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Summary: In this paper, we study a UAV‐based fog or edge computing network in which UAVs and fog/edge nodes work together intelligently to provide numerous benefits in reduced latency, data offloading, storage, coverage, high throughput, fast computation, and rapid responses. In an existing UAV‐based computing network, the users send continuous requests to offload their data from the ground users to UAV–fog nodes and vice versa, which causes high congestion in the whole network. However, the UAV‐based networks for real‐time applications require low‐latency networks during the offloading of large volumes of data. Thus, the QoS is compromised in such networks when communicating in real‐time emergencies. To handle this problem, we aim to minimize the latency during offloading large amounts of data, take less computing time, and provide better throughput. First, this paper proposed the four‐tier architecture of the UAVs–fog collaborative network in which local UAVs and UAV–fog nodes do smart task offloading with low latency. In this network, the UAVs act as a fog server to compute data with the collaboration of local UAVs and offload their data efficiently to the ground devices. Next, we considered the Q‐learning Markov decision process (QLMDP) based on the optimal path to handle the massive data requests from ground devices and optimize the overall delay in the UAV‐based fog computing network. The simulation results show that this proposed collaborative network achieves high throughput, reduces average latency up to 0.2, and takes less computing time compared with UAV‐based networks and UAV‐based MEC networks; thus, it can achieve high QoS. [ABSTRACT FROM AUTHOR]

Summary: An evaluation of various transmit precoding schemes is proposed in this thesis on basis of spectral efficiency (SE) of massive MIMO (m‐MIMO) system in 2 GHz spectrum. The present generation of wireless networks must be rethought due to the rapidly rising user base, huge volume data transfer, wide coverage requirement, and exponential rise in data rate. 5G mobile network includes a multi‐fold increase in network capacity, energy conservation, decreased latency, higher coverage probability, and a seamless connection. m‐MIMO has provided good solution for enhancing the data rate with the coverage, overcoming the effects of multipath fading and has also increased diversity of the system. Massiveness of MIMO system along with 5G network is the key technology to address the issue of SE, throughput, improvement of QoS (quality of service), coverage probability, power delay profile, diversity simulation, energy efficiency, and improvement in bit error rate. Parameters such as SE, throughput, and coverage probability are important for any communication system, and their improvement can increase overall capacity of cellular network system and could meet the requirement of upcoming demand for mobile network. The research paper is focused on performance analysis of m‐MIMO with reference to the SE of various transmit precoding schemes. Simulation results show that SE provided by M‐MMSE (multi‐cell minimum mean‐squared error) technique of precoding ranks highest for the same number of antennas and pilot reuse factor as compared to other schemes. [ABSTRACT FROM AUTHOR]

Summary: It has been confirmed that the aerial intelligent reflecting surface (AIRS) can dramatically improve the coverage and quality of service of wireless communication systems. This paper proposes to exploit an AIRS to enhance the physical layer security (PLS) of wireless communication systems. In particular, the AIRS flies at convenient positions for enhancing legitimate channel gain and reducing eavesdropping channel gain. Moreover, the worst‐case security is determined where the legitimate user is affected by hardware impairments (HIs) while the eavesdropper hardware is ideal (ID). The analytical expression of secrecy outage probability (SOP) of the considered systems (referred to as the AIRS‐HI systems) is derived over realistic Nakagami‐ m channels recommended for application in the fifth and beyond generations (5G & B5G). To clarify the behaviors of the considered systems, the asymptotic expressions of signal‐to‐distortion‐plus‐noise ratio (SDNR) at the legitimate user, signal‐to‐noise ratio (SNR) at the eavesdropper, and SOP are also provided. Monte‐Carlo simulations are employed to confirm the accuracy of the derived theorem. Numerical results confirm that the SOP of the AIRS‐HI systems is dramatically higher than the SOP of the AIRS‐ID systems. In other words, a strong effect of HIs on the SOP of the AIRS‐HI systems is clearly indicated. Consequently, utilizing the high transmit power is not an effective solution to improve the secrecy performance of the AIRS‐HI systems. In contrast, it is essential to employ an appropriate transmit power tailored to the specific system parameters. Furthermore, the considerable advantages of incorporating AIRS are demonstrated through a comparison between the SOPs of AIRS‐HI systems and HI systems lacking AIRS. Additionally, a comprehensive examination of AIRS‐HI system behaviors is conducted by varying various system parameters, including the predefined secrecy rate, HI level, the number of reflecting elements (REs) in AIRS, WiFi network frequency, AIRS altitude, bandwidth, and channel fading order. These observations lead to the identification of numerous recommended solutions for enhancing the SOP performance of the considered AIRS‐HI systems. [ABSTRACT FROM AUTHOR]

Summary: Flying ad hoc networks (FANETs) are a class of highly dynamic mobile ad hoc networks in which flying UAVs coordinate among themselves for delivering the data to the applications. Data routing in FANETs has been a challenge due to the inherent mobile and unpredictable movement of UAV nodes. This paper proposes a quality of service‐aware routing protocol (QARP) for FANETs which incorporates hybrid nature‐inspired heuristics to identify optimized routes to the destination UAVs. The routing mechanism operates in two phases. In the first phase, the neighbour discovery initializes the adapted firefly algorithm to identify nodes with least packet delivery delay to the destination. In the second phase, the Gaussian quantum‐behaved particle swarm optimization meta‐heuristic algorithm is utilized to identify the most optimal nodes to create a route for data delivery to destination. The proposed protocol has been tested to perform better in terms of delay, routing overhead, throughput and packet delivery ratio in comparison to MA‐DP‐AODV, MDA‐AODV and MDRMA routing protocols. [ABSTRACT FROM AUTHOR]

Summary: In the present scenario, wireless body area network (WBAN) use case has gone beyond medical monitoring (e.g., E‐Healthcare) and has become a vital part of our daily lives. WBANs, applied in E‐Healthcare systems, extract the physiological parameters through the implanted (in‐body) and/or wearable (on‐body) sensors applied to the human body and route them to the remote server in a systematized and well‐grounded manner. Thus, routing is the most primitive and non‐trivial task in WBANs for prompt and proper delivery of sensed data. The design of routing protocol is crucial for efficacious communication and high network performance. Therefore, the target of this paper is to present an all‐encompassing taxonomy of the state‐of‐the‐art routing protocols in WBANs. Firstly, this paper provides an insight into WBANs and their related projects. Next, WBAN routing challenges are explored, and after clustering these challenges based on their operating mechanism, the routing protocols are categorized into eight categories, which correspond to cluster‐ and tree‐based, cross‐layer‐based, fuzzy‐based, interference‐based, posture‐based, QoS‐based, SDN‐based, and temperature‐based routing protocols. Furthermore, comparison tables highlighting the goals, strengths, limitations, and novelty of each protocol, along with a qualitative comparison table of the routing protocols for each category based on their features are furnished. This exhaustive survey can serve as a starting point for WBAN researchers, as open research issues have been highlighted in the discussion section. [ABSTRACT FROM AUTHOR]

