Search

Due to their promising applications and intriguing characteristics, Unmanned Aerial Vehicles (UAVs) can be dispatched as flying base stations to serve multiple energy-constrained Internet-of-Things (IoT) sensors. Moreover, to ensure fresh data collection while providing sustainable energy support to a large set of IoT devices, a required number of UAVs should be deployed to carry out these two tasks efficiently and promptly. Indeed, the data collection requires that UAVs first make Wireless Energy Transfer (WET) to supply IoT devices with the necessary energy in the downlink. Then, IoT devices perform Wireless Information Transmission (WIT) to UAVs in the uplink based on the harvested energy. However, it turns out that when the same UAV performs WIT and WET, its energy usage and the data collection time are severely penalized. Worse yet, it is difficult to efficiently coordinate between UAVs to improve the performance in terms of WET and WIT. This work proposes to divide UAVs into two teams to behave as data collectors and energy transmitters, respectively. A Multi-Agent Deep Reinforcement Learning (MADRL) method, called TEAM, is leveraged to jointly optimize both teams’ trajectories, minimize the expected Age of Information (AoI), maximize the throughput of IoT devices, minimize the energy utilization of UAVs, and enhance the energy transfer. Simulation results depict that TEAM can effectively synchronize UAV teams and adapt their trajectories while serving a large-scale dynamic IoT environment. [ABSTRACT FROM AUTHOR]

Due to the dynamic nature of connectivity in terrestrial vehicular networks, it is of great benefit to deploy unmanned aerial vehicles (UAVs) in these networks to act as relays. As a result, a remarkable number of studies have exploited UAVs to bridge the communication gaps between terrestrial vehicles, and sometimes despite their unoptimized mobility, their restricted communication coverage, and their limited energy resources. However, it was noted that for an intermittently connected vehicular network, UAVs could not cover all sparse areas all the time. Even worse, when deploying enough UAVs to cover all these areas, the probability of inter-UAV collisions increases, and it will be complex to control their movements efficiently. Consequently, it is required to dispatch an organized and intelligent group of UAVs to perform communication relays in the long term while keeping their connectivity, minimizing their average energy consumption, and providing an efficient coverage strategy. To meet these requirements, we propose a deep reinforcement learning (DRL) framework, called DISCOUNT (Dispatch of UAVs for Urban VANETs). Extensive simulations have been conducted to evaluate the performance of the proposed framework. It has been shown that the proposed framework significantly outperforms two commonly-used baseline techniques and some reinforcement learning methods in terms of energy consumption, coverage, and routing performances. [ABSTRACT FROM AUTHOR]

With increasing vehicle density and the growth of accidents in urban areas, navigation management becomes a serious problem. Even though there is a multitude of navigation systems, ambulances, taxis, or even ordinary vehicles, sometimes find it challenging to reach their destinations on time. There are two main reasons for this difficulty: (i) lack of local knowledge of the area of navigation solutions and (ii) their inflexibility against unforeseeable situations that may occur on the roads. Indeed, the majority of navigation solutions are based only on the distance, the journey time, or even statistics related to the density of vehicles to plan the full paths, while neglecting the dynamic nature of the vehicle traffic. Also, their respective centralized architectures are unable to monitor both the traffic and unexpected events continuously and in real-time without not being overloaded by the flow of message exchanges between the road entities and the central processing entity. To address these issues, we propose in this paper a novel three-tier architecture, called SDN-enabled Approach for Vehicle Path-Planning (SEARCH), to enhance the situation awareness on urban roads, efficiently collect traffic information in real-time, and decide the best navigation strategy. The proposed architecture exploits Unmanned Aerial Vehicles (UAVs), Vehicular Ad hoc Networks (VANETs), 5G based cellular systems, and Software-Defined Networking (SDN) to provide better and faster communication to changing road conditions. Based on these technologies, some parameters related to vehicles and driving environments, such as speed, distance, traffic jams, incidents, and travel flow, are efficiently collected and dynamically exploited to achieve faster paths between any existing pairs of locations. Furthermore, the deployed architecture of SEARCH can provide sufficient bandwidth to support all data traffic needs to update vehicles during their journey efficiently and in real-time. To evaluate the performance of our architecture, we conduct a series of simulations and perform a set of comparisons with relevant route planning algorithms. We found that the proposed architecture works effectively in terms of saving on driving time to reach any target destinations. [ABSTRACT FROM AUTHOR]

