Service Delay Research Articles

Enhancing multi-cloud service deployment with [formula omitted]: A loss-aware coordinator in sky computing

Internet of Things (IoT) services deployed across different Cloud Service Providers (CSPs) require seamless migration across heterogeneous clouds. Sky Computing (SC) facilitates the requirement by implementing a coordinator with communication APIs among clouds. However, security concerns of CSPs prevent the coordinator from accessing detailed cloud hardware information, thereby hindering the assessment of Serving Ability (SA) and exacerbating delays in service delivery. To ensure delay experience, we designed a loss-aware coordinator SkyCap for the multi-CSP collaboration in SC. First, to assess the SA of clouds with available information, we design a loss-aware SA assessment mechanism AdaSA that collects delay experience and Packet Loss Ratio (PLR) information for SA assessment. Since the uncontrollable PLR can increase service delay, we incorporate PLR as a disturbing factor in SA assessment to ensure a more precise evaluation. Second, to maximize the admission profit of the collaboration, we design two approximation algorithms within SkyCap to serve requests. Since the coordinator may deploy services in batches, we design a delay-aware offline algorithm AdaOff to serve requests simultaneously, while ensuring the computing capacity of clouds and the delay requirement of requests. Meanwhile, for asynchronously arriving requests, we design an ability-aware online algorithm AdaOn to serve requests in real-time, while guaranteeing the computing capacity of clouds, SA of clouds, and delay requirement of requests. Finally, extensive theoretical analysis and experimental validation confirm the performance of the coordinator SkyCap. The SA assessment mechanism AdaSA outperforms existing solutions in SA assessment by ensuring at most 1% deviation, especially in high-PLR scenarios. Meanwhile, the algorithm AdaOff exhibits a remarkable 20% improvement over the state-of-the-art in admission profit while ensuring stringent service delay. Concurrently, the algorithm AdaOn surpasses existing solutions, achieving a nearly 10% enhancement in both admission profit and service delay. In summary, the coordinator SkyCap stands out in theoretical groundwork and practical implementation, offering advancements in the SA assessment, admission profit, and service delay.

Road to maternal death: the pooled estimate of maternal near-miss, its primary causes and determinants in Africa: a systematic review and meta-analysis

BackgroundMaternal near-miss (MNM) is defined by the World Health Organization (WHO) working group as a woman who nearly died but survived a life-threatening condition during pregnancy, childbirth, or within 42 days of termination of pregnancy due to getting quality of care or by chance. Despite the importance of the near-miss concept in enhancing quality of care and maternal health, evidence regarding the prevalence of MNM, its primary causes and its determinants in Africa is sparse; hence, this study aimed to address these gaps.MethodsA systematic review and meta-analysis of studies published up to October 31, 2023, was conducted. Electronic databases (PubMed/Medline, Scopus, Web of Science, and Directory of Open Access Journals), Google, and Google Scholar were used to search for relevant studies. Studies from any African country that reported the magnitude and/or determinants of MNM using WHO criteria were included. The data were extracted using a Microsoft Excel 2013 spreadsheet and analysed by STATA version 16. Pooled estimates were performed using a random-effects model with the DerSimonian Laired method. The I2 test was used to analyze the heterogeneity of the included studies.ResultsSixty-five studies with 968,555 participants were included. The weighted pooled prevalence of MNM in Africa was 73.64/1000 live births (95% CI: 69.17, 78.11). A high prevalence was found in the Eastern and Western African regions: 114.81/1000 live births (95% CI: 104.94, 123.59) and 78.34/1000 live births (95% CI: 67.23, 89.46), respectively. Severe postpartum hemorrhage and severe hypertension were the leading causes of MNM, accounting for 36.15% (95% CI: 31.32, 40.99) and 27.2% (95% CI: 23.95, 31.09), respectively. Being a rural resident, having a low monthly income, long distance to a health facility, not attending formal education, not receiving ANC, experiencing delays in health service, having a previous history of caesarean section, and having pre-existing medical conditions were found to increase the risk of MNM.ConclusionThe pooled prevalence of MNM was high in Africa, especially in the eastern and western regions. There were significant variations in the prevalence of MNM across regions and study periods. Strengthening universal access to education and maternal health services, working together to tackle all three delays through community education and awareness campaigns, improving access to transportation and road infrastructure, and improving the quality of care provided at service delivery points are key to reducing MNM, ultimately improving and ensuring maternal health equity.