Summary: The non‐orthogonal multiple access (NOMA) wireless networks are a robust multi‐access mechanism that serves multiple clients accessing the same resource block simultaneously. The fifth‐generation wireless networks offer huge efficiency in spectrum utilization, which can be exploited to deploy NOMA for LOS communication of unmanned aerial vehicles (UAVs). Previous research has extensively analyzed various aspects of NOMA‐UAV communication systems, including user access fairness, coverage, maximizing system capacity, and total energy efficiency. However, only a few researchers have focused on maximizing the EE of NOMA‐UAV wireless networks with user quality of service (QoS) constraints. This paper proposes a fuzzy logic‐based crossover‐based coati optimization algorithm for maximizing the energy efficiency of NOMA‐UAV, along with user scheduling. The main objective of this model is to offer a solution to the joint energy efficiency and user QoS scheduling problem. The fuzzy decision‐making strategy optimizes the energy efficiency (EE) of NOMA‐UAV by selecting appropriate power and time resources. Additionally, the crossover‐based coati optimization algorithm transforms the subchannel allocation problem into a two‐sided matching procedure. The efficiency of the proposed algorithm is evaluated concerning overall residual energy, number of remaining nodes, and time consumption. The experimental outcomes demonstrate the capability of the proposed model in optimizing the energy efficiency of the NOMA‐UAV network by identifying the optimal resource set in terms of time and power while satisfying the clients' QoS. [ABSTRACT FROM AUTHOR]

Summary: Small cell networks can fulfill the increasing demandfor the high data rate of wireless applications. Energy efficiency is an important design parameter of the ultra dense small cell network (UDSCN). The sleeping strategy of small base stations (s‐BSs) is used to enhance the network's energy efficiency. An efficient sleeping strategy of s‐BSs is required while preserving users' quality of service (QoS). The idle s‐BSs can be switched to sleep mode. This paper proposes a blockchain‐enabled solution for the sleeping strategy of s‐BSs. Here, a blockchain‐enabled small cell network is created between the s‐BSs. The network is decentralized, which eliminates the workload of the macro base station (MBS). The proposed network architecture is enabled as a decentralized network through blockchain. The blockchain provides distributed control over the s‐BS operations through a smart contract. Here, smart contracts act as distributed self organizing network features to handle self‐transactions among small cells for switching off s‐BSs in the network. All the software logic required to perform s‐BS operations is written in a smart contract using Ethereum. The proposed solution improves energy efficiency and enables the ultra dense small cell network to be decentralized. [ABSTRACT FROM AUTHOR]

Summary: The number of internet users and connected devices has dramatically expanded due to the recent technological boom and the benefits that the internet of things offers to ease our lives. Network scheduling, quality of service, resource allocation, and security issues are now being addressed via software‐defined networking (SDN). SDN has several benefits over traditional networks, including global centralized control, managing network traffic, and separating the forwarding and control plane. The work done in this paper aims to design and implement a traffic‐aware routing framework based on routing optimization presented as an integer linear programming (ILP) to improve heterogeneous traffic flows' quality of service (QoS) in a simulated SDN environment. With the knowledge that the routing problem is a nondeterministic polynomial‐time‐hard problem, the proposed scheme aims to decrease the computational routing time to make the ILP‐based routing system more suitable for real‐time processing. The simulation results illustrate that the proposed framework reduces the computational time by 23% and 49% for Abilene and Goodnet topology, respectively. Additionally, with 1000 flows in the network, the suggested scheme reduces the number of network flows that violate the QoS by 9% and 22% (with Abilene topology) and 16% and 51% (with Goodnet topology) as compared to the existing shortest path delay and sway methods, respectively. [ABSTRACT FROM AUTHOR]

Summary: The vast number of smart cloud applications that communicate with the "things" over a variety of physical networks and communication protocols contribute to the rise of complexity in Internet of Things (IoT) systems. The diversity of end‐user requirements related to the volume of generated data, its variety, and the velocity of its transmission makes quality of service (QoS) provisioning even more crucial and challenging in IoT. This paper provides a comprehensive and up‐to‐date survey of QoS support in IoT networks and communication protocols. An analysis of the QoS‐aware IoT architectures, layer‐dependent QoS metrics, and network resource optimization methods utilized in IoT systems are given. The limitations of the current state‐of‐the‐art studies for efficient delivery of QoS metrics are discussed. The paper concludes with future research directions on end‐to‐end QoS provisioning in IoT. [ABSTRACT FROM AUTHOR]

Summary: Massive, diverse, and high‐frequency Internet of Things (IoT) applications pose challenges to the operation of cluster systems that serve it. Fair and efficient multidimensional resource allocation is of great significance to the sustainable operation of these systems. However, most of the existing cluster multiresource allocation optimization researches focus too much on the fairness of resource allocation and ignore the efficiency. The unbalanced use of multidimensional system resources reduces the effective utilization of system resources, which seriously affects the service quality of IoT applications. In this paper, we define the multiresource fair and efficient sharing optimization as a fairness‐constrained efficiency optimization problem, which is from dynamics, discrete resources, and heterogeneous perspectives according to the characteristics of cluster system in practical. Moreover, we present a dynamic efficiency‐aware multiresource fair allocation algorithm, DEF, which can improve the ability of the cluster system to serve diverse IoT applications. In the algorithm, large jobs schedule to the servers that expect the least remaining resources. Simulations performed using Google cluster‐usage traces show that DEF can improve system resource utilization and guarantee the fairness of sharing among users. [ABSTRACT FROM AUTHOR]

Summary: Cooperative communication is a significant technology for fifth generation (5G) and beyond wireless communication to improve the quality of service (QoS) in massive networks. In addition, it serves as a promising candidate along with non‐orthogonal multiple access (NOMA) scheme to increase the spectral efficiency. Conventionally, cooperative‐NOMA (C‐NOMA) systems are analysed by assuming perfect successive interference cancellation (SIC) and imperfect SIC (I‐SIC) over Rayleigh, Rican, α−μ, Hoyt fading channels, and so on. In this paper, near–far relay (NFR) C‐NOMA system is analysed aiding perfect SIC, perfect channel state information (CSI), imperfect (I‐CSI) and (I‐SIC) over Rayleigh fading channel. Initially, we derive analytical expressions of outage probability (OP) by considering I‐SIC and I‐CSI for NFR‐C‐NOMA system. The accuracy of analytical results is verified through Monte Carlo (MC) simulations. Interpretation of the results conveys that I‐CSI and I‐SIC have a substantial impact on OP in NFR‐C‐NOMA scheme and existing schemes. Later, we examined impact on OP in NFR‐C‐NOMA by varying relay position, target rate of users and jointly considering the I‐SIC, I‐CSI. Further, it is also observed that the NFR‐C‐NOMA scheme shows better outage performance than state‐of‐the‐art schemes. [ABSTRACT FROM AUTHOR]

Summary: Vertical handoff is a major concern in the operation of mobile connections. Multiple wireless networks collate to provide smooth and quality service to the users over mobile connections. This paper formulates a Markov decision process for handoff decisions with a sample space that includes a union of parameters that are important for making a handoff decision. The major contribution of this paper is to propose three different yet closely related algorithms for reducing the computational complexity of the original problem. In particular, we propose a feature‐wise assessment algorithm, a network‐wise assessment algorithm, and a hybrid approach for computational complexity reduction. Discussed algorithms give pseudo‐optimal solutions with a significant reduction in computational complexity. Results indicate that different complexity reduction algorithms perform best under different circumstances. This provides a guideline for the selection of complexity reduction algorithms based on real scenarios. [ABSTRACT FROM AUTHOR]

