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Vertical handoff mechanism (VHO) becomes very popular because of the improvements in the mobility models. These developments are less to certain circumstances and thus do not provide support in generic mobility, but the vertical handover management providing in the heterogeneous wireless networks (HWNs) is crucial and challenging. Hence, this paper introduces the vertical handoff management approach based on an effective network selection scheme.

This paper aims to improve the working principle of previous methods and make VHO more efficient and reliable for the HWN.Initially, the handover triggering techniques is modelled for identifying an appropriate place to initiate handover based on the computed coverage area of cellular base station or wireless local area network (WLAN) access point. Then, inappropriate networks are eliminated for determining the better network to perform handover. Accordingly, a network selection approach is introduced on the basis ofthe Fractional-dolphin echolocation-based support vector neural network (Fractional-DE-based SVNN). The Fractional-DE is designed by integrating Fractional calculus (FC) in Dolphin echolocation (DE), and thereby, modifying the update rule of the DE algorithm based on the location of the solutions in past iterations. The proposed Fractional-DE algorithm is used to train Support vector neural network (SVNN) for selecting the best weights. Several parameters, like Bit error rate (BER), End to end delay (EED), jitter, packet loss, and energy consumption are considered for choosing the best network.

The performance of the proposed VHO mechanism based on Fractional-DE is evaluated based on delay, energy consumption, staytime, and throughput. The proposed Fractional-DE method achieves the minimal delay of 0.0100 sec, the minimal energy consumption of 0.348, maximal staytime of 4.373 sec, and the maximal throughput of 109.20 kbps.

In this paper, a network selection approach is introduced on the basis of the Fractional-Dolphin Echolocation-based Support vector neural network (Fractional-DE-based SVNN). The Fractional-DE is designed by integrating Fractional calculus (FC) in Dolphin echolocation (DE), and thereby, modifying the update rule of the DE algorithm based on the location of the solutions in past iterations. The proposed Fractional-DE algorithm is used to train SVNN for selecting the best weights. Several parameters, like Bit error rate (BER), End to end delay (EED), jitter, packet loss, and energy consumption are considered for choosing the best network.The performance of the proposed VHO mechanism based on Fractional-DE is evaluated based on delay, energy consumption, staytime, and throughput, in which the proposed method offers the best performance.

An infrastructure based on multiple heterogeneous access networks is one of the leading enablers for the emerging paradigm of pervasive computing. The optimal management of diverse networking resources is a challenging problem. This paper aims to present a context‐aware policy mechanism with related end‐to‐end (E2E) evaluation algorithm for adaptive connectivity management in multi‐access wireless networks.

A policy is used to express the criteria for adaptive selection of the best local and remote network interfaces. The best connection can then be used for the establishment of a channel as well as for the maintenance of on‐going data transmission. Rich context information is considered in the policy representation with respect to user profile and preference, application characteristics, device capability, and network quality of service conditions. The decision of the best access networks to be used is made on the basis of an E2E evaluation process. The decision can be made in both master–slave and peer‐to‐peer modes, according to the decision matrixes generated in both ends. The paper focuses on the policy representation and connection evaluation algorithm. A case study is presented to show the usability of the proposed policy mechanism and decision‐making algorithm in the adaptiv management of heterogeneous networking resources.

The proposed policy mechanism is for the adaptive decision of connection selection in channel establishment and vertical handoff between heterogeneous access networks. A policy is represented as a four‐tuple, including the direction and the class of traffic, requirement expression, and concrete evaluation items. Three steps are involved in the evaluation process, namely policy traverse, decision matrix calculation, and decision‐making.

The policy mechanism can be easily extended to include adaptive selection of multiple user devices in addition to multiple connections.

Heterogeneous network is mainly focused to enrich the demands of network's traffic and data rate. Heterogeneous network is an integrated system composed of diverse radio access technologies such as Wi-Fi, UMTS and WiMAX soon. To exchange the packets among these different wireless technologies, an adoptable vertical handoff (VHO) is required.

Various types of techniques have been proposed in line with VHO. However these algorithms lead to the threat of high dropping rate and poor Quality of Service (QoS). We modulate a new methodology by integrating Convolutional Neural Network with Fuzzy Logic (CNN-FL) for an optimum vertical handoff decision process (VHDP). The CNN-FL–based VHDP is very effective because of nonlinearity and generalization capability with uncertain data inputs.

The performance results exhibit that proposed methods show efficient for selecting the appropriate network with maximum throughput. At the same time, the proposed method reduces computational complexity and dropping rate considerably.

This paper proposes a novel CNN model along with a FL model for achieving a vertical hand off.

Vertical handover has been grown rapidly due to the mobility model improvements. These improvements are limited to certain circumstances and do not provide the support in the generic mobility, but offering vertical handover management in HetNets is very crucial and challenging. Therefore, this paper presents a vertical handoff management method using the effective network identification method.

This paper presents a vertical handoff management method using the effective network identification method. The handover triggering schemes are initially modeled to find the suitable position for starting handover using computed coverage area of the WLAN access point or cellular base station. Consequently, inappropriate networks are removed to determine the optimal network for performing the handover process. Accordingly, the network identification approach is introduced based on an adaptive particle-based Sailfish optimizer (APBSO). The APBSO is newly designed by incorporating self-adaptive particle swarm optimization (APSO) in Sailfish optimizer (SFO) and hence, modifying the update rule of the APBSO algorithm based on the location of the solutions in the past iterations. Also, the proposed APBSO is utilized for training deep-stacked autoencoder to choose the optimal weights. Several parameters, like end to end (E2E) delay, jitter, signal-to-interference-plus-noise ratio (SINR), packet loss, handover probability (HOP) are considered to find the best network.