Penerapan Jaminan Asuransi Kesehatan terhadap Perlindungan Pegawai Negeri Sipil (PNS)

Study aims to determine the implementation of health insurance carried out by BPJS Kesehatan, and can be used as a consideration in formulating and designing policies for implementing health insurance for Civil Servants (PNS) and also to find out the obstacles faced by BPJS Kesehatan Langkat Branch. The type of research used is descriptive qualitative research. The conclusions of this study in brief are: (1) The implementation of health insurance at the Langkat Branch of Health BPJS is in accordance with the law on state civil servants that civil servants are entitled to receive pension security, old age security, health insurance, work accident insurance and death security. And the implementation of health insurance for civil servants at BPJS Kesehatan Langkat Branch is in accordance with Law No. 24 of 2011, which stipulates that BPJS Kesehatan functions to organize a health insurance program with the aim of ensuring that participants receive health care benefits and protection in meeting basic health needs. (2) Obstacles found in the Langkat Branch of BPJS Health are delays in service to participants, health facilities obtained are not in accordance with the fees paid, lack of participant data collection. The solution to the obstacles in the Langkat Branch Health BPJS needs to be improved in the service system because what participants need is fast, accurate service and can provide convenience in participant administration.
 Keywords: Insurance, Health Insurance, Civil Servants, Services, Protection.

A Study on Decision-Making for Improving Service Efficiency in Hospitals

The provision of efficient healthcare services is essential, driven by the increasing demand for healthcare resources and the need to optimize hospital operations. In this context, the motivation to innovate and improve services while addressing urgent concerns is critical. Hospitals face challenges in managing internal dispatch services efficiently. Outsourcing such services can alleviate the burden on hospital staff, reduce costs, and introduce professional expertise. However, the pressing motivation lies in enhancing service quality, minimizing costs, and exploring innovative approaches. With the rising demand for healthcare services, there is an immediate need to streamline hospital operations. Delays in internal transportation services can have far-reaching implications for patient care, necessitating a prompt and effective solution. Drawing upon dispatch data from a healthcare center in Taiwan, this study constructed a decision-making model to optimize the allocation of hospital service resources. Employing simulation techniques, we closely examine how hospital services are currently organized and how they work. In our research, we utilized dispatch data gathered from a healthcare center in Taichung, Taiwan, spanning from January 2020 to December 2020. Our findings underscore the potential of an intelligent dispatch strategy combined with deployment restricted to the nearest available workers. Our study demonstrates that for cases requiring urgent attention, delay rates that previously ranged from 5% to 34% can be notably reduced to a much-improved 3% to 18%. However, it is important to recognize that the realm of worker dispatch remains subject to a multifaceted array of influencing factors. It becomes evident that a comprehensive dispatching mechanism must be established as part of a broader drive to enhance the efficiency of hospital service operations.

Quality Improvement Report: Improving Retrieval Time for CT Supplies by Using 5S.