Summary: Vehicular ad hoc network (VANET) has been established to mitigate road collisions and traffic congestion and provide infotainment facilities to users. Allocated channels to VANET, which is the DSRC (Dedicated Short‐Range Communication), are not adequate for the full implementation of VANET. Cognitive radio (CR) can be used to alleviate this issue. CR is a programmable and intelligent radio system capable of reaching various frequency ranges. CR needs to conduct spectrum sensing to get these bands. A vehicle fitted with a CR can sense the licensed spectrum to locate the vacant spectrum (which is not used by any licensed user) when the DSRC is wholly occupied. Compared to other CR networks, VANET faces specific additional difficulties related to spectrum sensing, such as periodic topological shifts due to high‐speed mobility, multipath fading and shadowing issues, and heterogeneous quality of service (QoS) specifications. This paper explains these problems in depth. All the problems and issues were explored from the perspective of the CR focused on VANET. Probable ideas and directions to overcome these problems have also been presented. We have provided a conceptual framework for spectrum sensing. The framework resolves a variety of issues and concerns that are discussed in the paper. It gives much better results than conventional sensing techniques. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we analyze the performance of maximum‐ratio combining (MRC) receivers for single‐input multiple‐output (SIMO) non‐orthogonal multiple access (NOMA) system. We explore the aforesaid system performance in presence of impairments like imperfect channel state information (CSI) and successive interference cancellation (SIC) errors. In general, receive diversity provides diversity gain and helps to maintain quality of service (QoS), while the NOMA system achieves higher spectral efficiency compared to orthogonal multiple access (OMA). Power‐domain NOMA system transmits superimposed‐coded signal, which utilize SIC detection method at the receiving users. Here, we derive the closed‐form expression of the average bit error rate (BER) for the MRC‐based NOMA system. We also analyze the performance of the system in high signal‐to‐noise ratio (SNR) regime through derived asymptotic expression. Furthermore, the outage probability, diversity order, and sum rate comparison between NOMA and OMA system are also presented. Simulation results also validate the derived theoretical expressions and confirm the diversity gain achieved for the considered system. [ABSTRACT FROM AUTHOR]

Summary: Heterogeneous wireless sensor networks (HWSNs) have a wide range of application in the contemporary world particularly in sensing and hunting of events without human interference. Due to this limitation of network resources and energy of sensor nodes, the contention of available resources for transmission will increase the energy consumption in the network and degrade the performance of Quality of Service. During dense traffic conditions, sensor nodes in close proximity to base station (BS) faces severe bottleneck resulting in congestion and energy hole problem. The efficient utilization of energy and packet loss is due to link break and by traffic analysis attack is a primary threat in HWSN applications. To sustain maximum energy in the network, two important aspects are considered, namely, flawless selection of path and concise clustering. This paper describes about a multi‐objective‐based Hybrid Diffusion Clustering Scheme (HDCS) through Jellyfish routing protocol with Time Division Multiple Access (JRP‐TDMA)‐based routing method in HWSN. Cluster head is elected based on multiple objectives such as residual energy, cost, and distance. Once CH selection is done, JRP‐TDMA based on available timeslot handpicks the best path for transmitting to BS. The proposed protocol is analyzed, simulated, and performance results are correlated with existing protocols namely, diffusion clustered routing protocol (DCRP), efficient unequal clustering (EEUC), Markov chain model‐based optimal cluster head (MOCH), and genetic algorithm (GA). The number of alive sensor nodes of proposed method has increased by 24.4% when compared with other approaches. [ABSTRACT FROM AUTHOR]

Summary: Extreme densities are an important factor in future mobile networks that can provide very high data rate to mobile users. It also increases complexity in handover decisions and resource management. However, SDNs (software‐defined networks) and mobility models can provide seamless mobility and efficient resource management in heterogeneous mobile environment, and ensure QoS (quality of service) is achieved. The paper proposes SDN based on GMM (Group Mobility Model) called MoMo, and resource management using MLOAs (mutation lion optimization algorithms) are used to alleviate handover and addressing issues in network congestion. The proposed method is based on SDN controllers working in global perspectives for achieving required network conditions and end user QoSs. SDN with GMM‐MoMo‐MLOA offer transparent and dynamic support for sessions during handoffs and thus eliminates congestion overheads and packet losses related to mobile traffic, resulting in improved QoS for mobile users. The performance analysis through experiments depicts that the proposed model gives enhanced performance when compared to that of the other conventional methods and also has proven efficiency in terms of other parameters such as handover latency, signaling cost, throughput, and packet loss. The results from the simulation show that the proposed method SDN‐GMM‐MoMo‐MLOA greatly improves the performance of network and also maintains optimum resource utilization and efficiency. [ABSTRACT FROM AUTHOR]

Summary: Device‐to‐device (D2D) is a fifth‐generation (5G) network's key technology which allows devices in proximity to communicate one‐to‐one without a base station (BS). Moreover, it ameliorates channel gain, communication latency, energy efficiency, and spectral efficiency. However, mitigating interference (D2D and cellular mobile users [CMUs]) and eavesdropper effect (at D2D links) is a prime concern in D2D communication. These issues can be resolved with an efficient allocation of radio resources. Cognitive radio (CR) and non‐orthogonal multiple access (NOMA) are viable solutions to resolve the aforementioned issues. Motivated by the aforementioned discussion, in this paper, we propose a joint CR and NOMA‐based scheme, that is, SARAS for secure resource allocation in D2D communication. It aims to maximize the overall sum rate and secrecy capacity of D2D users with assured quality of service (QoS) and quality of experience (QoE). CR is used for pairing between strong and weak D2D users (i.e., D2D pair) and NOMA's successive interference cancelation (SIC) technique helps to reduce the interference effect between cellular and D2D users. We used a coalition game for efficient resource utilization, which transfers D2D users from one coalition to another based on the preference order and channel conditions. This landed D2D users in the best coalition having favorable channel conditions. We have executed the proposed SARAS scheme over the MATLAB simulation tool, considering a varying number of D2D and CMUs. Simulation results show that the proposed scheme outperforms the traditional OFDMA, random, and nearest approaches concerning parameters such as sum rate and secrecy capacity. [ABSTRACT FROM AUTHOR]

Summary: In recent times, the expeditious growth of Internet of Things (IoT) offers applications to ease day‐to‐day activities with minimum human effort. Once the IoT application installed, the connected devices perform their tasks without human intervention. Hence, the need of performance optimization and security enhancement is vital to minimize end‐to‐end communication delay, improve kernel‐level security, mitigate faults adaptively, and have suitable backup options in case of node failure. This paper proposes a quality of service (QoS)‐aware fault‐proof secure Q‐learning‐based IoT (QIoT) kernel‐level protocol that integrates multipath aggregation and fuzzy authentication for security, with multichannel communication for improved QoS. Especially, this protocol integrates a source‐level clustering mechanism based on Q‐learning that aims at reducing route search delay. In order to provide fault tolerance, the kernel is equipped with real‐time fault‐tolerance mechanism that is activated in case of node‐level faults. Due to integration of Q‐learning, computational overheads are reduced by over 15% when compared with Zephyr, AliOS, and RTX kernels. This reduction in computational overheads facilitates light‐weight behavior of the kernel, due to which other QoS parameters like energy consumption, throughput, and routing overhead are reduced. The proposed QIoT kernel‐level protocol is compared with standard kernel modules, and performance evaluation showcases an improvement in authentication security by 8%, end‐to‐end delay by 5%, energy efficiency by 25%, and fault mitigation by 18%, thereby assisting the use of the proposed kernel for real‐time deployments. [ABSTRACT FROM AUTHOR]

