Failover Mechanism Research Articles

Securing and Managing Cloud Databases for Business - Critical Applications

Mission-critical applications demand robust and reliable database management. This paper examines key strategies for Database Administrators (DBAs) managing these applications in the cloud. We discuss critical aspects such as performance optimization through sharding, replication, and read replicas. We also explore strategies for ensuring high availability and disaster recovery, including leveraging cloud-native services like autoscaling and failover mechanisms. Furthermore, we delve into critical security considerations, including data encryption, access control, and threat detection. Finally, we analyze best practices for optimizing cloud database costs while maintaining performance and reliability. This Paper explores as cloud-based infrastructures continue to change, a deep understanding of the differences between SQL databases, such as MySQL, SQL Server, RedShift, PostgreSQL, and Oracle, and NoSQL solutions, such as MongoDB, Cassandra, and DynamoDB, a prerequisite to design to manage systems

System Integration Failures and Their Impact on Patient Safety in Critical Care Settings

Robotic surgery systems offer precision and minimally invasive procedures, enhancing surgical outcomes in critical care settings. However, these systems' complexity, with integrated hardware and software, can lead to integration failures, compromising patient safety. This paper examines the system integration challenges in robotic surgery, explores their effects on patient safety, and suggests solutions to overcome them. Rigorous testing strategies during development and continuous monitoring of system performance are crucial in detecting failures early and ensuring reliable system operation. Keywords: Robotic Surgery Systems, System Integration, Patient Safety, Software Failures, Hardware Failures, Critical Care, Integration Testing, Failover Mechanisms, Robotic Arms, Sensor Calibration, Real-Time Data Processing, Medical Robotics, Surgical Precision, Failure Detection, Stress Testing, Fault-Tolerant Design, Error Handling, Modular Design, Quality Assurance, ISO 13485, Robotic Surgery Failures, Calibration Errors, Mako System, Da Vinci Surgical System, CyberKnife System, Automated Testing, Robotic Surgery Technology.

Fault Tolerance Management Implementation from Medium-to-Large-Scale Networks

As network infrastructures grow in complexity, ensuring high availability and resilience becomes critical, especially for medium-to-large scale networks. This study focuses on the development and implementation of fault tolerance management within Software-defined networking (SDN) environments, aimed at minimizing downtime and enhancing network reliability. SDN’s centralized control and dynamic programmability provide an ideal framework for implementing efficient fault detection and recovery mechanisms. The proposed model leverages real-time monitoring, redundancy protocols, and adaptive rerouting strategies to mitigate the impact of node or link failures. Key components of the model include failover mechanisms, load balancing, and traffic rerouting algorithms, designed to maintain seamless network operations during failures. Through simulation and testing, the model demonstrates significant improvements in network resilience, reducing recovery time and ensuring uninterrupted service delivery. This research provides a comprehensive guide to implementing fault-tolerant networks using SDN, offering scalable solutions that can be adapted to various network sizes and configurations. The findings emphasize the potential of SDN to revolutionize fault management in modern network infrastructures, making it a crucial consideration for future network design and operations.

Advancements in AI-Driven Disaster Recovery: Predictive Failure Detection and Automated Data Protection

This article explores the transformative impact of artificial intelligence (AI) on disaster recovery systems in information technology. It examines how AI-driven solutions are revolutionizing traditional approaches to data protection and business continuity through advanced predictive analytics, automated backup mechanisms, and intelligent recovery processes. The research highlights the significant improvements achieved in recovery times, with some implementations reporting up to 60% faster recovery compared to conventional methods. Key aspects discussed include AI-powered predictive failure detection, automated data backup mechanisms, and the acceleration of recovery times. The article also delves into the enhancement of data availability through AI-driven replication strategies and intelligent failover mechanisms, emphasizing their critical role in maintaining operational resilience. Additionally, it addresses the challenges and considerations in implementing these advanced systems, including integration with existing infrastructure and the necessary adaptation of IT personnel. The article concludes by exploring future directions in AI algorithms for disaster recovery, potential integrations with cloud-based solutions, and the broader applications of these technologies across various industries. This comprehensive analysis underscores the pivotal role of AI in shaping the future of disaster recovery and business continuity strategies in an increasingly digital world.