The developed APBSO-based deep stacked autoencoder outperformed than other methods with a minimal delay of 11.37 ms, minimal HOP of 0.312, maximal stay time of 7.793 s and maximal throughput of 12.726 Mbps, respectively.

The network identification approach is introduced based on an APBSO. The APBSO is newly designed by incorporating self-APSO in SFO and hence, modifying the update rule of the APBSO algorithm based on the location of the solutions in the past iterations. Also, the proposed APBSO is used for training deep-stacked autoencoder to choose the optimal weights. Several parameters, like E2E delay, jitter, SINR, packet loss and HOP are considered to find the best network. The developed APBSO-based deep stacked autoencoder outperformed than other methods with minimal delay minimal HOP, maximal stay time and maximal throughput.

This paper proposes a new Heterogeneous Multi‐hop Cellular IP (MCIP) network that integrates multi‐hop communication with Cellular IP. MCIP increases the coverage of the wireless network and improves the network robustness against adverse propagation phenomena by supporting communication in dead zones and areas with poor radio coverage. MCIP includes three components: location management, connection management and route reconfiguration. Location management is responsible for maintaining the location information for Mobile Stations (MSs) in a local domain. Connection management establishes an initial path for data transmission and a route reconfiguration mechanism is proposed to take advantage of various multi‐hop connection alternatives available based on terminal interfaces, network accessibility and topology. Our simulation results show that MCIP performs well in networks of various sizes including scalability, throughput, and packet delay.

The paper aims to propose an optimized handover necessity estimation scheme for a mobile terminal (MT) traversing from a third-generation (3G) cellular network into the wireless local area network (WLAN) cell for reducing the number of handover failures and unnecessary handovers.

The proposed optimized handover necessity estimation scheme comprises of two algorithms – a “travelling time prediction” reliant on consecutive received signal strength (RSS) measurements and MT’s velocity, and a “time threshold estimation” depending on the handover latency, WLAN’s cell radius, tolerable handover failure probability and the tolerable unnecessary handover probability.

Our performance analysis reveals that the suggested mechanism effectively minimizes the number of handover failures and unnecessary handovers by 60 per cent as compared to the already proposed schemes in the literature.

The convergence of Internet and wireless mobile communication accompanied by a massive increase in the number of cellular subscribers has led mobility management to emerge as a significant and challenging domain for wireless mobile communication over the Internet. Mobility management enables serving networks to locate roaming terminals for the call delivery (location management) and ensures a seamless connection as MT enters into the new service area (handover management). In this manuscript, an optimized handover necessity estimation scheme has been envisaged for reducing the probability of handover failures and unnecessary handovers from 3G cellular networks to WLANs to provide optimal network utilization along with an enhanced user satisfaction. Performance analysis reveals that the suggested scheme yields enhanced results as compared to the schemes already proposed in the literature.

Patient handoffs involve the exchange of information between health professionals accompanying a transfer of responsibility for, or control of, a patient. Concerns over the safety risks of poor handoffs have resulted in regulatory pressure to standardize practice and considerable growth in research. But handoffs involve more than information transfer, and their consequences for health care organizations extend beyond the safety of patients. Using an organization theory lens, we review the literature on handoffs and propose a framework that characterizes handoffs as multifunctional, situated organizational routines. We also identify implications for researchers and hospital policymakers. Standardization and improvement efforts run the risk of causing unintended problems if they overlook the complexity of handoff and the larger organizational functions it serves. Deepening our understanding of the multifunctional, situated nature of handoff can lead to improvement efforts that not only safeguard individual patients, but also enhance the capabilities of the larger health care organization.

Mobility management for single‐hop cellular networks has received much research attention in the last few years. One of the research challenges for 4G wireless systems is the design of mobility management techniques that integrate cellular and ad‐hoc networks. Currently, there are no structured mobility management schemes for these heterogeneous multi‐hop networks. This paper aims to address these issues.

This paper describes techniques for tracking a mobile node (MN) in an integrated architecture with minimum overhead. This paper proposes group rerouting concept.

The paper implements and evaluates the proposed protocol by using the network simulator (NS‐2). The proposed protocol increases performance compared to broadcasting schemes.

This scheme considers devices with two interfaces only.

The paper proposes a scheme to extend the coverage of cellular base stations by using ad‐hoc devices.

This paper describes techniques for tracking an MN in an integrated architecture with minimum overhead. This scheme is independent of the routing protocol used in a multi‐hop network.

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.

Purpose – This chapter argues that the concept of agility is an effective robust framework for designing sustainable health care systems.

Design/methodology/approach – This case study of Alegent Health was based on 7 years of data collection. It includes observations of meetings, large-group interventions, and other activities; site visits to different hospitals in the system to observe changes in practice; interviews with Alegent Health executives, primary care physicians, hospital presidents, specialist physicians and physician groups, and health systems staff and nurses; and a variety of archival data including meeting minutes, video tapes, conference proceedings, and web site material.

Findings – The Alegent Health system has evolved over time according to the principles of agility. It built a series of new capabilities that contribute to improved clinical outcomes, sustained financial results, and more socially and ecologically responsible results. Designing health care systems based on agility is a more effective and sustainable approach than relying on legislative or other criteria.

Originality/value – The discussion of sustainability in health care has focused primarily on specific projects or how to respond to specific technological, regulatory, or clinical changes. Alegent Health's experience provides important lessons, opportunities, and challenges that can help advance our understanding of effective health care and use organizational agility to create more sustainable health care systems. This chapter provides health care system administrators an alternative design option.