Summary: In order to improve the efficiency of service migration in mobile edge computing (MEC), and obtain higher quality of service and better user experience, we take mobile agent technology, instead of container, as the application component hosting technology. The advantages of mobile agent include small size, high flexibility, autonomy, and suitability for heterogeneous environments. For 5G communications, how to offer cross‐platform support and deal with frequent roaming of mobile nodes is our main concern. Therefore, this paper provides a service migration framework using mobile agent in MEC environment and performance evaluation. Experiments with tasks of different complexity show that in terms of efficiency of service migration, mobile agent technology obviously outperforms container technology. The main contributions of this paper include the following: (1) we solve the problem that too many auxiliary modules were used in the container architecture, (2) we use the agent container and the resource manager (RM) for performance evaluations to investigate the differences between mobile agent and container technology, and (3) we use the decision tree to confirm the execution cost of each node so as to analyze why the mobile agent responds to migration commands slowly. [ABSTRACT FROM AUTHOR]

Summary: Cooperation between mobile nodes is the predominant factor required for achieving reliable data dissemination in mobile ad hoc networks (MANETs), since non‐cooperative nodes crumbles the routing process and degrades network performance. The degree of non‐cooperation rendered by mobile nodes need to be accurately identified by exploring feasible and comprehensive number of criteria to achieve maximized cooperation in uncertain MANET. In this paper, fuzzy preference ranking organization method for enrichment evaluation (FPROMETHEE)‐based node cooperation technique is proposed with the merits of trapezoidal fuzzy interval numbers that aids in the selection of high trustworthy mobile nodes for attaining maximized data delivery. This FPROMETHEE technique utilizes complex and multiple criteria for potential ranking in the presence of finite number of mobile nodes. It prevented the bias of information that is more common during the judgmental process associated with the cooperation estimation of mobile nodes. It includes information about the relative weights of criteria and decision maker's preferences for estimating the trust of mobile nodes to include or isolate them from the routing path. It is also useful in handling the degree of uncertainly involved in the process of routing without compromising Quality of Service (QoS) level in the network. The simulation experiments of the proposed FPROMETHEE technique conducted using ns‐2 simulator confirmed its predominance in enhancing the packet dissemination rate, throughput, energy consumptions, total overhead, and packet loss rate for different number of mobile nodes, malicious nodes, and pairs of source and destination nodes. [ABSTRACT FROM AUTHOR]

Summary: The Vehicular Ad‐hoc Network (VANET) is one of the emerging research areas in recent days, in which accomplishing the robustness and security are the demanding tasks. To obtain these objectives, various offloading‐based techniques are developed in the traditional works. Still, it remains with the limitations of high mobility, no assurance for data acceptance, and limited applicability for multiple data exchange units. Thus, this paper aims to develop a Data Centric Dispatcher Selection (DCDS) algorithm based on data offloading for a secure information exchange in VANET. It aims to enable the cellular‐based VANET connection by using the application layer protocol without taking the Pending Interest (PI)‐based information. Also, the Content Centric Network (CCN) concept is utilized to exchange the data between for upcoming internet. In this environment, the position of own vehicle and neighboring vehicle are known to each vehicle by using the Global Positioning System (GPS) and security messages. Moreover, the communication does not depend on the device's name, but it depends on the content name in CCN. Because of the availability of multiple interfaces in CCN, there is no content loss in the network. During simulation, various performance measures are used to evaluate the performance of the proposed technique, which includes throughput, packet loss rate, average end‐to‐end delay, total Satisfied Interest Packet (SIP), Forwarded Interest Packet (FIP), and average Interest Satisfactory Delay (ISD). Also, the superiority of this paper is proved by comparing it with some existing techniques such as Internet Protocol Television Quality of Service (IPTV‐QoS), Michael Oche (MO), and RobUst Forwarder Selection (RUFs). [ABSTRACT FROM AUTHOR]

Summary: Nowadays, due to the increased amount of network users and resources, some emerging technologies like big data and cloud have been developed. But managing these types of networks is more complex; in order to solve this issue, a software‐defined network (SDN) is developed for managing the network in a comfortable manner, in which maintaining load balance and energy efficiency of network is highly important to satisfy the requirements of quality of service (QoS). For these reasons, various optimization‐based algorithms are developed in the traditional works, but these lack with the limitations of increased network traffic and energy consumption. In order to solve these issues, an enhanced hybrid flower pollination algorithm (HFPA) with improved harmony search (IHS) is developed in this paper. It intends to obtain an improved resource utilization and reduced network load and delay by efficiently allocating the bandwidth to the network. Moreover, an optimal routing protocol (ORP) is employed to perform the data transmission with condensed network traffic. During experimentation, the performance results of the proposed algorithm are examined and compared with some traditional methodologies. From the results, it is noted that the proposed HFPA‐IHS‐ORP provides the better results than the existing methods. [ABSTRACT FROM AUTHOR]

Summary: The manifold increase in the number of cellular wireless network consumers has presented a monumental challenge to upgrade the current infrastructure for imparting superior throughput and good quality of service. End‐users of the network will want super high‐speed data with very low latency, as well as secure and with a lower packet data drop rate. Joint coordination between various network resources such as that of a dense heterogeneous network is crucial for achieving the above demands. It is also inevitable that such a dense arrangement of small cells or macro cells or other network equipment will be challenged by different forms of interference apart from being costly and less mobile. Beamforming is among the most advanced technology that is available up to date which has shown good results at handling interference and at guiding transmitted data to the desired end‐user. It is quite useful but also struggles from certain factors when deployed in a dense network. A thorough review of recent works of literature is detailed in the current paper with a focus placed on two major fields, which are interference mitigation techniques and gainful interference exploitation techniques. Some highly advanced interference mitigation techniques which are either developed or under development with their merits have been proposed. Most of these techniques use machine learning and artificial intelligence‐based methods to ensure the best quality of service (QoS) to every individual connected to the network. However some research works focused on negating away any kind of interference present in a signal, some focused on harnessing interference for optimizing the power of transmitted signals. [ABSTRACT FROM AUTHOR]

Summary: In view of the handover problem of visible light communication (VLC) and WiFi, most of existing works focus on optimization of vertical handover algorithm of heterogeneous network. However, cooperative handover strategy of horizontal handover (HHO) and vertical handover (VHO) was rarely studied. In the situation, this paper proposes a cooperative horizontal VHO (CHVHO) strategy for heterogeneous network based on quality of experience (QoE). This strategy mainly coordinates the HHO and VHO of the network from the aspects of building servers and the simplification of indoor movement model, which improves the QoE allocated to users. Simulation results demonstrate that, compared with traditional immediate VHO (IVHO) and dwell VHO (DVHO), this strategy can be adaptive to user movement and get higher average QoE. [ABSTRACT FROM AUTHOR]