SUMMARY Mobility management is required to ensure the session continuity for multiple Internet Protocol-enabled devices onboard a satellite that hands off between ground stations. Network Mobility (NEMO) can efficiently manage the mobility of multiple Internet Protocol-enabled devices that are connected as a mobile network. However, existing mobility management solutions for satellite networks are unable to route through intermediate satellites links when a direct connection with a ground station is lost. We proposed an architecture of NEMO in satellite networks with routing through multiple satellite links using nesting, where a mobile network connects to another mobile network. However, NEMO Basic Support Protocol can be inefficient in satellite networks because of poor nesting formation leading to the routing loop, inefficient routes, and overloaded links. We extended NEMO Basic Support Protocol for the efficient use in satellite networks by augmenting it with a decision criteria for the nesting. Results verify that the extended protocol ensures loop-free and continuous connection despite the loss of direct connection to the ground and provides an insight on how to form the nested NEMO to avoid overloading. The architecture and the extended NEMO protocol can be used for the efficient and continuous transfer of data from satellite networks to the ground. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Characteristics of wireless sensor networks, specifically dense deployment, limited processing power, and limited power supply, provide unique design challenges at the transport layer. Message transmission between sensor nodes over a wireless medium is especially expensive. Care must be taken to design an efficient transport layer protocol that combines reliable message delivery and congestion control with minimal overhead and retransmission. Sensor networks are created using low cost, low power nodes. Wireless sensors are assumed to have a finite lifetime; care must be taken to design and implement transport layer algorithms that allow maximum network lifetime. In this paper we present current and future challenges in the design of transport layers for sensor networks. Current transport layer protocols are compared based on how they implement reliable message delivery, congestion control, and energy efficiency. [ABSTRACT FROM AUTHOR]

With the convergence of wireless communication and IP-based networking technologies, future IP-based wireless networks are expected to support real-time multimedia. IP services over wireless networks (e.g. wireless access to Internet) enhance the mobility and flexibility of traditional IP network users. Wireless networks extend the current IP service infrastructure to a mix of transmission media, bandwidth, costs, coverage, and service agreements, requiring enhancements to the IP protocol layers in wireless networks. Furthermore, QoS provisioning is required at various layers of the IP protocol stack to guarantee different types of service requests, giving rise to issues related to cross-layer design methodology. This paper reviews issues and prevailing solutions to performance enhancements and QoS provisioning for IP services over mobile wireless networks from a layered view. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In recent years, there has been a strong interest in transmitting compressed video over packet switched networks, such as asynchronous transfer mode (ATM). Previous work has dealt with transmitting MPEG over constant bit rate (OW) and variable bit rate (VER) services of ATM. The available bit rate (ABR) service of ATM is expected to be much more cost effective than OW or VBR. However, there hasn't been much work done on running interactive client/server applications (for example, video on demand) over ABR. In this paper, we have developed a framework to design interactive video systems transmitting MPEG video over the ATM ABR service. We have developed models to determine the network connection parameters required to run interactive client/server multimedia applications over an ATM network using the ABR service. We solve our model using real-time dynamic equilation (RTDE) analysis. We conclude that by proper dimensioning of the buffers at the client and the server, it is possible to run interactive video over the ATM ABR service. [ABSTRACT FROM AUTHOR]

The Stream Control Transmission Protocol (SCTP) is being standardized by the IETF as a reliable transport protocol to transport SS7 signaling messages over IP networks. Due to its attractive features such as multistreaming and multihoming, SCTP has received much attention from the network community, in terms of both research and development. This article introduces the main features of SCTP, and discusses the state of the art in SCTP research and development activities. We also provide a survey of the available products that use SCTP. Finally, with a view to stimulating further research in this area, the challenges faced by the SCTP research community are identified. [ABSTRACT FROM AUTHOR]

Presents a study that proposed a novel selective retransmission scheme for multimedia transmission over wireless networks. Illustration of the system model and the proposed transmission scheme; System analysis; Minimum receiver buffer requirement.

The low pass filter (LPF) algorithm, which is used to calculate the average queue length in the random early detection (RED) algorithm, results in a poor response time when RED recovers from congestion. In this paper, we propose a new algorithm, called low pass filter/over drop avoidance (LPF/ODA), to improve the response time of RED. LPF/ODA is based on reducing the time required by RED to recover from long-term congestion. Simulation results have been used to show that the proposed LPF/ODA algorithm significantly improves the response time, throughput and delay of RED gateways. Copyright © 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Continued progress in both civil and military radio-frequency (RF) digital avionics applications is overstressing the capabilities and reliability of existing RF communication networks based on coaxial cables on board modern aircrafts. Future avionics systems will require high-bandwidth on-board communication links that are lightweight, immune to electromagnetic interference, and highly reliable. Fibre-optic networks can meet all these challenges in a cost-effective manner. Recently, on-board fibre-optic communication systems, where a fibre-optic network acts like a local area network (LAN) for digital data communications, have become a topic of extensive research and development. However, modern digital avionics systems require a system capable of transporting microwave and millimeter-wave RF signals that carry digital data on board an aircraft. Such optical networks transporting RF signals are completely different from the digital fibre-optic communication systems. Recent advances in optoelectronics technology, including linear optoelectronic devices and wavelength division multiplexing (WDM), have opened a number of possibilities for designing on-board fibre-optic networks, including all-optical networks for digital avionics RF signal communication. The objective of this paper is to present a number of optical network architectures for transmitting RF signals carrying digital data in an aircraft. In this paper, we investigate a number of different approaches, including all optical architectures, for building an optical network using fibre-optic transmission of on-board VHF and UHF RF signals. The relative merits and demerits of the network architectures are discussed, and the suitability of the architectures for particular applications is presented. Copyright © 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Studies the effect of hot spots on the performance of buffered multiple-bus systems. Analytical models for determining the bandwidth of buffered multiple-bus systems in the presence of a hot spot memory request pattern; Modeling assumptions; Comparison of the performance of buffered and unbuffered systems.