The CT supply room is a critical resource in the imaging workflow. However, the supply room for the two CT scanners at our cancer center, one of which is used for our busy interventional service, was disorganized, and the time spent searching for the appropriate equipment could potentially lead to delays in service and contribute to patient safety risks. The purpose of this project was to reduce the time to find supplies and to increase the satisfaction of CT technologists and medical providers by reorganizing and clearly labeling supplies using "lean" principles. A multidisciplinary team was assembled to reorganize the CT storage using lean 5S methodology (sort, set in order, shine, standardize, and sustain). Baseline and postintervention analysis of the impact of supply reorganization and labeling was performed using three methods: (a) the time recorded for a supply retrieval scavenger hunt, (b) a spaghetti diagram of participant movement during the scavenger hunt, and (c) satisfaction surveys of radiologists and staff. Seven radiology residents participated in the timed supply retrieval scavenger hunt before and after the intervention. Spaghetti diagrams demonstrated a reduction in redundant foot traffic for supply retrieval after the intervention. There was a 61.7% decrease in the average time to retrieve the 10 items in the scavenger hunt (P < .01). Satisfaction surveys after the intervention had statistically significant positive responses compared with those before the intervention. ©RSNA, 2024.

Service, Interrupted: Analyzing Chat Reference Referrals

ABSTRACT This study examines chat reference interruptions at a public land grant university, focusing primarily on referrals. Since interrupted service is never ideal, how do we best handle these situations, both with the patrons and within and across library departments? Researchers examined chat transcripts and pinpointed transactions that contained interruptions or delays in service. The transcripts with service interruptions were then combed and analyzed to discover which strategies and actions proved most successful, and which library departments or staff members were absorbing most of the referred queries. Findings not only provided evidence and case studies for better reference training and interdepartmental cooperation, but also shed light on the intricacies of referrals. The analysis revealed many paths forward, including creating targeted canned chats, utilizing our findings in reference trainings, and improving communication and cooperation with the most referred-to library department.

Adaptive channel reservation multiple access protocol based on differentiated traffic guarantee

Ad Hoc network is widely used because of its distributed flexibility, in which nodes may generate different types of traffic, and some high-priority traffic requires lower delay and other Quality of service (QoS) requirements. However, as the load of traffic increases, the probability of conflict increases significantly, which makes it difficult to guarantee the requirement of these traffic. It is significant to design the efficient multiple access protocol to ensure the quality of different kinds of traffic. Channel reservation mechanism is an important method to ensure QoS. However, the existing channel reservation mechanism does not fine-adjust reservation parameters according to the QoS when dealing with various traffic differently, and the differentiation mechanism is rough. In addition, it is difficult to ensure the performance of common services when low-latency services are met. Therefore, a differentiated service guarantee adaptive reservation mechanism (DSGARM) to solve the above problems is proposed. The core idea of the protocol is to provide differentiated services in detail according to the delay tolerance requirements of each business. Absolute reservation mechanism is used to guarantee delay-sensitive services, and relative reservation mechanism is used to service relatively delay-insensitive services. In the protocol, a model is established to design an adaptive algorithm to quantitatively calculate reservation parameters that meet the delay requirements. On the premise of prioritized reservation for various services, appropriate reservation parameters can be adjusted according to network conditions to ensure the delay tolerance requirements of each type of service. The present work can be widely applied to scenarios with differentiated business requirements. The simulation results show the advantages of the present protocol and have great practical significance.

Implementation of Good Governance in Improving the Quality of Public Services at the Fatuaruin Village Office, Sasitamean District, Malaka District

This research aims to assess the Application of Good Governance in Enhancing Public Service Quality at the Fatuaruin Village Office, Sasitamean District, Malacca Regency, utilizing descriptive research methods with a qualitative approach. A total of 7 informants were purposively sampled for data collection through observations, interviews, and documentation analysis. The theoretical framework employed is based on the work of Ramdani et al (2022). The findings reveal challenges in the implementation of good governance at the Fatuaruin Village Office. Transparency is compromised, particularly in disseminating information related to business licensing services, leading to public perception that transparency efforts are not fully optimized. Responsiveness falls short as officials are frequently unavailable when needed, causing delays in service. The fairness of services provided is questioned, with instances of unequal treatment and illegal levies. Effectiveness and efficiency are criticized due to slow services that deviate from predetermined standards, resulting in community dissatisfaction with time and cost implications. Several obstacles impede the effective implementation of good governance in the village, including limited resources, insufficient awareness among officials, a lack of community involvement, and instances of corruption and nepotism. Recommendations include optimizing the principles of good governance—transparency, responsiveness, fairness, and efficiency—considering local contexts. This optimization is expected to enhance the quality of services provided, ensuring satisfaction within the community.

