This work introduces an autonomic prospective on managing the fault tolerance which ensure scalability, reliability and availability. HAProxy has been used to provide scaling to the web servers for load balancing in proactive manner. It also monitors the web servers for fault prevention at the user level. Our framework works with autonomic mirroring and load balancing of data in database servers using MySQL master- master replication and Nginx respectively.
Here nginx is used to balance the load among the database servers. It shifts the request to the appropriate DB server. Administrator keeps an eye on working of servers through Nagios tool 24X7 monitoring can’t be done manually by the service provider. The proposed work has been implemented in the cloud virtualization environment. Experimental results show that our framework can deal with fault tolerance very effectively.
Cloud based systems are more popular in today’s world but fault tolerance in cloud is a gigantic challenge, as it affects the reliability and availability for the end users. A number of tools have been deployed to minimize the impact of faults. A fault tolerable system ensures to perform continuous operation and produce correct results even after the failure of components up to some extent. More over huge amount of data in the cloud cannot monitor manually by the administrator. Automated tools, dynamic deploying of more servers are the basic requirements of the today’s cloud system in order to handle unexpected traffic spikes in the network.
Table of Contents
1. INTRODUCTION
1.1. Cloud Computing Evolution
1.2. Introduction to Cloud Computing
1.3. Characteristics of Cloud Computing
1.4. Cloud Computing Services
1.4.1. Software as a Service (SAAS)
1.4.2. Platform as a Service (PAAS)
1.4.3. Infrastructure as a Service (IAAS)
1.5. Deployment Models of Cloud Computing
1.5.1. Public cloud
1.5.2. Private Cloud
1.5.3. Community Cloud
1.5.4. Hybrid Cloud
1.6. Layered Architecture of Cloud Computing
1.7. Research Issues in Cloud Computing
1.8. Virtualization
1.8.1. Overview of X86 Virtualization
1.8.2. CPU Virtualization
1.9. Introduction to Fault Tolerance
1.9.1. Importance of Fault Tolerance in Cloud Environment
1.9.2. Management of Fault tolerance
1.9.3. Fault Tolerance Techniques
1.10. Structure of Thesis
2. LITERATURE SURVEY
3. PRESENT WORK
3.1. Problem Definition
3.2. Objectives
3.3. Framework Design
3.3.1 Vmware Workstation
3.3.2 Ubuntu
3.3.3 Haproxy
3.3.4 Docker
3.3.5 Servlet Application
3.3.6 Nginx
3.3.7 MySQL Database
3.3.8 Nagios
3.4. Interaction Diagram
3.5. Implementation of the Framework
4. RESULTS AND DISCUSSION
5. CONCLUSIONS AND FUTURE SCOPE
Objectives & Core Themes
This thesis addresses the critical challenge of fault tolerance in cloud computing environments. The primary research objective is to develop an autonomic framework that manages and recovers from faults proactively, thereby ensuring high scalability, reliability, and continuous service availability for end users.
- Proactive fault detection and automated load balancing
- System-level and OS-level virtualization for high availability
- Master-master database replication for data consistency
- Automated 24/7 infrastructure monitoring
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3.1. Problem Definition
Existing literature covers distributed architectures to cover fault tolerance which inherently covers data transmission delay and communication response. Detecting fault and replicating entire system image is typically a hard job to achieve. However, the replication can be performed but with much delay. On the other side client has to wait tremendous amount of time so recovery still possible but with large response time. Our research focus on similar kind of replication techniques based upon mirror cloning in single standalone system where proactive measures has been deployed to check system performance degradation. The level of degradation just before unresponsive behaviour of system state is detected and the present workload is spread out to the scaled system deployed. Although number of concurrent request are scheduled according to the efficiency of the current intended systems. The Figure 3.1 shows the traditional approach used for the data transmission.
The Problem is to tolerate the fault if any of the servers goes down.
(i) For this, there is need to insert the large number of web servers and DB servers.
(ii) To shift the load on secondary servers if the primary one fails.
Summary of Chapters
INTRODUCTION: Provides an overview of cloud computing evolution, service models, deployment architectures, and the fundamental challenges regarding fault tolerance and virtualization.
LITERATURE SURVEY: Reviews existing research on virtual machine migration, fault tolerance mechanisms, and security strategies, identifying gaps in current distributed fault management.
PRESENT WORK: Details the problem statement and the proposed autonomic framework design, including tools like HAProxy, Nginx, Docker, and Nagios to achieve system-level fault tolerance.
RESULTS AND DISCUSSION: Evaluates the experimental prototype, demonstrating how the proposed framework effectively manages load and maintains service availability during simulated server failures.
CONCLUSIONS AND FUTURE SCOPE: Summarizes the effectiveness of the implemented framework in enhancing system reliability and suggests future improvements such as incorporating database locks and more advanced virtualization techniques.
Keywords
Cloud Computing, Fault Tolerance, Load Balancing, Virtualization, HAProxy, Nginx, Docker, MySQL Replication, Autonomic Management, High Availability, System Monitoring, Nagios, Distributed Systems, Proactive Fault Recovery, Middleware
Frequently Asked Questions
What is the core focus of this research?
The research focuses on implementing an autonomic, fault-tolerant framework for cloud computing environments to ensure system reliability and availability.
What are the primary technical themes of the work?
The core themes include proactive fault tolerance, virtualization (OS and system level), load balancing, and automated server monitoring.
What is the central research question?
The primary goal is to address how to effectively detect and manage server faults proactively to ensure that cloud-based applications remain operational without significant latency or data loss.
Which scientific methodology is applied?
The methodology involves the design and implementation of a layered framework, utilizing load-balancing software (HAProxy, Nginx) and replication techniques within a virtualized (VMware, Docker) cloud environment.
What does the main body of the work cover?
The main body describes the problem definition, the design of the autonomic framework, the specific tools used (VMware, Ubuntu, Haproxy, Docker, Nginx, MySQL, Nagios), and the implementation details, followed by experimental results and performance analysis.
How is the work characterized by its keywords?
The work is characterized by its emphasis on fault tolerance, virtualization techniques, and automated monitoring, reflecting a modern approach to maintaining high availability in distributed systems.
How does the framework handle server failures?
The framework utilizes HAProxy to distribute requests based on server priority and redirects traffic to healthy nodes if a web server fails, while Nginx handles load balancing and failure redirection for database servers.
What role does database replication play in the system?
Master-master MySQL replication is implemented to maintain mirror copies of data across database servers, ensuring data redundancy and high availability even if a database node fails.
Why is Nagios integrated into the system?
Nagios is used for automated, 24/7 monitoring of server status. It provides real-time alerts via email and SMS, allowing administrators to identify and respond to discrepancies immediately.
- Arbeit zitieren
- Ashima Garg (Autor:in), Sachin Bagga (Autor:in), 2015, Autonomic approach for fault tolerance using scaling, replication and monitoring of servers in cloud computing, München, GRIN Verlag, https://www.grin.com/document/336348