Interactive Video on Demand with Instantaneous Access (IVoD-i) can offer users with VCR like functions by sending requests to video servers. Earlier work has shown that the Available Bit Rate Service of ATM networks can be effectively used for interactive video on demand. However, non optimal values of the connection setup parameters can affect the Quality of Service (QoS) at the user. This is because the ABR service only provides minimum bandwidth guarantee for a connection. The objective of this paper is to provide QoS to IVoD-i over the ABR service of ATM. To achieve this objective, we have developed an analytical framework to determine the ABR connection parameters to guarantee QoS to IVoD-i users. Our proposed framework has been tested with real life MPEG video traces. Results show that our framework can provide QoS to IVoD-i users. Moreover, our framework outperforms previous schemes in terms of startup delay, user buffer requirement, and jitter. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT)-inspired drone environment is having a greater influence on daily lives in the form of drone-based smart electricity monitoring, traffic routing, and personal healthcare. However, communication between drones and ground control systems must be protected to avoid potential vulnerabilities and improve coordination among scattered UAVs in the IoT context. In the current paper, a distributed UAV scheme is proposed that uses blockchain technology and a network topology similar to the IoT and cloud server to secure communications during data collection and transmission and reduce the likelihood of attack by maliciously manipulated UAVs. As an alternative to relying on a traditional blockchain approach, a unique, safe, and lightweight blockchain architecture is proposed that reduces computing and storage requirements while keeping privacy and security advantages. In addition, a unique reputation-based consensus protocol is built to assure the dependability of the decentralized network. Numerous types of transactions are established to characterize diverse data access. To validate the presented blockchain-based distributed system, performance evaluations are conducted to estimate the statistical effectiveness in the form of temporal delay, packet flow efficacy, precision, specificity, sensitivity, and security efficiency. [ABSTRACT FROM AUTHOR]

The number of cyber-attacks targeting the Internet of Things (IoT) has elevated in the last decade. This is due to the inherent security vulnerabilities inside IoT endpoints, as well as the broad acceptance and usage of Industrial IoT. In this context, botnets have arisen as a significant risk to IoT-based infrastructures by exploiting security flaws in firmware, including weak or default passwords, to hack devices. In this article, research is performed on an Intrusion Detection System (IDS) that can be installed within an IoT device to increase visibility and help devices become more secure. The presented research framework termed a Blockchain-inspired Botnet Detection System (BDS) includes the node-level IDS. Moreover, the comprehensive architecture of the node-level BDS framework is discussed. Using the ISOT, IoT23, and BoTIoT datasets, the performance of the presented model is assessed for alerts, detection rates, detection delay, and peak CPU and memory usage. Based on the computational results effective outcomes were registered for the proposed technique. [ABSTRACT FROM AUTHOR]

A model for the analysis of multistage switches based on shared buffer switching for Asynchronous Transfer Mode (ATM) networks is developed, and the results are compared with the simulation. Switches constructed from shared buffer switches do not suffer from the head of line blocking which is the common problem in simple input buffering. The analysis models the state of the entire switch and extends the model introduced by Turner to global flow control with backpressure mechanism. It is shown that buffer utilization is better and throughput improves significantly compared with the same switch using local flow control policy. Copyright © 1999 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Presents an overview of the traffic management issues and their possible solutions for transmission of multimedia over asynchronous transfer mode (ATM) networks. Advantages of ATM networks; Background on ATM networks and its service categories; Two main issues of bandwidth allocation; Significance of continuous transmission of multimedia traffic even during congestion in the network.

More than 10-billion physical items are being linked to the internet to conduct activities more independently and with less human involvement owing to the Internet of Things (IoT) technology. IoT networks are considered a source of identifiable data for vicious attackers to carry out criminal actions using automated processes. Machine learning (ML)-assisted methods for IoT security have gained much attention in recent years. However, the ML-training procedure incorporates large data which is transferable to the central server since data are created continually by IoT devices at the edge. In other words, conventional ML relies on a single server to store all of its data, which makes it a less desirable option for domains concerned about user privacy. The Federated Learning (FL)-based anomaly detection technique, which utilizes decentralized on-device data to identify IoT network intrusions, represents the proposed solution to the aforementioned problem. By exchanging updated weights with the centralized FL-server, the data are kept on local IoT devices while federating training cycles over GRUs (Gated Recurrent Units) models. The ensemble module of the technique assesses updates from several sources for improving the accuracy of the global ML technique. Experiments have shown that the proposed method surpasses the state-of-the-art techniques in protecting user data by registering enhanced performance measures of Statistical Analysis, Energy Efficiency, Memory Utilization, Attack Classification, and Client Accuracy Analysis for the identification of attacks. [ABSTRACT FROM AUTHOR]

Drone advancements have ushered in new trends and possibilities in a variety of sectors, particularly for small-sized drones. Drones provide navigational interlocation services, which are made possible by the Internet of Things (IoT). Drone networks, on the other hand, are subject to privacy and security risks due to design flaws. To achieve the desired performance, it is necessary to create a protected network. The goal of the current study is to look at recent privacy and security concerns influencing the network of drones (NoD). The current research emphasizes the importance of a security-empowered drone network to prevent interception and intrusion. A hybrid ML technique of logistic regression and random forest is used for the purpose of classification of data instances for maximal efficacy. By incorporating sophisticated artificial-intelligence-inspired techniques into the framework of a NoD, the proposed technique mitigates cybersecurity vulnerabilities while making the NoD protected and secure. For validation purposes, the suggested technique is tested against a challenging dataset, registering enhanced performance results in terms of temporal efficacy (34.56 s), statistical measures (precision (97.68%), accuracy (98.58%), recall (98.59%), F-measure (99.01%), reliability (94.69%), and stability (0.73). [ABSTRACT FROM AUTHOR]