Summary: In recent years, fog computing, a novel paradigm, has emerged for location and latency‐sensitive applications. It is a powerful complement for cloud computing that enables provisioning services and resources outside the cloud near the end devices. In a fog system, the existence of several nonhomogenous devices, which are potentially mobile, led to quality of service (QoS) worries. QoS‐aware approaches are presented in various parts of the fog system, and several different QoS factors are taken into account. In spite of the importance of QoS in fog computing, no comprehensive study on QoS‐aware approaches exists in fog computing. Hence, this paper reviews the current research used to guarantee QoS in fog computing. This paper investigates the QoS‐ensuring techniques that fall into three categories: service/resource management, communication management, and application management (published between 2013 and October 2018). Regarding the selected approaches, this paper represents merits, demerits, tools, evaluation types, and QoS factors. Finally, on the basis of the reviewed studies, we suggest some open issues and challenges which are worth further studying and researching in QoS‐aware approaches in fog computing. [ABSTRACT FROM AUTHOR]

Summary: The development of the wireless sensor networks (WSN) being deployed among numerous application for its sensing capabilities is increasing at a very fast tread. Its distributed nature and ability to extend communication even to the inaccessible areas beyond communication range that lacks human intervention has made it even more attractive in a wide space of applications. Confined with numerous sensing nodes distributed over a wide area, the WSN incurs certain limitations as it is battery powered. Many developed routing enhancements with power and energy efficiency lacked in achieving the significant improvement in the performance. So, the paper proposes a machine learning system (capsule network) and technique (data pruning) for WSN involved in the real world observations to have knowledge‐based learning from the experience for an intelligent way of handling the dynamic and real environment without the intervention of the humans. The WSN cluster‐based routing aided with capsule network and data pruning proffered in paper enables the WSN to have a prolonged network lifetime, energy efficiency, minimized delay, and enhanced throughput by reducing the energy usage and extending communication within the limited battery availability. The proposed system is validated in the network simulator and compared with the WSN without ML to check for the performance enhancements of the WSN with ML inclusions in terms of quality of service enhancements, network lifetime, packet delivery ratio, and energy to evince the efficacy of the WSN with capsule network‐based data pruning. [ABSTRACT FROM AUTHOR]

Summary: One of the nondeterministic polynomial (NP) hard problem in the area of wireless networks is the quality of service (QoS) routing problem. This has always been a key area wherein research is required to enhance the QoS metrics considered with respect to the considered network model. In this paper, mobile ad hoc network (MANET) model is identified for which an effective QoS routing protocol which meets the set QoS constraints is designed employing the novel variant of differential evolution (DE) model. The ultimate aim of the proposed work is to identify an optimal feasible path for the MANET model with the set objective function criterion being met. A variant of DE capsule net model is built by hybridizing it with the nature‐inspired firefly (FF) algorithmic approach. The effectiveness of the proposed technique is achieved by minimizing the set objective function on satisfying the QoS constraints in the MANETs. The developed technique chose better QoS path with respect to the best fitness value than that of the route replay the shortest path algorithm of ad hoc on‐demand distance vector (AODV) protocol. The modeled variant DE‐FF model achieves better QoS metrics with all the set constrained being met. Simulated results depict the superiority and better performance of the developed DE‐FF model than that of the other methods considered for comparison from the existing literature works. [ABSTRACT FROM AUTHOR]

Summary: In recent years, applying Internet of Things (IoT) applications has significantly increased to facilitate and improve quality of human life activities in various fields such as healthcare, education, industry, economics, etc. The energy aware cloud‐edge computing paradigm has developed as a hybrid computing solution to provide IoT applications using available cloud service providers and fog nodes for the smart devices and mobile applications. Since the IoT applications are developed in the form of several IoT services with various quality of service (QoS) metrics which can deploy on the cloud‐edge providers with different resource capabilities, finding an efficient placement solution as one of challenging topics to be measured for IoT applications. The service placement issue arranges IoT applications on the cloud‐edge providers with various capabilities of atomic services though sufficient different QoS factors to support service level agreement (SLA) contracts. This paper presents a technical analysis on the cloud‐edge service placement approaches in IoT systems. The key point of this technical analysis is to identify substantial studies in the service placement approaches which need additional consideration to progress more efficient and effective placement strategies in IoT environments. In addition, a side‐by‐side taxonomy is proposed to categorize the relevant studies on cloud‐edge service placement approaches and algorithms. A statistical and technical analysis of reviewed existing approaches is provided, and evaluation factors and attributes are discussed. Finally, open issues and forthcoming challenges of service placement approaches are presented. [ABSTRACT FROM AUTHOR]

Summary: Wireless Sensor Network (WSNs) is a collection of sensor nodes with a base station for data transmission. Mostly the network has various paths with the unbalanced nodes; therefore, energy consumption is always high. This causes the letdown of quality of service (QoS) routing metrics such as delay, inefficient throughput in WSNs. This paper concentrates on this problem and proposes an energy‐efficient multipath routing (EEMR) protocol for WSNs. EEMR protocol computes the optimal path using the multi‐objective lion optimization algorithm with less energy consumption. The main aim of EEMR protocol is to achieve an efficient path among multiple paths to satisfy quality requirements such as delay, throughput, energy consumption, delivery ratio, loss ratio, and latency. Thus, the proposed EEMR protocol is designed with a multi‐objective function using an optimization algorithm and implemented in MATLAB. The simulation results show that the performance of the proposed protocol is very efficient in comparison to state of the art. [ABSTRACT FROM AUTHOR]

Summary: Wireless multimedia sensor networks (WMSNs), with its exceptional properties, have found a sturdy and steady spot in automation and surveillance applications. The WMSN had made a massive drift of concentration from the wireless sensor networks with its capability of retrieving multimedia files through multimedia devices. The huge capacity data transfer through the multimedia sensors drain the power capacity of the sensors and is considered to be the vital challenge of the WMSNs. The challenges associated with the WMSNs are the restrictions in resources, connectivity, and security and maintaining a good level of quality of service (QoS). This paper proposes a novel protocol, optimized compressed sensing routing protocol (OCSRP), that performs the routing of multimedia data in a highly efficient manner through which the aforementioned research challenges like resource restrictions and QoS can be addressed. In addition, the security methods were incorporated in routing mechanism, and the results were compared with the existing LEACH algorithm. The quantitative analysis proves that the proposed model possesses high level of QoS with high level of security than the existing security algorithms. [ABSTRACT FROM AUTHOR]

Summary: Nowadays, the popular 2.4‐GHz band is used in different systems, such as Wi‐Fi, Bluetooth, wireless sensor systems, and wireless cameras. Instead of the over‐crowded 2.4‐GHz Wi‐Fi band, this research offers the experience of using the 5‐GHz Wi‐Fi band, which provides more spectrum availability, more channels, larger bandwidth, faster data transmission, higher data rates, higher speed, and better quality of service compared to those of the 2.4‐GHz band. In this paper, practical implementation and testing of a cooperative spectrum sensing system are presented. The spectrum utilization in the 5‐GHz Wi‐Fi licensed band at six different locations is investigated to allow the transition of secondary users (SUs) to free bands. The spectrum measurement is performed on a centralized cooperative spectrum sensing system, which consists of a master cognitive radio node and five cognitive radio stations. The measurement and simulation results for the practical system are compared with the previous related measurements obtained in Singapore, Barcelona, North Dakota (USA), and Germany. They all agree that the spectrum is underutilized, and it needs to be better utilized for increasing the spectrum efficiency. The practical results show that the newly implemented system in the 5‐GHz range fulfills the requirements of users with high efficiency and high quality of service compared to those of the 2.4‐GHz system. [ABSTRACT FROM AUTHOR]

