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Fifth-generation (5G) networks play a significant role in handover methods. 5G wireless network is open, flexible and highly heterogeneous along with the overlay coverage and small cell deployments. Handover management is one of the main problems in the heterogeneous network. Also, handover satisfies the needs of ultra-reliable communications along with very high reliability and availability in 5G networks. Handover management deals with every active connection of a user’s device, which moves the connection between the user’s device and the counterparty from one network point to another. Thus, the handover decision determines the best access network and also decides whether the handover is performed or not.

The main intention of this survey is to review several existing handover technologies in 5G. Using the categories of analysis, the existing techniques are divided into different techniques such as authentication-based techniques, blockchain-based techniques, software-defined-based techniques and radio access-based techniques. The survey is made by considering the methods such as used software, categorization of methods and used in the research works. Furthermore, the handover rate is considered for performance evaluation for the handover techniques in 5G. The drawbacks present in the existing review papers are elaborated in research gaps and issues division.

Through the detailed analysis and discussion, it can be summarized that the widely concerned evaluation metric for the performance evaluation is the handover rate. It is exploited that the handover rate within the range of 91%–99% is achieved by three research papers.

A survey on the various handover mechanisms in 5G networks is expected in this study. The research papers used in this survey are gathered from different sources such as Google Scholar and IEEE. Also, this survey suggests a further extension for the handover mechanism in 5G networks by considering various research gaps and issues.

Software-define vehicular networks (SDVN) assure the direct programmability for controlling the vehicles with improved accuracy and flexibility. In this research, the resource allocation strategy is focused on which the seek-and-destroy algorithm is implemented in the controller in such a way that an effective allocation of the resources is done based on the multi-objective function.

The purpose of this study is focuses on the resource allocation algorithm for the SDVN with the security analysis to analyse the effect of the attacks in the network. The genuine nodes in the network are granted access to the communication in the network, for which the factors such as trust, throughput, delay and packet delivery ratio are used and the algorithm used is Seek-and-Destroy optimization. Moreover, the optimal resource allocation is done using the same optimization in such a way that the network lifetime is extended.

The security analysis is undergoing in the research using the simulation of the attackers such as selective forwarding attacks, replay attacks, Sybil attacks and wormhole attacks that reveal that the replay attacks and the Sybil attacks are dangerous attacks and in future, there is a requirement for the security model, which ensures the protection against these attacks such that the network lifetime is extended for a prolonged communication. The achievement of the proposed method in the absence of the attacks is 84.8513% for the remaining nodal energy, 95.0535% for packet delivery ratio (PDR), 279.258 ms for transmission delay and 28.9572 kbps for throughput.

The seek-and-destroy algorithm is one of the swarm intelligence-based optimization designed based on the characteristics of the scroungers and defenders, which is completely novel in the area of optimizations. The diversification and intensification of the algorithm are perfectly balanced, leading to good convergence rates.

This paper models the cost efficiency of service function chaining (SFC) in software-defined LTE networks and compares it with traditional LTE networks.

Both the capital expenditure (CAPEX) and operational expenditure (OPEX) of the SFC are quantified using an average Finnish mobile network in 2015 as a reference. The modeling inputs are gathered through semi-structured interviews with Finnish mobile network operators (MNO) and network infrastructure vendors operating in the Finnish market.

The modeling shows that software-defined networking (SDN) can reduce SFC-related CAPEX and OPEX significantly for an average Finnish MNO in 2015. The analysis on different types of MNOs implies that a MNO without deep packet inspection sees the biggest cost savings compared to other MNO types.

Service function investments typically amount to 5-20 per cent of the overall MNO network investments, and savings in SFC may impact highly on the cost structure of a MNO. In addition, SFC acts as both a business interface, which connects the local MNOs with global internet service providers, and as a technical interface, where the 3GPP and IETF standards meet. Thus, the cost efficient operation of SFC may bring competitive advantages to the MNO.

The results show solid basis of network-related cost savings in SFC and contributes to MNOs making cost conscious investment decisions. In addition, the results act as a baseline scenario for further studies that combine SDN with virtualization to re-optimize network service functions.

In this paper, the authors present different methods for reconfigurable finite impulse response (RFIR) filter design. Distributed arithmetic (DA)-based reconfigurable FIR filter design is suitable for software-defined radio (SDR) applications. The main contribution of reconfiguration is reuse of registers, multipliers, adders and to optimize various parameters such as area, power dissipation, speed, throughput, latency and hardware utilizations of flip-flops and slices. Therefore, effective design of building blocks will be optimized for RFIR filter with all the above parameters.

The modified, direct form register structure of FIR filter contributes the reuse concept and allows utilization of less number of registers and parallel computation operations. The disadvantage of DA and other conventional methods is delay increases proportionally with filter length. This is due to different partial products generated by adders. The usage of adder and multipliers in DA-FIR filter restricts the area and power dissipation because of their complexity of generation of sum and carry bits. The hardware implementation time of an adder can be reduced by parallel prefix adder (PPA) usage based on Ling equation. PPA uses shift-add multiplication, which is a repetitive process of addition, and this process is known as Bypass Zero feed multiplicand in direct multiplication, and the proposed technique optimizes area-power product efficiently. The modified DA (MDA)-based RFIR filter is designed for 64 taps filter length (N). The design is developed by using Verilog hardware description language and implemented on field-programmable gate array. Also, this design validates SDR channel equalizer.