• A comprehensive classification of VANET clustering algorithms: strength and weakness. • Intelligence-based VANET clustering including machine learning and fuzzy logic. • The distinction between vehicle mobility as well as network mobility strategies. • A detail study of VANET multi-hop clustering strategies. Clustering is an important concept in vehicular ad hoc network (VANET) where several vehicles join to form a group based on common features. Mobility-based clustering strategies are the most common in VANET clustering; however, machine learning and fuzzy logic algorithms are also the basis of many VANET clustering algorithms. Some VANET clustering algorithms integrate machine learning and fuzzy logic algorithms to make the cluster more stable and efficient. Network mobility (NEMO) and multi-hop-based strategies are also used for VANET clustering. Mobility and some other clustering strategies are presented in the existing literature reviews; however, extensive study of intelligence-based, mobility-based, and multi-hop-based strategies still missing in the VANET clustering reviews. In this paper, we presented a classification of intelligence-based clustering algorithms, mobility-based algorithms, and multi-hop-based algorithms with an analysis on the mobility metrics, evaluation criteria, challenges, and future directions of machine learning, fuzzy logic, mobility, NEMO, and multi-hop clustering algorithms. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Network function virtualization (NFV) allows edge devices to host different types of virtual network functions (VNFs) and support Computing in the Network. Therefore, an edge device can abstract multiple VNFs of different infrastructure providers (InPs) as services and serve them at different times to act as a tenant for different InPs. Deploying edge devices is expensive and difficult to manage. Hence, crowdsourced edge devices can be used. To ensure the quality and availability of the services and the privacy of sensitive data of the service stakeholders, it is extremely important to establish a service level agreement (SLA) between an edge device owner and an InP. For monitoring of SLA compliance and enforcing accountability, a trusted platform is required. The traditional NFV management authority cannot be trusted due to its centralized characteristics. In this article, we propose a blockchain-powered framework for the SLA compliance of edge devices offering VNFs as services and introduce a smart contract-driven framework to establish trust in edge-based NFV. We analyze the performance of the proposed framework in the context of a private blockchain network. [ABSTRACT FROM AUTHOR]

The use of Virtual Private Networks (VPNs) has witnessed an outstanding rise as they aim to provide confidentiality and anonymity to communication. Despite this enormous and ubiquitous usage, VPNs come with various security, misconfiguration, and performance related issues thereby hindering the users to take maximum advantage of this revolutionary technology. To address this concern, VPN users must choose the most secure and perfect VPN solution for the smooth functioning of daily life activities. Generally, no clear set of directions is available for assisting a common VPN user thereby accentuating the need to develop an elucidated and coherent checklist that thoroughly helps in evaluating any VPN based on its security, performance, auditing, and management function. This research comprehensively surveys VPN technologies, its features, working principles, and compliance principles that evolved over the last two decades. Based on it, this research presents a new methodology in the form of a feature-enriched template to comprehensively analyze a VPN solution. Each VPN feature is given its score against the potential damage it may cause in case of failure and the probability of occurrence of that failure. In this way, the corporate sector and individual users can quantitatively and qualitatively grade available options while choosing a VPN and use it effectively. [ABSTRACT FROM AUTHOR]

In the last few years, many smart objects found in the physical world are interconnected and communicate through the existing internet infrastructure which creates a global network infrastructure called the Internet of Things (IoT). Research has shown a substantial development of solutions for a wide range of devices and IoT platforms over the past 6-7 years. However, each solution provides its own IoT infrastructure, devices, APIs, and data formats leading to interoperability issues. Such interoperability issues are the consequence of many critical issues such as vendor lock-in, impossibility to develop IoT application exposing cross-platform, and/or cross-domain, difficulty in plugging non-interoperable IoT devices into different IoT platforms, and ultimately prevents the emergence of IoT technology at a large-scale. To enable seamless resource sharing between different IoT vendors, efforts by several academia, industry, and standardization bodies have emerged to help IoT interoperability, i.e., the ability for multiple IoT platforms from different vendors to work together. This paper performs a comprehensive survey on the state-of-the-art solutions for facilitating interoperability between different IoT platforms. Also, the key challenges in this topic is presented. [ABSTRACT FROM AUTHOR]

The article focuses on the High Performance Switching and Routing (HPSR) workshop, which took place in Torino, Italy during June 24-27, 2003 under the technical co-sponsorship of IEEE and was financially supported by a number of other organizations. The workshop is the flagship meeting of the IEEE Communication Society's Technical Committee on Communication Switching and Routing. One hundred thirty participants from 24 countries attended the workshop. The technical program covered a wide spectrum of research topics, such as switch architectures, wavelength- division multiplexiing networks, scheduling algorithms, quality of service issues, metro ring networks, optical burst switching networks, resilience, protection and restoration, traffic engineering, packet lookup, classification and forwarding and routing. A lot of attention was devoted in HPSR 2003 to switch architecture. Traffic engineering is a hot topic that is tightly related to routing. Multipoint-to-point label switched path trees has been proposed as a technique to reduce label space usage.