Summary: Existing mobile network architectures are flatter and employ a centralized mobility management (CMM) scheme, where the entire intelligence is focused on the single‐end, which leads to low scalability, lack of dynamic mobility support, suboptimal routing, and insufficiency to support large volumes of data. The fifth‐generation (5G) networks demand high‐speed seamless connections to the best‐connected network irrespective of user position and connectivity. Further, seamless handover has to be carried out between wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX), universal mobile telecommunication system (UMTS), and long‐term evolution (LTE). This paper aims to propose a distributed mobility management (DMM) solution in order to bring the mobility anchor point nearer to the mobile node (MN) to support the acceptable quality of service (QoS) and quality of experience (QoE) provision to end users. An information and decision server (IDS)‐based partial DMM scheme (IDS‐PDMM) is suggested to support optimized handover in internet protocol (IP)‐based heterogeneous architecture. The IDS estimates the nearest candidate network for MN during handover and thus provides a seamless connection for delay‐sensitive applications. The performance of the presented approach is compared with the existing CMM scheme and the simulation results prove that the IDS‐PDMM efficiently minimizes the handover delay and packet loss rate with guaranteed QoS provision. [ABSTRACT FROM AUTHOR]

Summary: Non‐orthogonal multiple access (NOMA) has been investigated as a promising multiple radio access technology for future wireless networks to enable massive connectivity and improve spectral efficiency (SE). Furthermore, energy efficiency (EE) is becoming a primary concern and an inevitable trend for future wireless networks. For this, recent works have been provided good thoughts into joining these two conflicting performance metrics EE and SE. The joint EE–SE trade‐off problem for multi‐user NOMA systems in downlink is studied in this paper. The mathematical formulation of the EE–SE trade‐off is given as an optimization issue subject to some constraints. The basic thought is to improve EE by imposing simultaneously a minimum SE to be satisfied. The quality of service (QoS) requirement for each user is also provided to ensure optimality. For this, a dynamic energy‐efficient power allocation is proposed. Then, an iterative optimization algorithm with low computational complexity is developed to reach the proposed power allocation. Simulations have been conducted and compared to existing NOMA systems to show the effectiveness of the suggested approach in terms of EE and SE. [ABSTRACT FROM AUTHOR]

Summary: Trust is considered as the most significant factor that helps in enforcing cooperation among the autonomous nodes of Mobile Ad hoc Network (MANETs). The computation of trust is essential for assessing the level of cooperation rendered by each individual mobile toward the activity of data routing. The calculation of trust in a self‐configuring and infrastructure‐less network is a challenge due to the dynamic movement of mobile nodes. Moreover, the trust of intermediate nodes in the routing path needs to be estimated for preventing the deterioration of network performance. In this paper, a Fuzzy COPRAS‐based Node Cooperation Enforcing Trust Estimation (FCOPRAS‐NCETE) Scheme was proposed for maintaining superior Quality of Service (QoS) in the event of reliable data dissemination. This proposed FCOPRAS‐NCETE Scheme was proposed for comprehensive ranking of mobile nodes acting as intermediate nodes between the source and destination nodes. It incorporated the benefits of fuzzy set theory and COmplex PRoportional ASsessment of alternatives (COPRAS) to determine the trust of intermediate nodes for isolating them from the routing path in the uncertain routing process with the objective to maintain superior QoS in the network. The simulation experiments of the proposed FCOPRAS‐NCETE Scheme conducted using ns‐2 confirmed its predominance in improving the throughput, packet dissemination rate, packet loss rate, energy consumptions and total overhead with different number of mobile nodes, CBR traffic rate and pairs of source and destination nodes in the network. [ABSTRACT FROM AUTHOR]

Summary: Achieving a fair usage of network resources is of vital importance in Slice‐ready 5G network. The dilemma of which network slice to accept or to reject is very challenging for the Infrastructure Provider (InfProv). On one hand, InfProv aims to maximize the network resources usage by accepting as many network slices as possible; on the other hand, the network resources are limited, and the network slice requirements regarding Quality of Service (QoS) need to be fulfilled. In this paper, we devise three admission control mechanisms based on Reinforcement Learning, namely, Q‐Learning, Deep Q‐Learning, and Regret Matching, which allow deriving admission control decisions (policy) to be applied by InfProv to admit or reject network slice requests. We evaluated the three algorithms using computer simulation, showing results on each mechanism's performance in terms of maximizing the InfProv revenue and their ability to learn offline or online. [ABSTRACT FROM AUTHOR]

Summary: Most often, in centralized distributed computing, users are getting impatient by experiencing the delays in loading the content of the web applications over the internet; it is usually caused by the poor latency management and is becoming a catastrophic situation in availing the services and applications of the centralized‐cloud computing; cloud being a distributed platform, its customers are facing the latencies issues at the various tiers of the cloud. Workloads distributions are occurring concurrently on various virtual cloud platforms. Latency‐oriented applications and services usually in cloud platform are running over various virtual machines and possess the high complexities while interacting and face the difficulties in the consolidations of the various applications containing heterogenetic workloads. In this paper, we study the fog computing and consider that it will be a feasible platform to get rid of the cloud high‐latency issues and to reduce the delay time and workflow across the network. The main purpose is to enhance the latency across the various nodes in a network. The factors like interference, availability, and interaction among various participating nodes with nearer VMware are of importance for reducing the latencies. Reduced latencies will enhance the quality of service parameters, resources, and services availability. Latency can be an important factor for the resource optimization issues in cloud computing. The comparisons with existing technologies greatly show that latency in fog is quite efficient than in the cloud paradigm. [ABSTRACT FROM AUTHOR]

Summary: Cloud computing provides solutions to many scientific and business applications. Large‐scale scientific applications, which are structured as scientific workflows, are evaluated through cloud computing. In this paper, we proposed a Quality‐of‐Service‐aware fault‐tolerant workflow management system (QFWMS) for scientific workflows in cloud computing. We have considered two real‐time scientific workflows, i.e., Montage and CyberShake, for an evaluation of the proposed QFWMS. The results of the proposed QFWMS scheduling were evaluated through simulation environment WorkflowSim and compared with three well‐known heuristic scheduling policies: (a) minimum completion time (MCT), (b) Maximum‐minimum (Max‐min), and (c) Minimum‐minimum (Min‐min). By considering Montage scientific workflow, the proposed QFWMS reduces the make‐span 8.86%, 8.94%, and 5.53% compared with existing three heuristic policies. Similarly, the proposed QFWMS reduces the cost 6.19%, 3.52%, and 3.60% compared with existing three heuristic policies. Likewise, by considering CyberShake scientific workflow, the proposed QFWMS reduces the make‐span 19.54%, 21.41%, and 25.71% compared with existing three heuristic policies. Similarly, the proposed QFWMS reduces the cost 8.78%, 8.40%, and 8.61% compared with existing three heuristic policies. More so, for QFWMS, SLA is neither violated for time constraints nor for cost constraints. While for MCT, Max‐min and Min‐min scheduling policies, SLA is violated 32, 37, and 23 times, respectively. Conclusively, the proposed QFWMS scheduling and management system is one of the significant workflow management systems for execution and management of scientific workflows in cloud computing. [ABSTRACT FROM AUTHOR]