Cache Optimization Methods Involving Node and Content Sharding of Blockchain in Internet of Vehicles

Blockchain stands out in addressing the data security requirements of the Internet of Vehicles. However, blockchain has storage pressure that cannot be met by most existing nodes. The emergence of Mobile Edge Computing allows nodes closer to the users to undertake the caching and computation process. Although sharding can alleviate the storage pressure on blockchain nodes, frequent cross-shard communication can affect the overall performance of the blockchain. In this paper, combining the features of traffic flow with strong regional similarity as well as inter-node correlation, we propose two sharding methods based on the current Vehicle–Infrastructure–Clouds three-tier service model. The proposed Content Sharding method can optimize node caching and improve the cache-hitting ratio. The proposed node sharding method can effectively reduce the system service delay by assisting nodes to cache the whole blockchain together across the network.

A service function chain mapping scheme based on functional aggregation in space-air-ground integrated networks

Being a novel network architecture, the Space-air-ground integrated network (SAGIN) offers advantages such as extensive network coverage and seamless ubiquitous access. However, it also encounters the challenge of balancing a growing user demand with limited network service resources. In order to further improve the utilization rate of network resources, a group of virtual network functions can be connected according to certain business logic to form a dynamic reconfigurable service function chain. This can provide diversified and high-quality network services for users. So by aggregating the same type of network function, we can reduce the cost of service chain mapping. Based on the above ideas, this paper proposes an Aggregation of Service Function Chain mapping algorithm (A-SFC). The aggregated service function chain topology is mapped according to an improved isomorphic graph search mapping algorithm, resulting in a deployment solution that minimizes the mapping cost by aggregating static SFC requests by end-system division. Experimental results show that the algorithm is able to find an effective mapping scheme under resource constraints. In addition to reducing computation, the algorithm effectively minimizes the consumption of computational resources while delivering excellent performance in terms of service delay and mapping cost.

Mobility-aware task offloading in MEC with task migration and result caching

Numerous computation-intensive applications have emerged, demanding lower delay and energy consumption. Multi-access Edge Computing (MEC) provides task offloading services for mobile users (MUs) through proximate MUs, effectively minimizing service delay and energy consumption. However, the challenges of supporting MUs’ mobility persist, and ensuring uninterrupted task offloading services from MEC servers still needs to be solved. Additionally, applications like autonomous driving generate repetitive tasks, introducing unnecessary computational overhead. This paper adopts a task migration strategy to tackle these issues, specifically addressing task offloading failure due to MU mobility. Simultaneously, a computation-result cache-assisted technique is leveraged to alleviate the burden of repetitive computation. The objective is to minimize the system cost, which consists of the processing delay and energy consumption of tasks for all MUs. The problem is modeled as an integer linear programming problem, and the optimal solution is meticulously derived. In response to the high computational complexity inherent in obtaining the optimal solution, a low-complexity heuristic algorithm (CMHA) is introduced. Simulation results demonstrate that optimal and heuristic schemes significantly reduce the overall system delay and energy consumption.

MEC Server Sleep Strategy for Energy Efficient Operation of an MEC System

Optimizing the energy consumption of an MEC (Multi-Access Edge Computing) system is a crucial challenge for operation cost reduction and environmental conservation. In this paper, we address an MECS (MEC Server) sleep control problem that aims to reduce the energy consumption of the system while providing users with a reasonable service delay by adjusting the number of active MECSs according to the load imposed on the system. To tackle the problem, we identify two crucial issues that influence the design of an effective sleep control technique and propose methods to address each of these issues. The first issue is accurately predicting the system load. Changes in system load are spatio-temporally correlated among MECSs. By leveraging such correlation information with STGCN (Spatio-Temporal Graph Convolutional Network), we enhance the prediction accuracy of task arrival rates for each MECS. The second issue is rapidly selecting MECSs to sleep when the load distribution over an MEC system is given. The problem of choosing sleep MECS is a combinatorial optimization problem with high time complexity. To address the issue, we employ a genetic algorithm and quickly determine the optimal sleep MECS with the predicted load information for each MECS. Through simulation studies, we verify that compared to the LSTM (Long Short-Term Memory)-based method, our method increases the energy efficiency of an MEC system while providing a compatible service delay.