A wireless sensor network (WSN) consists of a large number of static or mobile, low-cost, and low-power sensor nodes. And energy is one of the most important factors that should be considered. In this paper, we propose clustering-based routing protocol for dynamic networks (CRPD) to reduce energy consumption and improve energy efficiency through clustering and routing algorithms. The basic idea is to periodically update the network topology and select the node with larger degree and high residual energy as the cluster head to be responsible for data aggregation and transmission. With the nodes moving, joining, and choosing the optimal clustering radius, the energy load of the whole network can be evenly distributed to each sensor node, which can significantly prolong the network lifetime. Extensive simulations show that CRPD is more energy-efficient than the existing protocols. [ABSTRACT FROM AUTHOR]

The main challenge for embedded real-time systems, especially for mobile devices, is the trade-off between system performance and energy efficiency. Previous works mainly focused on finding an optimal tasks assignment with the minimum energy under the constraints of time or architecture. In this paper, we propose an Accelerated Search (AS) algorithm based on Dynamic Programming (DP) to obtain a combination of various task schemes which can be completed in a given time with the minimum possible energy by introducing the guaranteed probability and data migration energy. We adopt a DAG (Directed Acyclic Graph) to represent the dependent relation between tasks and develop a Minimum-Energy Model to find the optimal tasks assignment. The heterogeneous multi-core architectures can execute tasks under different voltage levels with DVFS (Dynamic Voltage and Frequency Scaling) which leads to different execution times and different consumption energies. We first design a Minimum Energy Under Probability Constraints (MEUPC) algorithm to assign a proper core and proper voltage level to each task to satisfy the probability constraints with the minimum energy and then a Leaf-Partition (LP) algorithm is used to determine the execution sequence on each core according to the position of the task in DAG. Finally, a Trading Energy For Time (TEFT) algorithm is proposed to explore the opportunity the parallelism of the tasks to reduce the execution time. The experimental results demonstrate that our approach outperforms state-of-the-art algorithms in this field (maximum improvement of 30.7%). [ABSTRACT FROM AUTHOR]

With a more Internet-savvy and sophisticated user base, there are more demands for interactive applications and services. However, it is a challenge for existing radio access networks (e.g. 3G and 4G) to cope with the increasingly demanding requirements such as higher data rates and wider coverage area. One potential solution is the inter-collaborative deployment of multiple radio devices in a 5G setting designed to meet exacting user demands, and facilitate the high data rate requirements in the underlying networks. These heterogeneous 5G networks can readily resolve the data rate and coverage challenges. Networks established using the hybridization of existing networks have diverse military and civilian applications. However, there are inherent limitations in such networks such as irregular breakdown, node failures, and halts during speed transmissions. In recent years, there have been attempts to integrate heterogeneous 5G networks with existing ad hoc networks to provide a robust solution for delay-tolerant transmissions in the form of packet switched networks. However, continuous connectivity is still required in these networks, in order to efficiently regulate the flow to allow the formation of a robust network. Therefore, in this paper, we present a novel network formation consisting of nodes from different network maneuvered by Unmanned Aircraft (UA). The proposed model utilizes the features of a biological aspect of genomes and forms a delay tolerant network with existing network models. This allows us to provide continuous and robust connectivity. We then demonstrate that the proposed network model has an efficient data delivery, lower overheads and lesser delays with high convergence rate in comparison to existing approaches, based on evaluations in both real-time testbed and simulation environment. [ABSTRACT FROM AUTHOR]

The article reports various topics discussed within the issue including one on effective offloading services and another on media independent handover.

The article discusses various reports published within the issue, including one by Y. Xiao, X. Du, and J. Zhang on Internet Protocol Television and another by J. Oh, N. Choi, and Z. Haas on the elimination of unnecessary broadcasting traffic.

The article discusses various reports within the issue on fourth generation of wireless communication, including one about the minimum interference routing with fast protection, and another one about the self composing networks that allow dynamic configuration of networks for creation of new types of networks.

A preface is presented to articles on digital communications published in this periodical.

Introduces a series of articles on the Internet technology published in the October 1, 2005 issue of the "IEEE Communications Magazine."

The article focuses on the next-generation Internet which will be characterized by large numbers of devices, high speed, and multiple services over the same network. IPv6 is the next generation of the IP protocol and has been developed by the Internet Engineering Task Force to allow a large number of IP addresses. A number of countries are already testing IPv6 services, and many service providers have adopted rnultiprotocol label switching to allow multiservice capabilities for users. Mobile IP provides a framework for allowing user mobility between IP networks. It is a network layer solution consisting of handoff and location management for mobile users. However, it does not provide quality of service guarantees and hence lacks the support of seamless iritradomain mobility.

iThe article reports that the network management platforms can be viewed as the main console in network operations for detecting faults in the infrastructure. The ability to detect problems quickly in any network is critical. Network operations personnel can rely on a graphical network map to display the operational states of critical network elements such as routers and switches. "TEAM: A Traffic Engineering Automated Manager for DiffServ-Based MPLS Networks" is a system designed by C. Scoglio, T. Anjali, J.C. de Oliveira, L.C. Chen, and I.F. Akyildiz. TEAM is designed for complete automated management of an Internet domain. It is an adaptive manager that provides the required quality of service by reserving bandwidth resources and reduces congestion in the network by distributing the load efficiently. The authors show, using experimental results, the efficiency of TEAM as a network manager in different and unpredictable traffic conditions at the expense of a limited increase in computational complexity and costs. The virtual private networks (VPNs) provide safe and secure connectivity at lower costs than leased lines, several commercial and open source VPN products are now available that can be configured to provide VPN services with varying characteristics.