Summary: In an infrastructure‐critical manufacturing industry, continuous monitoring of the assembly lines with internet‐integrated sensors in an unforeseeable, stochastic, and harsh environment becomes indispensable for real‐time fault detection, location, and isolation. State‐of‐the‐art literature suggest that the Cognitive Radio‐based Industrial Internet of Things (CR‐IIoTs), a spectrum aware wireless communication paradigm, is best suited for monitoring as they are proficient in overcoming spectrum scarcity in a 2.4‐GHz industrial, scientific, and medical (ISM) band and guarantee a threshold Quality of Service (QoS) in hostile environs. Nonetheless, CR‐IIoTs and the Cognitive Radio‐based network archetype are susceptible to internal and external security threats at the application layer and vulnerable to Spectrum Sensing Data Falsification (SSDF) at Data Link Layer (DLL). In CR‐IIoTs, cooperative spectrum sensing (CSS) is a competent technique to ameliorate the performance of Primary User (PU) detection and optimizes the idle licensed spectrum bands access management. In this paper, a novel belief adaption framework in conjunction with an optimized secure communication scheme (termed as CBAF) based on the Certificateless‐Public Key Cryptography (CL‐PKC) is proposed for robust CSS in CR‐IIoTs. CBAF proficiently provides full‐Perfect Forward Secrecy, Ephemeral Secret Leakage‐Resilience, Public Key Replacement‐Resilience Malicious but Passive KGC‐Resilience, and Key Escrow Resilience. Simulation analysis pertaining to network performance indices ascertains the efficacy of CBAF, as it outperforms the state‐of‐the‐art in throughput, packet delivery ratio, and communication overhead by 8.5%, 6.7%, and 19.9% respectively. Under internal attacks, CBAF outperforms the best from state‐of‐the‐art by 11.3% in On‐Off attack, 19.7% in Data Tampering attack, 21.1% in SDF attack, and 13.4% in DDoS attack. [ABSTRACT FROM AUTHOR]

Summary: This paper introduces a new way to allocate the modulation format and improves the energy efficiency in elastic optical networks. For every connection request, both the quality of transmission and quality of service requirements are investigated. The allocation of modulation formats is based on both the physical distance and the required number of frequency slots. To improve the energy efficiency, Yen's algorithm is executed for every connection requested, and the lightpath with the lowest power consumption is selected. Numerical results were compared with adaptive modulation algorithms presented in the existing literature. The energy efficiency was improved by up to 27%, the used bandwidth available was reduced by up to 60%, and the blocking probability was decreased by 30% using our proposed adaptive algorithm. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the energy‐efficient resource allocation problem in orthogonal frequency division multiplexing (OFDM)‐based cognitive radio (CR) networks with multiple decode‐and‐forward relays. In order to maximize the system energy efficiency (EE), we jointly optimize the relay selection, subcarrier pairing, and power allocation subject to the transmit power constraints, the interference thresholds at the primary system, and the quality of service (QoS) provisioning for the CR system. Using the fractional programming and the Lagrangian dual decomposition method, the optimization problem which is a mixed‐integer nonlinear program (MINLP) can be efficiently solved to obtain an asymptotically optimal solution. We also propose a suboptimal scheme to reduce the computational complexity at the expense of a little performance loss. Simulation results demonstrate the performance of proposed schemes and the effect of the constraints values. [ABSTRACT FROM AUTHOR]

In recent years, the vehicular ad hoc network has attracted worldwide attention from academe and industry. Many researches have been executed to improve the quality of services (QoS) of the intelligent transportation system. However, current existing channel access schemes at the medium access control layer specified in 802.11 protocol, including hybrid coordination function control channel access (HCCA) and enhanced distributed channel access, could not efficiently achieve the QoS requirements in some special situations. This paper proposes a delay guaranteed HCCA (DG-HCCA) scheduling scheme, which works based on a Markov decision process model and the measurement of historic performance, to guarantee the QoS enhanced data transmission for vehicles to roadside unit. Besides, this paper also presents a performance analysis model to systematically evaluate the system performance of the channel utility and the average delay. The performance of the proposed delay guaranteed HCCA scheduling scheme is compared with that of original HCCA scheme specified in 802.11p standard and other 2 HCCA improved schemes by the simulation experiments. The simulation results demonstrate that the proposed solution could highly fulfill the transmission delay requirements with a better channel utility and less loss rates than those by the standard HCCA scheme and other 2 schemes. [ABSTRACT FROM AUTHOR]

Summary: With the recent development of LTE‐A/5G technologies, data sharing among mobile devices offer an attractive opportunity to reduce Internet access. However, it requires smart strategies to share the data with low trade‐offs in time, cost, and energy. Several existing schemes offer a super‐peer‐based two‐tier model using a distributed hash table (DHT) organization for smart devices having device‐to‐device (D2D)/Bluetooth/WiFi capabilities. The primary focus of these schemes has been to reduce Internet usage by increased D2D content sharing. However, the real challenge is not in creating a two‐tier model, but evolving an efficient overlay that offers enhanced opportunities for D2D content sharing over the existing model. In this paper, we formulated a P‐median‐based selection of tier‐1 devices in a distribution network and solved it using the Lagrangian relaxation method. The tier‐2 devices become clients seeking content sharing services from tier‐1 devices. A strong motivation in this work is to raise a user's perception of the grade of service known as quality of experience (QoE). We analyzed the challenge for QoE assessment in resource‐constrained smartphones under the proposed model of enhanced D2D communication. Our focus is to establish a framework to evaluate QoE for applications and services over LTE‐A/5G networks with an improved D2D communication level. The simulation and the experimental results validate the claim that substantial improvements in QoE are possible with the proposed mathematical model for selecting and placing tier‐1 mobile devices and maintaining a DHT for D2D communication. [ABSTRACT FROM AUTHOR]

Summary: Task scheduling in the cloud is the multiobjective optimization problem, and most of the task scheduling problems fail to offer an effective trade‐off between the load, resource utilization, makespan, and Quality of Service (QoS). To bring a balance in the trade‐off, this paper proposes a method, termed as crow–penguin optimizer for multiobjective task scheduling strategy in cloud computing (CPO‐MTS). The proposed algorithm decides the optimal execution of the available tasks in the available cloud resources in minimal time. The proposed algorithm is the fusion of the Crow Search optimization Algorithm (CSA) and the Penguin Search Optimization Algorithm (PeSOA), and the optimal allocation of the tasks depends on the newly designed optimization algorithm. The proposed algorithm exhibits a better convergence rate and converges to the global optimal solution rather than the local optima. The formulation of the multiobjectives aims at a maximum value through attaining the maximum QoS and resource utilization and minimum load and makespan, respectively. The experimentation is performed using three setups, and the analysis proves that the method attained a better QoS, makespan, Resource Utilization Cost (RUC), and load at a rate of 0.4729, 0.0432, 0.0394, and 0.0298, respectively. [ABSTRACT FROM AUTHOR]