Both RFIR and SDR are integrated as single system and implemented on Artix-7 development board of XC7A100tCSG324 and exploited the advantages in area-delay, power-speed products and energy efficiency. The theoretical and practical comparisons have been carried out, and the results are compared with existing DA-RFIR designs in terms of throughput, latency, area-delay, power-speed products and energy efficiency, which are improved by 14.5%, 23%, 6.5%, 34.2% and 21%, respectively.

The DA-based RFIR filter is validated using Chipscope Pro software tool on Artix-7 FPGA in Xilinx ISE design suite and compared constraint parameters with existing state-of-art results. It is also tested the filtering operation by applying the RFIR filter on Audio signals for removal of noisy signals and it is found that 95% of noise signals are filtered effectively.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

This study explores challenges facing the applicability of deep learning (DL) in software-defined networks (SDN) based campus networks. The study intensively explains the automation problem that exists in traditional campus networks and how SDN and DL can provide mitigating solutions. It further highlights some challenges which need to be addressed in order to successfully implement SDN and DL in campus networks to make them better than traditional networks.

The study uses a systematic literature review. Studies on DL relevant to campus networks have been presented for different use cases. Their limitations are given out for further research.

Following the analysis of the selected studies, it showed that the availability of specific training datasets for campus networks, SDN and DL interfacing and integration in production networks are key issues that must be addressed to successfully deploy DL in SDN-enabled campus networks.

This study reports on challenges associated with implementation of SDN and DL models in campus networks. It contributes towards further thinking and architecting of proposed SDN-based DL solutions for campus networks. It highlights that single problem-based solutions are harder to implement and unlikely to be adopted in production networks.

Collaborative robots – “cobots” – are intended for direct interaction with a human worker, handling a shared payload. They are a marked departure from autonomous industrial robots which must be isolated from people for safety reasons. Cobots are also distinct from teleoperators, in which a human operator controls a robot and payload remotely. Cobots interact with people by producing software‐defined “virtual surfaces” which constrain and guide the motion of the shared payload, but add little or no power. Ergonomic as well as productivity benefits result from combining the strength and computer‐interface of the cobot with the sensing and dexterity of the human worker. This paper explains cobots as one approach to an emerging class of materials handling equipment called Intelligent Assist Devices (IADs). We describe two cobots of this class presently in industrial testbed settings. Future applications of cobots’ virtual surfaces are tool guidance in image guided surgery, and haptic display in which the surfaces of a CAD model can be felt.

In recent years, it is imperative to establish the structure of manufacturing industry in the context of smart factory. Due to rising demand for exchange of information with various devices, and huge number of sensor nodes, the industrial wireless networks (IWNs) face network congestion and inefficient task scheduling. For this purpose, software-defined network (SDN) is the emerging technology for IWNs, which is integrated into cognitive industrial Internet of things for dynamic task scheduling in the context of industry 4.0.

In this paper, the authors present SDN based dynamic resource management and scheduling (DRMS) for effective devising of the resource utilization, scheduling, and hence successful transmission in a congested medium. Moreover, the earliest deadline first (EDF) algorithm is introduced in authors’ proposed work for the following criteria’s to reduce the congestion in the network and to optimize the packet loss.

The result shows that the proposed work improves the success ratio versus resource usage probability and number of nodes versus successful joint ratio. At last, the proposed method outperforms the existing myopic algorithms in terms of query response time, energy consumption and success ratio (packet delivery) versus number of increasing nodes, respectively.

The authors proposed a priority based scheduling between the devices and it is done by the EDF approach. Therefore, the proposed work reduces the network delay time and minimizes the overall energy efficiency.

The purpose of this paper is to improve the tracking performance of the carrier phase lock loop (PLL) in the strapdown inertial navigation system/global positioning system (SINS/GPS) integrated system with an innovative scheme of ultra‐tight integration.

First, providing the Doppler frequency for PLL using SINS velocity could enlarge the loop equivalent bandwidth and reduce the dynamic effect on the carrier loop. Meanwhile, lowering the filter bandwidth could increase the immunity to noise. Second, the relationships between the PLL and SINS errors have been analyzed, and then the PLL error model is established to eliminate the correlation between the pseudo‐range‐rate error and SINS velocity error. Third, the carrier frequency is regulated to improve the tracking accuracy, according to the error estimations of Kalman filter.

The innovative ultra‐tightly integrated system could not only enhance the anti‐jamming capability and the dynamic tracking performance of the tracking loops, but also improve the pseudo‐range‐rate measurements accuracy for the integrated filter.

This paper provides further study on the method of enhancing the carrier‐tracking performance and improving the integration mode in the ultra‐tightly integrated system based on the software‐defined GPS receiver.

Addresses the current state of the art of wireless technologies and infrastructures, projects where the field will be in the next decade, and discusses some of the challenges that must be met. Elaborates on the established major areas of commercial wireless access technology in the USA, ranked by deployment extent, which are: terrestrial mobile wireless access; terrestrial broadband wireless access; and mobile satellite service.