Introduces the May 2003 issue of the periodical 'IEEE Communications Magazine' which contains articles regarding topics in Internet technology. Characteristics of interdomain traffic; Extension to the resource reservation protocol; Tandem-free voice over internet protocol conferencing.

Rapidly developing intelligent healthcare systems are underpinned by sixth generation (6G) connectivity, the ubiquitous Internet of Things, and deep learning (DL) techniques. This portends a future where 6G powers the Internet of Medical Things (loMT) with seamless, large-scale, and real-time connectivity among entities. This article proposes a convolutional neural network (CNN)-based federated learning framework that combines secure multi-party computation (SMPC) based aggregation and Encrypted Inference methods, all within the context of 6G and 1oMT. We consider multiple hospitals with clusters of mixed 1oMT and edge devices that encrypt locally trained models. Subsequently, each hospital sends the encrypted local models for SMPC-based encrypted aggregation in the cloud, which generates the encrypted global model. Ultimately, the encrypted global model is returned to each edge server for more localized training, further improving model accuracy. Moreover, hospitals can perform encrypted inference on their edge servers or the cloud while maintaining data and model privacy. Multiple experiments were conducted with varying CNN models and datasets to evaluate the proposed framework's performance. [ABSTRACT FROM AUTHOR]

By decoupling the data plane and the control plane of networking devices, Software Defined Network (SDN) enables the control plane devices to obtain the abstract view of the entire network and accomplish network functions as necessary. In SDN, control plane device, known as SDN controller is responsible for managing and setting rules for the data plane devices (SDN switches). Multiple SDN controllers are often used to formulate distributed controller architecture for geographically larger networks where different sets of switches are connected to and managed by different controllers. Due to network dynamics, any particular controller can become overloaded which results in increased response time and thereby reduce the end-user quality of service. To tackle the controller overload issue, in this paper, an effective and efficient load balancing framework is proposed. Most of the previous works in this domain focus on precise load balancing; therefore many load shifting (switch migration) operations are required and consequently degrade the end-user QoS. Additionally, beneath a certain load, CPU performs almost equally well; therefore load balancing before reaching a certain controller’s load seems unnecessary and questionable. Unlike most of the previous works, our algorithm balances the load loosely in a proper distributed controller SDN architecture. The load balancing framework uses five key modules to perform faster switch migrations to balance the load. Number of switch migrations, selection time performance, and load balancing precision are the performance metrics for evaluation and comparison for this work. The resultant load-balancing solution has successfully shown its potency in terms of reducing the number of switch migrations and the selection time compared to some recent and notable works in this domain. Moreover, a completely new functionality named Switch Restoration is introduced in our load balancing solution to optimize the network further. [ABSTRACT FROM AUTHOR]

Introduces a series of articles about optical networks, communications systems and devices.

Editorial. Deals with the management of traffic inside the network and switching to the use of multimedia. Various traffic management functions; How asynchronous transfer mode (ATM) can help in the transmission of multimedia; Factors that affect the multimedia transmission through ATM.

Editorial: Novel IT industry evolution improves people's life and brings economic benefits using innovative technologies of the Internet of Things (IoT), edge/fog computing, cloud computing, social networks, vehicular ad hoc networks, AI, and big data. Acknowledgements As the guest editors of this special issue, we would like to thank all authors who have submitted papers to the special issue and in particular those whose papers have been accepted for this special issue. The third paper, "A coverage vulnerability repair algorithm based on clustering in underwater wireless sensor networks" by Wenbo Zhang, et al., proposes a vulnerability repair algorithm based on clustering. [Extracted from the article]

Cyber threats have been growing tremendously in recent years. There are significant advancements in the threat space that have led towards an essential need for the strengthening of digital infrastructure security. Better security can be achieved by fine-tuning system parameters to the best and optimized security levels. For the protection of infrastructure and information systems, several guidelines have been provided by wellknown organizations in the form of cybersecurity standards. Since security vulnerabilities incur a very high degree of financial, reputational, informational, and organizational security compromise, it is imperative that a baseline for standard compliance be established. The selection of security standards and extracting requirements from those standards in an organizational context is a tedious task. This article presents a detailed literature review, a comprehensive analysis of various cybersecurity standards, and statistics of cyber-attacks related to operating systems (OS). In addition to that, an explicit comparison between the frameworks, tools, and software available for OS compliance testing is provided. An in-depth analysis of the most common software solutions ensuring compliance with certain cybersecurity standards is also presented. Finally, based on the cybersecurity standards under consideration, a comprehensive set of minimum requirements is proposed for OS hardening and a few open research challenges are discussed. [ABSTRACT FROM AUTHOR]