Summary: Recently, academic and industrial research communities are paying more explicit attention to the 5G multiple radio access technology ultra‐dense networks (5G multi‐RAT UDNs) for boosting network capacity, especially in UD urban zones. To this aim, in this paper, we intend to tackle the user association problem in 5G multi‐RAT UDNs. By considering the decoupled uplink/downlink access (DUDA), we divide our user association problem into two distinct subproblems representing, respectively, the uplink and the downlink channels. Next, we formulated each one as a nonlinear optimization problem with binary variables. Then, to solve them, we were restricted by the hard complexity, as well as the hard feasibility of centralized user association schemes. Thus, to resolve our user association problem in a reasonable time and distributed manner, we formulated each subproblem as a many‐to‐one matching game based on matching theory. Next, we provide two fully distributed association algorithms to compute the uplink and downlink stable matching among user equipments (UEs) and base stations (BSs). Simulation results corroborate our theoretical model and show the effectiveness and improvement of our achieved results in terms of the overall network performance, quality of service (QoS), and energy efficiency (EE) of UEs. [ABSTRACT FROM AUTHOR]

Summary: Enabling a reliable and secure communication in cognitive radio networks (CRNs) is one of the interesting and demanding research areas and these days, it is used in wide range of applications. The traditional works mainly aimed to improve the spectrum efficiency and bandwidth utilization of the CRN. Moreover, it focused on attack detection in the network for improving the reliability. Thus, this work intended to secure the CRN by considering the objectives of both attack detection and quality of service (QoS) improvement. For this purpose, an integrated digital signature and mutual authentication (IDsMA) mechanism is proposed in this paper, which incorporates the benefits of both security and reliability. Also, the Rivest‐Sharmir‐Adlemann (RSA) algorithm is utilized to encrypt and decrypt the data at the transmitter and receiver side. Here, the unique user ID is generated by the service eNodeB based on the hash function, which is validated at the server side for validating the authenticity of the user. Furthermore, the particle swarm optimization (PSO) and relevant vector machine (RVM) techniques are utilized for optimal channel selection and attack classification. The simulation results evaluate the performance of the proposed technique by using various performance measures. Also, its superiority is proved by comparing the proposed technique with the existing techniques. [ABSTRACT FROM AUTHOR]

Summary: Wireless network with high data rate applications has seen a rapid growth in recent years. This improved quality of service (QoS) leads to huge energy consumption in wireless network. Therefore, in order to have an energy‐efficient resource allocation in cellular system, a device‐to‐device (D2D) communication is the key component to improve the QoS. In this paper, we propose a noncooperative game (NCG) theory approach for resource allocation to improve energy efficiency (EE) of D2D pair. A three‐tier network with macrocell base station (MBS), femtocell base station (FBS), and D2D pair is considered, which shares the uplink resource block. A resource allocation strategy with constraints is arrived, which maintains minimum throughput for each user in the network. The proposed resource allocation strategy optimizes the EE of D2D pair in the three‐tier network, which achieves Nash equilibrium (NE) and Pareto optimality (PO). Simulation results validate that EE is uniform and optimum for all D2D pair, which converges to NE when channel is static and it converges to PO when the channel is dynamic. [ABSTRACT FROM AUTHOR]

Optical burst switching (OBS) is the most favourable switching paradigm for future all-optical networks. Burst assembly is the first process in OBS and it consists of aggregating clients packets into bursts. Assembled bursts wait for an offset time before being transmitted to their intended destinations. Offset time is used to allow burst control packet reserve required resources prior to burst arrival. Burst assembly process and offset-time create extra delay in OBS networks. To make OBS suitable for real time applications, this extra latency needs to be controlled. This paper proposes and evaluates a novel offset time and burst assembly scheme to address this issue. Constant bit rate (CBR) traffic that has stringent end-to-end delay QoS requirements is used in this study. The proposed scheme is called hybrid offset-time and burst assembly algorithm (H-OTBA). The objective of the paper is achieved by controlling maximum burst transfer delay parameters of CBR. The proposed scheme was evaluated via network simulation. Simulation results demonstrate that, H-OTBA has effectively reduced end-to-end delay for CBR traffic compared with current solutions. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents our experiences with SoftToken protocol, a new contention-free medium access control protocol for wireless local area network. This new mechanism adds a token-passing procedure on top of Institute of Electrical and Electronics Engineers 802.11 for coordinating transmissions and avoiding collisions. With this extension, it becomes possible to offer differentiated services in a deterministic manner. In this paper, we provide a thorough performance evaluation of SoftToken in terms of its scalability, robustness and efficiency in comparison with Institute of Electrical and Electronics Engineers 802.11 and a time division multiple access (TDMA)-based Wi-Fi extension called Soft-TDMA. Our evaluation is based on experiments run on different test beds covering different scenarios in a wired virtual network environment and practical wireless environments supporting different types of traffic. The results show that SoftToken indeed provides better QoS performance in scenarios that require service differentiation (e.g. mixed voice over Internet protocol and best effort traffic scenarios). Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Internet protocol (IP) traffic connections arrive dynamically at wavelength-division multiplexing (WDM) network edges with low data rates compared with the wavelength capacity, availability, and quality-ofservice (QoS) constraints. This paper introduces a scheme to be integrated into the control and management plane of IP/WDM networks to satisfy the availability and QoS required for IP traffic connections bundled onto a single wavelength (lightpath) in WDM networks protected by shared-backup path protection (SBPP). This scheme consists of two main operations: (i) routing multi-granular connections and traffic grooming policies, and (ii) providing appropriate shared protection on the basis of subscribers' service-level agreements in terms of data rate, availability, and blocking probability. Using the Markov chain process, a probabilistic approach is developed to conceive connection blocking probability models, which can quantify the blocking probability and service utilization of M:N and 1:N SBPP schemes. The proposed scheme and developed mathematical models have been evaluated in terms of bandwidth blocking ratio, availability satisfaction rate, network utilization, and connection blocking probability performance metrics. The obtained research results in this paper provide network operators an operational setting parameter, which controls the allocation of working and backup resources to dynamic IP traffic connections on the basis of their priority and data rate while satisfying their requirements in terms of bandwidth and availability. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a novel framework for quality‐of‐service (QoS) multicast routing with resource allocation that represents QoS parameters, jitter delay, and reliability, as functions of adjustable network resources, bandwidth, and buffer, rather than static metrics. The particular functional form of QoS parameters depends on rate‐based service disciplines used in the routers. This allows intelligent tuning of QoS parameters as functions of allocated resources during the multicast tree search process, rather than decoupling the tree search from resource allocation. The proposed framework minimizes the network resource utilization while keeping jitter delay, reliability, and bandwidth bounded. This definition makes the proposed QoS multicast routing with resource allocation problem more general than the classical minimum Steiner tree problem. As an application of our general framework, we formulate the QoS multicast routing with resource allocation problem for a network consisting of generalized processor sharing nodes as a mixed‐integer quadratic program and find the optimal multicast tree with allocated resources to satisfy the QoS constraints. We then present a polynomial‐time greedy heuristic for the QoS multicast routing with resource allocation problem and compare its performance with the optimal solution of the mixed‐integer quadratic program. The simulation results reveal that the proposed heuristic finds near‐optimal QoS multicast trees along with important insights into the interdependency of QoS parameters and resources. [ABSTRACT FROM AUTHOR]