Computing and Communication Cost-Aware Service Migration Enabled by Transfer Reinforcement Learning for Dynamic Vehicular Edge Computing Networks

Due to the high mobility of vehicles, service migration is inevitable in vehicular edge computing (VEC) networks. Frequent service migrations incur prohibitive migration cost including the computing cost (e.g., increased computing delay) and communication cost (e.g., occupied backhaul bandwidth). Yet existing service migration schemes are usually designed without considering the impact of the computing cost. This paper considers the impact of computing and communication cost jointly, and proposes a computing and communication cost-aware service migration scheme for VEC networks (i.e., CA-migration). Taking the service delay as a QoS metric for VEC networks, this paper formulates a migration optimization problem aiming to maximize the services' satisfaction degree of delay (i.e., the probability that the service delay is smaller than the service delay requirement), where both the communication cost and computing cost affect the services' satisfaction degree. Since the optimization problem is a constrained non-linear integer programming problem, it is difficult to solve. Moreover, the VEC networks are highly dynamic. Thus, a fast transfer reinforcement learning (fast-TRL) method combining transfer learning and reinforcement learning is proposed to provide an adaptive service migration scheme in dynamic VEC networks. Simulation results show that compared with existing schemes, the proposed CA-migration scheme can increase the satisfaction degree by up to 30%, and needs 25% less training time to obtain the optimal service migration policy.

Tensor-Based Lyapunov Deep Neural Networks Offloading Control Strategy with Cloud-Fog-Edge Orchestration

Using DNN (Deep Neural Networks) models to obtain high Quality of Services (QoS) through the cloud has become increasingly popular nowadays. Users want to use DNN by their edges (such as smartphones) anytime and anywhere. For most small and medium-sized enterprises, cloud computing resources are limited. Temporary exhaustion of resources may cause obvious service delay. For users, if all tasks are done locally, the battery capacity of the edge is too small to support such huge computing tasks. To remove this contradiction, we propose a Tensor-based Lyapunov DNN Offloading Control (TLDOC) strategy. First, we offload DNN computational tasks to cloud-fog-edge from an overall perspective. That is, layers in DNN are considered as basic offloadable objects. Second, we provide an original tensor-based Lyapunov equation and the entire process is derived in the tensor space. Lastly, we consider more key limiting factors (e.g., cellular data and remaining edge energy) to achieve better QoS. Via above contributions, our strategy reduces service delay and energy consumption for DNN cloud-fog-edge orchestration. Our experiments include two parts - detail and comparison. The experimental detail verifies that TLDOC strategy is practical and stable. Compared experiments show that our strategy could provide better QoS than existing methods on efficiency and energy saving.

5G Network Performance Optimization Strategies for Smart Grids

Abstract In this paper, a network slice resource allocation algorithm based on delay sensing is proposed for the problems of service delay and QoS reduction, and resource utilization reduction caused by unreasonable network slice resource allocation. MIMO technology is being studied to establish a communication system that supports multiple inputs and outputs for channels. A resource preallocation method for 5G edge computing is proposed by reasonably allocating resources in the 5G edge computing environment. Then, the performance of the 5G network is optimized, and the optimized network performance is analyzed based on case studies. The results show that the buffer depth of the optimized 5G network is reduced by 1.25, the network delay is reduced by 0.02s, and the network throughput is significantly improved. This study provides the theoretical basis and technical support for the further development of a smart grid in a 5G environment.