Implementation of High Availability Based on Load Balancing and Failover Method in E-commerce Using MySQL Database

The rapid growth of e-commerce has brought about challenges in managing traffic loads and ensuring the availability of database servers. One critical issue is what happens when the main database server fails, potentially leading to downtime or data loss. This research aims to address these problems by optimizing server resource distribution and implementing data replication across multiple database servers. The goal is to enhance system efficiency, prevent server overloads, ensure data availability, and minimize downtime or data loss when server failures occur.This research utilizes a multi-stage methodology. First, data collection was conducted to gather relevant information. In the second stage, a needs analysis was performed to identify system requirements. The third stage involved designing the system architecture, including the creation of entity-relationship diagrams (ERD), flowcharts, and network topologies. In the final stage, the system was implemented through database replication and the application of failover methods.The results demonstrate that the failover mechanism operates effectively, ensuring that data is successfully replicated across all database servers. This confirms that the system achieves high availability and minimizes the risk of data loss or service downtime. The implications of this research provide a reliable solution for improving the resilience and performance of e-commerce systems, particularly in managing database server failures.

Comprehensive data security and compliance framework for SMEs

Small and Medium-sized Enterprises (SMEs) are increasingly relying on cloud platforms to support critical business operations, making effective disaster recovery (DR) strategies essential for ensuring business continuity. This review proposes a robust disaster recovery framework tailored for SMEs, designed to minimize downtime and data loss in the event of a system failure, cyberattack, or natural disaster. The framework integrates advanced cloud technologies to create a cost-effective, scalable solution that aligns with the resource constraints of SMEs while providing enterprise-grade resilience. Key components of the disaster recovery framework include cloud-based data replication, automated backup solutions, and geo-redundant storage to ensure that data is continuously available and recoverable. This model employs real-time data synchronization and incremental backups to minimize Recovery Point Objectives (RPO), ensuring that critical data is not lost during an unexpected outage. Additionally, the framework leverages automated failover mechanisms to achieve low Recovery Time Objectives (RTO), allowing businesses to restore operations quickly after an interruption. Cloud orchestration tools such as AWS Elastic Disaster Recovery or Azure Site Recovery are utilized to automate disaster recovery processes, reducing manual intervention and improving the speed of recovery. The framework also incorporates regular testing of disaster recovery plans, using simulation tools to identify weaknesses and optimize response times. For SMEs, cost-effectiveness and ease of management are crucial. The framework emphasizes a pay-as-you-go model for cloud resources, allowing businesses to scale their disaster recovery solutions as they grow without incurring excessive upfront costs. By providing continuous monitoring and proactive threat detection, this disaster recovery framework ensures that SMEs can maintain uninterrupted business operations on cloud platforms, thereby enhancing resilience and mitigating the financial and operational risks associated with data loss and system downtime.

Openflow groups based fast failover mechanism for software defined networks

Openflow groups based fast failover mechanism for software defined networks

Dataplane-Based Fast Failover in SDN-Enabled Wide Area Measurement System of Smart Grid

In the wide area measurement system (WAMS) of smart grid, the real-time monitoring and protection applications have stringent requirements for the end-to-end transmission delays between PMUs and PDC, and fast failover is required to ensure the communication performance after link failures. In this work, the software-defined network (SDN) technology is utilized to enable datapath failover upon a link failure with a global view of the communication network. Then, a novel dataplane based fast failover (DFF) mechanism is proposed to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">directly</i> re-route the data packet in dataplane without interacting with the SDN controller. Based on the mathematical analysis over the WAMS topology features, the proposed DFF optimizes two procedures of failover: backup path construction, and backup path installation. Using the proposed backup path construction algorithms, the 3-approximate and (1+2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula> )-approximate ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$0&lt; \varepsilon &lt; 1$</tex-math></inline-formula> ) backup paths can be constructed, theoretically guaranteeing the data transmission delays both <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">during</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">after</i> failover. Using the proposed LinkID-based FF group table installation method, the conflict of forwarding rules between original and backup paths can be eliminated, while the storage cost is also optimized. The simulation results on six IEEE benchmark test power systems show that the proposed DFF mechanism could achieve lower data transmission delays during and after failover compared to the existing control plane based and dataplane based failover mechanisms.

A Software-Defined Networking Solution for Interconnecting Network Functions in Service-Based Architectures

Mobile core networks handle critical control functions for delivering services in modern cellular networks. Traditional point-to-point architectures, where network functions are directly connected through standardized interfaces, are being substituted by service-based architectures (SBAs), where core functionalities are finer-grained microservices decoupled from the underlying infrastructure. In this way, network functions and services can be distributed, with scaling and fail-over mechanisms, and can be dynamically deployed, updated, or removed to support slicing. A myriad of network functions can be deployed or removed according to traffic flows, thereby increasing the complexity of connection management. In this context, 3GPP Release 16 defines the service communication proxy (SCP) as a unified communication interface for a set of network functions. In this paper, we propose a novel software-defined networking (SDN)-based solution with the same role for a service mesh architecture where network functions can be deployed anywhere in the infrastructure. We demonstrated its efficiency in comparison with alternative architectures.