Mobile edge computing (MEC) has been considered as a promising paradigm to support the growing popularity of mobile devices (MDs) with similar capabilities as cloud computing. Most existing research focuses on MEC enabled by terrestrial base stations (BSs), which is unable to work in certain scenarios, e.g., disaster rescue and field operation. Some researchers have been making efforts on studying MEC assisted by unmanned-aerial-vehicles (UAVs) and developed lots of efficient scheduling algorithms. However, MEC assisted only by UAVs has limited capability and is unsuitable for heavy-computation applications. To address the issue, this paper proposes a novel UAV-and-BS hybrid enabled MEC system, where multiple UAVs and one BS are deployed to facilitate the provisioning of MEC services either directly from UAVs or indirectly from the BS. Considering maximizing the lifetime of all MDs, the energy-efficient scheduling problem is formulated as minimizing the energy consumption of all MDs by jointly optimizing UAV trajectories, task associations, computing-and-transmitting resource allocations. The optimization problem is further decomposed into three sub-problems and solved by the proposed hybrid heuristic and learning based scheduling algorithms to reduce the complexity. Experimental results show that the proposed algorithm can achieve promising performance improvements over baseline algorithms, including local-computing, random-offloading and greedy-offloading. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including advances in heterogenous computer networking, self-adaptive threshold in cloud computing, and orthogonal frequency division multiple access (OFDMA).

Mobile users need to maintain end-to-end connections when changing subnets. Handoff across networks often causes delay and loss of packets and make end users vulnerable to security threats that may lead to disruptions. In this paper, we design P-SIGMA , a delay and security-hardened, disruption-tolerant and signalling cost-effective end-to-end mobility management scheme by incorporating paging in SIGMA , an internet protocol diversity-based end-to-end transport layer mobility management scheme. P-SIGMA can detect and mitigate disruptions against two most common security threats: session hijacking and freeloading. We also propose a signalling cost analysis model for paging and a recovery-time model for attacks. To demonstrate performance improvement, we compare P-SIGMA with SIGMA and show the speed at which P-SIGMA can detect attacks (security breaches). We observe that P-SIGMA has lower signalling than SIGMA while maintaining all the benefits of a transport layer mobility management scheme. P-SIGMA can also detect paging related security threats with a small detection time without incurring any additional signalling. [ABSTRACT FROM AUTHOR]

The throughput degradation of Transport Control Protocol (TCP)/Internet Protocol (IP) networks over lossy links due to the coexistence of congestion losses and link corruption losses is very similar to the degradation of processor performance (i.e., cycle per instruction) due to control hazards in computer design. First, two types of loss events in networks with lossy links are analogous to two possibilities of a branching result in computers (taken vs. not taken). Secondly, both problems result in performance degradations in their applications, i.e., penalties (in clock cycles) in a processor, and throughput degradation (in bits per second) in a TCP/IP network. This has motivated us to apply speculative techniques (i.e., speculating on the outcome of branch predictions), used to overcome control dependencies in a processor, for throughput improvements when lossy links are involved in TCP/IP connections. The objective of this paper is to propose a cross-layer network architecture to improve the network throughput over lossy links. The system consists of protocol-level speculation based algorithms at transport layer, and protocol enhancements at middleware and network layers that provide control and performance parameters to transport layer functions. Simulation results show that, compared with prior research, our proposed system is effective in improving network throughput over lossy links, capable of handling incorrect speculations, fair for other competing flows, backward compatible with legacy networks, and relatively easy to implement. [ABSTRACT FROM AUTHOR]

Critical event information dissemination has been proliferating on VANET allowing road safety via connected vehicular communications. Despite the prospect of promising applications in vehicular networks, it faces unresolved challenges that hold the capability to slow down network performance upon deployment, especially in terms of security. Particularly, insider attacks such as Blackhole attacks that are carried out against VANET systems can disrupt the networks' average performance and prevent communication between vehicles entirely. Many state-of-the-art solutions have been proposed to detect and eliminate such nodes based on reputation systems and broadcast routing. However, if the network consists of multiple malicious nodes, the message dissemination could fail due to broadcast message tampering attack or packet dropping. In this study, we explore to answer the question of "can we improve the insider attacks mitigation in VANET by enhancing the trust in the network system so that the possibility of successful attacks can be reduced?". To answer this question, in this paper, we present the blockchain-based decentralized trust score framework for the participating nodes to detect and blacklist insider attackers in VANET proactively. We propose a two-level detection system, in which at the first level, neighboring nodes calculate the trust individually. In the second level, a consortium blockchain-based system with authorized Road Side Units (RSUs) as validators, aggregate trust scores for vehicular nodes. Then, based on trust scores reported by the neighboring nodes, the blacklist node tables are dynamically modified. The experimental analysis shows that the proposed system is efficient and scalable in terms of the network's practical size. Finally, we also present evidence that the proposed system improves the VANET performance by mitigating and blacklisting insider attack launching nodes. • Blockchain based decentralized trust system to eliminate malicious nodes in VANET routing protocol. • The proposed blockchain based trust system is able to mitigate the blackhole attacks in AODV routing protocol. • The proposed system is lightweight, scalable and efficient, which makes it viable to adapt in VANET applications. [ABSTRACT FROM AUTHOR]