Digital Twin-Assisted, SFC-Enabled Service Provisioning in Mobile Edge Computing

Mobile Edge Computing (MEC) has been identified as a desirable computing paradigm that provides efficient and effective services for various applications, while meeting stringent service delay requirements. Orthogonal to the MEC computing paradigm, Network Function Virtualization (NFV) technology is another enabling technology that provides the network resource management with great flexibility and scalability, where the instances of Virtual Network Functions (VNFs) are deployed in edge servers as Service Function Chains (SFCs) for SFC-enabled services. Although reliable service provisioning in MEC environments is fundamentally important, the deployed VNF instances usually are not reliable, which can be affected by their software implementation, their execution duration, the workload among edge servers, and so on. Empowered by digital twin techniques, the states of VNF instances can be maintained by their digital twins in a real-time manner and their reliability can be accurately predicted through their digital twins. In this paper, we study digital twin-assisted, SFC-enabled reliable service provisioning in MEC networks by exploiting the dynamics of VNF instance reliability. We concentrate on two novel optimization problems of reliable service provisioning: the service cost minimization problem, and the dynamic service admission maximization problem. We first show their NP-hardness. We then formulate an Integer Linear Program (ILP) solution, and devise an approximation algorithm with a constant approximation ratio for the service cost minimization problem. We thirdly provide an ILP solution to the offline version of the dynamic service admission maximization problem. Built upon this offline ILP solution, we also develop an online algorithm with a provable competitive ratio for the problem, by adopting the primal-dual dynamic updating technique. We finally evaluate the performance of the proposed algorithms via simulations. Simulation results demonstrate that the proposed algorithms outperform their comparison benchmarks, and improve the performance of their comparison counterparts by no less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10.2 \%$</tex-math></inline-formula> .

Profile and Operations of Highway Tourist Stop-over Foodservice Establishments in Uganda

ABSTRACT This study was set out to identify and document the highway tourist stop-over foodservice establishments (HTSFE) characteristics; thus, creating a profile and grading for informed choice by tourists. The study adopted a cross-sectional design and quantitative data was collected from managers of establishments. The questionnaire was interviewer- administered in addition to an observational check-list. The study involved 30 HTSFE identified with the assistance from Uganda Tourism Board (UTB) and Uganda Safari Guides Association (USAGA). The response rate was 100%. Most of HTSFE were located in Western (47.6%) and Eastern Uganda (36.7%). Some were either stand-alone restaurants (40%) or part of a bigger hotel (43%). A considerable number (30%) employed between 1-5 food handlers and most (63.3%) had operated for more than 10 years. Majority (58.6%) were inspected by UTB in addition to either local council or city council. The commonest complaint recorded was delay in service (73.7%). The dishes prepared included local dishes (90%) and international cuisines (66.7%). Most HTSFE used water from National Water and Sewerage corporation (79.3%). None of the HTSFE had a food safety management system. The HTSFE belonged to three grade categories: B (36.6%), C (30%) and Non-graded (33.3%). The findings of the study suggest the need for implementing food safety management systems and more regular inspections and trainings for food safety assurance.

MASALAH PELAYANAN PUBLIK BIDANG PENDIDIKAN DI ERA DIGITAL PERSPEKTIF KOMUNIKASI (STUDI KASUS DINAS PENDIDIKAN KOTA PADANG)

Public services in general have problems in their service to the community, such as: are protracted delays in service, abuse of authority, irregularities in procedures, not providing services, asking for money for services, incompetence, taking sides, discrimination, conflict interests and others. Digitalization of education is one form of transformation of public services at education field. Viewed from a communication perspective, digitalization of education is a form of improvement public services from the media elements, which influence other communication elements such as communicators, message, communication and of course the effect. This research aims to describe communication problems in public servants digitalizing education. This research uses a descriptive qualitative approach,using interview techniques and non-participant observation as data collection techniques. The result. However, from a communication perspective, these problems can be broken down into communicator problems and communication. Communicators who have insufficient knowledge of school digitalization, a mindset that is slow to accept change. Meanwhile, from the communicator's perspective, there are problems of poor communication skills, unsupportive attitudes from communicants, Insufficient knowledge of the program and technology, values and culture that hinder the process the communication.