GeoRep—Resilient Storage for Wide Area Networks

Embedded systems typically have limited processing and storage capabilities, and may only intermittently be powered on. After sending an event upstreams with data from its sensors, the system must therefore be able to trust that the data, once acknowledged, is not lost. The purpose of this work is to propose a novel solution for replicating data between the upstreams nodes in such systems, with a minimal effect on the software architecture. Based on the assumption that there would be no relative order between replicated data tuples, we designed a new replication protocol which uses only 2 communication steps per data tuple, instead of between 3 and 12 used by other solutions. We verified its failover mechanism in a proof-of-concept implementation of the protocol using simulated network failures, and evaluated the implementation on throughput and latency in several controlled experiments using up to 7 nodes in up to 5 geographically separated areas, with up to 1000 data producers per node. The recorded system throughput increased linearly relative to both the number of nodes and the number of data producers. For comparison, with 3 nodes Paxos showed a similar performance as our protocol, but it instead got slower when nodes were added. The lack of a relative order, in combination with partial replication, enables our system to continue working during network partitions, not only in the part containing the majority of the nodes, but also in any sufficiently large minority partitions.

Frisbee: automated testing of Cloud-native applications in Kubernetes

As more and more companies are migrating (or planning to migrate) from on-premise to Cloud, their focus is to find anomalies and deficits as early as possible in the development life cycle. We propose Frisbee, a declarative language and associated runtime components for testing cloud-native applications on top of Kubernetes. Given a template describing the system under test and a workflow describing the experiment, Frisbee automatically interfaces with Kubernetes to deploy the necessary software in containers, launch needed sidecars, execute the workflow steps, and perform automated checks for deviation from expected behavior. We evaluate Frisbee through a series of tests, to demonstrate its role in designing, and evaluating cloud-native applications; Frisbee helps in testing uncertainties at the level of application (e.g., dynamically changing request patterns), infrastructure (e.g., crashes, network partitions), and deployment (e.g., saturation points). Our findings have strong implications for the design, deployment, and evaluation of cloud applications. The most prominent is that: erroneous benchmark outputs can cause an apparent performance improvement, automated failover mechanisms may require interoperability with clients, and that a proper placement policy should also account for the clock frequency, not only the number of cores.

Performability Evaluation of Load Balancing and Fail-over Strategies for Medical Information Systems with Edge/Fog Computing Using Stochastic Reward Nets.

The aggressive waves of ongoing world-wide virus pandemics urge us to conduct further studies on the performability of local computing infrastructures at hospitals/medical centers to provide a high level of assurance and trustworthiness of medical services and treatment to patients, and to help diminish the burden and chaos of medical management and operations. Previous studies contributed tremendous progress on the dependability quantification of existing computing paradigms (e.g., cloud, grid computing) at remote data centers, while a few works investigated the performance of provided medical services under the constraints of operational availability of devices and systems at local medical centers. Therefore, it is critical to rapidly develop appropriate models to quantify the operational metrics of medical services provided and sustained by medical information systems (MIS) even before practical implementation. In this paper, we propose a comprehensive performability SRN model of an edge/fog based MIS for the performability quantification of medical data transaction and services in local hospitals or medical centers. The model elaborates different failure modes of fog nodes and their VMs under the implementation of fail-over mechanisms. Sophisticated behaviors and dependencies between the performance and availability of data transactions are elaborated in a comprehensive manner when adopting three main load-balancing techniques including: (i) probability-based, (ii) random-based and (iii) shortest queue-based approaches for medical data distribution from edge to fog layers along with/without fail-over mechanisms in the cases of component failures at two levels of fog nodes and fog virtual machines (VMs). Different performability metrics of interest are analyzed including (i) recover token rate, (ii) mean response time, (iii) drop probability, (iv) throughput, (v) queue utilization of network devices and fog nodes to assimilate the impact of load-balancing techniques and fail-over mechanisms. Discrete-event simulation results highlight the effectiveness of the combination of these for enhancing the performability of medical services provided by an MIS. Particularly, performability metrics of medical service continuity and quality are improved with fail-over mechanisms in the MIS while load balancing techniques help to enhance system performance metrics. The implementation of both load balancing techniques along with fail-over mechanisms provide better performability metrics compared to the separate cases. The harmony of the integrated strategies eventually provides the trustworthiness of medical services at a high level of performability. This study can help improve the design of MIS systems integrated with different load-balancing techniques and fail-over mechanisms to maintain continuous performance under the availability constraints of medical services with heavy computing workloads in local hospitals/medical centers, to combat with new waves of virus pandemics.