In order to evaluate network trust, different intrusion detection methods have been proposed. However, it is difficult for a single detection node to collect massive data and perform detection and evaluation in a large-scale network. In addition, disclosure of security-related data and detection pattern might weaken data provision incentives due to privacy concern, which could result in deliberately forging data to evade detection. Current literature still lacks a general framework to conduct decentralized intrusion detection towards network trust evaluation with privacy preservation. In this paper, we propose SeDID, a Software Guard Extension (SGX)-enabled decentralized intrusion detection framework for network trust evaluation based on blockchain. We design a novel consensus mechanism to avoid forking and guarantee high efficiency and real decentralization, where block creation is uniquely consented by miners and block creation difficulty is determined by the number of blocks previously created by a relative miner within a time window. The smaller the number, the easier the miner creates a new block. SeDID also offers incentives according to node contributions for motivating security-related data collection, intrusion detection and network trust evaluation. Additional employment of Intel SGX makes SeDID preserve both data and pattern privacy. We analyze SeDID's efficacy in terms of incentive, privacy preservation and security. Its performance is further evaluated through simulations. In specific settings, its block creation time, task completion time and throughput are 19.61s, 44.55s and 224.47 transactions/s, respectively. Compared with state-of-the-art systems, SeDID offers better performance, which implies its potential to be applied in practice. • A decentralized intrusion detection framework for network trust evaluation. • A novel consensus mechanism to overcome main challenges of blockchain. • An incentive mechanism to motivate all involved participants based on contributions. • Intel SGX-enabled privacy preservation with efficiency guarantee. [ABSTRACT FROM AUTHOR]

Smart vehicles are expected to be equipped with high-dimensional, resource-intensive applications, including platoon control, augmented reality supported gaming, AI-based pedestrian detection, fuel scheduling, and so on, catering to diverse user preferences and enhancing safety and efficiency. These applications pose unique challenges for resource-constrained vehicles due to their intense computation requirements, whereas vehicular edge computing (VEC) networks, consisting of roadside units (RSUs) and MEC servers, contain the capability of providing cloud-like computing experience at vehicular edges while meeting performance requirements in terms of latency and throughput. Moreover, the development of intelligent VEC (IVEC) infrastructure is accelerated due to rapid advancement of AI algorithms in recent years. However, IVEC is prone to attacks, including fake computation feedback, unfair or biased resource allocation in a VEC server, and so on, due to its centralized governance and black box computation (edge computation works like a black box for end users). To combat such security vulnerabilities, we propose a blockchain-based decentralized architecture to enhance transparency in IVEC resource management and leverage edge consumers (e.g., vehicles) with a computation verification option. Additionally, we address the unbalanced load distribution issue and propose a secure IVEC federation model for balancing loads. We also outline the main challenges and provide a brief description of promising research directions to draw the attention of concerned stakeholders and parties in both the blockchain and edge computing domains. [ABSTRACT FROM AUTHOR]

We present a privacy-preserving framework for Artificial Intelligence (AI) enabled composition for the edge networks. Edge computing is a very promising technology for provisioning realtime AI services due to low response time and network bandwidth requirements. Due to the lack of computational capabilities, an edge device alone cannot provide the complex AI services. Complex AI tasks should be divided into multiple sub-tasks and distributed among multiple edge devices for efficient service provisioning in the edge network. AI-enabled or automatic service composition is one of the essential AI tasks in the service provisioning. In edge computing-based service provisioning, service composition related tasks need to be offloaded to several edge nodes for efficient service. Edge nodes can be used for monitoring services, storing Quality-of-Service (QoS) data, and composing services to find the best composite service. Existing service composition methods use plaintext QoS data. Hence, attackers may compromise edge devices to reveal QoS data of services and modify them for giving an advantage to particular edge service providers, and the AI-based service composition becomes biased. From that point of view, a privacy-preserving framework for AI-based service composition is required for the edge networks. In our proposed framework, we introduce an AI-based composition model for edge services in the edge networks. Additionally, we present a privacy-preserving AI service composition framework to perform composition on encrypted QoS data using fully homomorphic encryption (FHE) algorithm. We conduct several experiments to evaluate the performance of our proposed privacy-preserving service composition framework using a synthetic QoS dataset. [ABSTRACT FROM AUTHOR]

In-band full duplex wireless medium access control (MAC) protocol is essential in order to enable higher layers of the protocol stack to exploit the maximum benefits from physical layer full duplex technology. Unlike half duplex wireless local area network, a full duplex MAC protocol has to deal with several unique issues and challenges that arise because of the dynamic nature of the wireless environment. In this paper, we have discussed several existing full duplex MAC protocols and have shown qualitative comparisons among these full duplex MAC protocols. Full duplex in-band wireless communication has the potential to double the capacity of wireless network. Inter-client Interference (ICI) is a hindrance in achieving double spectral efficiency of the in-band full-duplex wireless medium. In this paper, we have classified existing solutions to the ICI problem and compared the solutions with respect to the proposed approaches, their advantages and disadvantages.We have also identified and discussed several issues and challenges of designing a full duplex MAC protocol. Results of qualitative comparisons of various wireless full duplex MAC protocols may be applied to design new protocols as well as researchers may find the identified issues and challenges helpful to solve various problems of a full duplex MAC protocol. [ABSTRACT FROM AUTHOR]