Better, Connected Care: integrated services reform in Victoria, Australia

Better, Connected Care is a whole of government reform currently underway in the Australian state of Victoria. It is focussed on improving service delivery for people with multiple and complex needs who need support from multiple service systems. Better, Connected Care (BCC) is about joining up services, putting the person at the centre and considering their needs across all stages of their life.&#x0D; The reform vision is: better connected care and services for people with multiple needs, supported by stronger partnerships and earlier intervention, to achieve improved client outcomes and reduce demand on acute services.&#x0D; The problem that Better, Connected Care seeks to address:&#x0D; Over the past decade, pressure on the provision social services has increased. There is a growing number of Victorians who have been in contact with multiple services funded or provided by a variety of Victorian government departments, including human services, housing, health and justice. Demand across the service system has soared, as evidenced by a 26% increase in child protection placements and a 25% increase in family violence incidents since 2016. In the same period, there has been a 13% increase in people accessing homelessness services, with a 21% increase in mental health related presentations to emergency departments since 2015 and a 25% increase in incarceration rates since 2011.&#x0D; Accessing multiple services can be difficult for people, particularly those with multiple needs. This service system fragmentation can cause frustration for the person as they are often required to undertake multiple assessments, re-tell their story, leave services due to age requirements and sever relationships with trusted workers, and be required to fit into existing service models. From a person-centred perspective, BCC aims to address the barriers many people experience as they navigate access to multiple services across a range of programs and organisations.&#x0D; From a system perspective, the boundaries between services can cause service delays or prevent people from accessing the services they need. In the absence of an integrated joined up approach, people with multiple needs may not be adequately supported, which can result in increasingly complex needs, making it harder to achieve positive outcomes. In addition, service models can be narrow and are sometimes not able to provide the range of services a person or their family might need, such as housing, mental health and drug and alcohol service support. A more joined-up service system that can respond to people earlier and more holistically can help overcome these challenges.&#x0D; &#x0D; The Better, Connected Care approach:&#x0D; BCC is building on the successes of joined up care for specific cohorts, such as the Multiple and Complex Needs Initiative and the Orange Door services for Family Violence, and expanding these to the whole service system for health, justice and social services. BCC activities will address a range of system barriers that exist between services – like improving information sharing practices, considering more flexible and portable funding approaches, building capacity and capability in joined up responses, streamlining assessments and trialling service delivery models with increased levels of integration."

A secure and lightweight container migration technique in cloud computing

The present research has found that container virtualization systems are more effective and more straightforward to handle in contrast to traditional virtualization systems. The live migration processes can be substantially reduced by using lightweight containers developed on virtualization techniques. It shrinks the suspension of service by transmitting minimum memory of the source without stopping the migration process. Therefore, transferring many memory pages leads to long migration time and downtime, which affects the performance of containerized applications and cost is a major concern. In this paper, the pre-copy container live migration is analyzed in a detailed manner to trace out the possibilities to improve the performance in various applications and introduce a probability-based migration technique to overcome the memory transmission limitations. For continual learning, we used containers to run and manage the AI-based system on the cloud to overcome the delay in service during migration. The pre-dump is the first phase of sending the container file system to the destination host. Additionally, dirty pages are predicted during a migration process using the Meta-Heuristic approach. After that, the active set of pages and their update rate have also been identified. In addition, based on the threshold level of the maximum update rate, the pages have been shortlisted to be discarded from pre-dump. The proposed technique is implemented and tested on different scenarios, and results show that it reduces the size of the pre-dump by 26.48% compared to the traditional pre-copy migration technique, which leads to less downtime for cloud services. The results reveal that the suggested technique surpasses existing alternatives in overall migration time and amount of data transmitted. There is 31.04% reduction in the amount of data transferred during the iterative phase.