Crafting optimal and resilient iBGP-IP/MPLS overlays for transit backbone networks

The Internet is a collection of interconnected Autonomous Systems (ASes) that use the Border Gateway Protocol (BGP) to exchange reachability information. In this regard, BGP stability and scalability in the inter-domain scope have been matters of major concern for many years, and network engineers have been applying several techniques to cope with these issues. BGP is also used intra-domain (internal BGP - iBGP), to disseminate reachability information inside each AS, and works together with the Interior Gateway Protocols (IGPs) such as OSPF or IS-IS, to build routing tables. Route reflection is a widely adopted technique to tackle BGP scalability in the intra-domain scope, and choosing which routers will play the reflector role and which BGP sessions will be established among reflectors and clients (i.e. the routers which are not elected as reflectors), building an overlay of iBGP sessions, is known as the iBGP overlay design problem. The design of an optimal iBGP overlay is known to be a NP-Hard problem, and we proposed solutions for pure IP networks (i.e. best effort traffic forwarding) in our previous work. However, most Internet providers implement their backbones by combining IP routing with MPLS (Multiprotocol Label Switching) for QoS-aware traffic forwarding. MPLS forwarding incorporates traffic engineering and more efficient failover mechanisms; under this traffic forwarding paradigm, the design of traffic-engineered Label Switched Paths (LSPs, also referred as MPLS tunnels) shall be combined with the aforementioned iBGP overlay design. The present work introduces a coordinated design of both the iBGP overlay and the IP/MPLS substrates. Our contribution is the proposal of an optimal and resilient topology design for an IP/MPLS Internet backbone, which takes advantage of traffic engineering features to optimize the demands, while guaranteeing iBGP overlay optimality. We present a complete solution for a real world scenario, and we study the scalability of the solution for synthetic topologies, achieving encouraging results.

PENERAPAN METODE PER CONNECTION CLASSIFIER (PCC) PADA PERANCANGAN LOAD BALANCING DENGAN ROUTER MIKROTIK

The NOC (Network Operation Center) Division is highly dependent on the availability of internet access in carrying out its duties to monitor and maintain the network remotely. Therefore, the absence of adequate internet access will determine the performance of the work performed by the NOC division. However, problems often occur on computer networks or the internet that can hinder the work done by the NOC division, these problems include, such as the process of uploading or downloading files from the server feeling slow, unable to send emails smoothly, connections often experiencing time-out, There is a long network downtime, as well as traffic congestion on the network which can reduce network reliability. To solve this problem, one solution that can be done is to implement load balancing and failover mechanisms on the network using a MikroTik router. This study aims to design a load balancing scheme using the per connection classifier (PCC) method to overcome traffic congestion problems on the network. The research was conducted using field research methods using observation and interview techniques which were conducted from August to December 2020. The results showed that the application of the load balance technique on the xMikrotik router with the PCC (Per Connection Classifier) method can separate the internet connection through the two available ISP lines so that it can solve the problem of traffic buildup on one of the ISP links to reduce latency and improve existing network performance.

REINFORCE: Achieving Efficient Failure Resiliency for Network Function Virtualization-Based Services

Ensuring high availability (HA) for software-based networks is a critical design feature that will help the adoption of software-based network functions (NFs) in production networks. It is important for NFs to avoid outages and maintain mission-critical operations. However, HA support for NFs on the critical data path can result in unacceptable performance degradation. We present REINFORCE, an integrated framework to support efficient resiliency for NF service chains. REINFORCE includes timely failure detection and consistent failover mechanisms. REINFORCE replicates state to standby NFs (local and remote) while enforcing correctness. It minimizes the number of state transfers by exploiting the concept of external synchrony, and leverages opportunistic batching and multi-buffering to optimize performance. Experimental results show that, even at line-rate packet processing (10 Gbps), REINFORCE achieves chain-level failover across servers in a LAN within 10ms, incurring less than 10% performance overhead, and adds average latency only ~400 μs, with a worst-case latency of less than 1ms. REINFORCE also recovers from software failures within the same node in less than 100 μs, incurring less than 1% performance overhead and adds less than 5 μs latency during normal operation.

