agriculture, forest protection, and others, in which it is difficult or even impossible to connect the GW to the power grid or to perform battery replacement at the end-devices. Consequently, maximizing the networks’ energy efficiency is expected to have a crucial impact on maximizing the network lifetime. Motivated by this, as well as the observation that the overall LoRaWAN network energy efficiency is significantly affected by the selected communication protocol, in this paper, we identify and discuss critical aspects and research challenges involved in the design of a LoRaWAN communication protocol, under an energy efficiency perspective. Building upon our findings, research directions towards a novel GreenLoRaWAN communication protocol are given, focusing on achieving energy efficiency, robustness, and scalability.

CoFA for QoS based secure communication using adaptive chaos dynamical system in fog-integrated cloud

Fog computing addresses the issues experienced in Cloud computing such as latency, delay, and bandwidth while provisioning the resources such as computation, storage, and network for IoT applications. Fog resources and their integration with Cloud poses other significant problems such as data security, overhead in data acquisition, data tampering, data privacy, data breach, etc. Designing a secure, resilient, and scalable infrastructure for IoT network is challenging because of resource heterogeneity, resource-constrained devices, and unreliable network connectivity. The researchers have developed many chaos-based encryption algorithms to enhance the security level and make it difficult for intruders to access the data. However, such traditional algorithms increase the communication overhead and computational cost. This necessitates the design of new secure communication protocols that comply with various security requirements of Class of Fog Applications (CoFA). This work proposes an efficient and intelligent method that classifies the applications arriving at the system into CoFA and maps them to five levels of chaos-based security protocols for secure communication. An adaptive sliding mode security schemes are developed using Genesio-Tesi, Modified-Jerk, Chua's chaotic, and Financial systems in CoFA framework for secure communication. A comparison-based performance study, with state-of-art, reveals the efficacy of the proposed method, which performs better for security optimization and synchronization with the least error.

Unequal error protection transmission for federated learning

Communication has been recognized as one of the primary challenges of federated learning (FL), but the actual communication algorithm or protocol design is still rarely involved in the existing studies. In the paper, viewing the model exchange in FL as a special kind of traffic, an unequal error protection (UEP) scheme is designed based on multi-rate channel coding and multi-layer modulation for it. To answer the question of how to make error control for FL when the wireless channel is no longer simplified as a pipeline, this paper firstly theoretically analyzes the impact of transmission error on machine leanring (ML) model, which reveals that the dynamic range of the weights should be taken into consideration. Guided by the analysis, the UEP scheme is applied to FL in multiple perspectives including parameter, network and time. Furthermore, a UEP-based adaptive coding method is developed for the case with dynamic signal-to-noise ratio (SNR) to ensure faster and more stable convergence of the FL model while saving as much bandwidth as possible. Comprehensive numerical simulation on several real-world datasets verifies that the proposed UEP transmission schemes can indeed bring significant benefits in accuracy, robustness and efficiency, especially when the channel condition is poor.

Network Communication Protocol Design from the Perspective of Batched Network Coding

Most existing network communication systems, such as the Internet, are built around the TCP/IP protocol stack. However, TCP/IP cannot effectively support the upcoming network communication systems with more wireless communication links and higher requirements in terms of throughput, latency, and reliability. In this article, we introduce a general network communication protocol design based on batched network coding (BNC), which includes the existing framework as a special case and whose design can be guided by channel coding theory. BNC-based protocols can have significant throughput gain for single-hop or multihop wireless communications and provide better trade-off among throughput, latency and reliability.