A New Adaptive Prioritization and Fail-Over Mechanism for Ring Network Adapter

This paper presents a new adaptive prioritization and fail-over mechanism for ring network adapters (RNA). Owing to the use of a shared medium in the structure of ring networks, management of network resources is very important and cannot completely be fulfilled by fixed priority strategies. An adaptive prioritization mechanism for efficient utilization of network resources is proposed in this paper. Hop-Count and the distance between source and destination are the key parameters that are included in the priority assignment procedure. Unlike the conventional ones, the arrived traffic is not put blindly into the queues thanks to the awareness of stations form status of each other. The newly introduced fail-over mechanism is based on the Power over Ethernet concept. Each station monitors the heartbeat of its neighbors and tries to keep them alive by providing their minimum required electrical power whenever a fault occurs. By doing so, not only single failure but also any successive double failure scenarios cannot disrupt data path continuity. Several simulations are carried out to assess the behavior and performance of the proposed methods in OPNET Modeler. Moreover, a high-speed USB test board is designed using Xilinx-Spartan6-lx9 FPGA to experimentally verify the performance of the proposed mechanisms.

Comparation of distributed cache and centralized cache on web proxy

Caching is an object storage mechanism from a web page that has been accessed. With caching, bandwidth usage will be more efficient and the time to access a web page is getting faster. In caching there are 2 techniques used, namely centralized cache and distributed cache. The purpose of this study is to build a distributed cache system that supports Availability, Reliability, and Scalability. This system will overcome various problems found in the centralized cache, such as single point of failure, unreliable, and not scalable. With the availability of Availability, the system will avoid the problem of single point of failure by implementing a failover mechanism. For the Reliability system will still hold (reliable) accept requests from users, because some proxy servers (parent proxy) will serve requests from users. For Scalability, the system can add proxy servers easily and quickly. To develop the system, the developer takes several approaches such as basic learning about proxy servers and related theories. Next is an analysis to build a system that supports Availability, Reliability, and Scalability. Then the analysis phase is implementedand testing of the system is built. Tests carried out are testing centralized cache systems and testing distributed cache systems. The test results will then be compared to see the performance comparison between centralized cache and distributed cache.

Proactive Failure Recovery for NFV in Distributed Edge Computing

Deploying NFV technologies to the edge networks has attracted growing attention in the stateof- the-art studies. In this article, we first review the most recent work on the topic of applying NFV to edge networks. Then, we identify that an urgent research challenge is to provide proactive failure recovery (shorten as failover hereafter) mechanism for the NFV-enabled distributed edge computing. To address this issue, we propose a novel management architecture that supports the proactive failover mechanism while provisioning NFV services in distributed edge computing. Simulation results show that the proposed proactive failover mechanism outperforms the reactive manner significantly in terms of latency spending on failover operations. We hope this article can spur deeper studies on the proactive intelligent resilience mechanism for deploying NFV in distributed edge computing and other related edge intelligence topics.

SAP Failover Setup for HANA Database 1.0 SP12 and SAP ASCS/ERS using Pacemaker Tool

This research paper explores the implementation of a high availability solution for SAP HANA Database 1.0 SP12 and SAP ASCS/ERS (ABAP Central Services/Enqueue Replication Server) using the Pacemaker clustering tool. The study focuses on the architecture, configuration, and best practices for setting up a robust failover mechanism to ensure continuous operation of critical SAP systems. By examining the integration of SAP HANA's system replication capabilities with Pacemaker's cluster management features, this paper provides insights into creating a resilient SAP environment capable of minimizing downtime and maintaining data consistency during failover events.

Gateway Redundancy Using Common Address Redundancy Protocol (CARP)

Gateway redundancy can ensure the network availability and reliability in providing a service. One way is to make a backup system on the gateway. This backup system can be applied to the router so that if a failure occurs on the master router its task and function can be transferred to the slave router. The transition process from master router to slave router is known as failover. Common Address Redundancy Protocol (CARP) is one of the redundancy gateway protocols and provides a failover mechanism on the router. Therefore, this study will analyse the CARP protocol implementation in ensuring the network services availability by measuring parameters of throughput, delay, retransmission, and downtime. The results showed that CARP implementation on the network produced the throughput, delay, and retransmission values of 61.7 Mbps, 0.14 ms, and 1.11% when without the link termination and 18 Mbps, 0.53 ms, and 1.58% when with link termination, while the downtime value is 2.91 seconds. The QoS test results show good quality based on ITU-T.