Aspect-Oriented Programing Techniques to support Distribution, Fault Tolerance, and Load Balancing in the CORBA-LC Component Model

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.

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Factors Affecting Fault Tolerance during Load Balancing in Cloud Computing

Turkish Journal of Computer and Mathematics Education (TURCOMAT) ◽

10.17762/turcomat.v12i11.6079 ◽

2021 ◽

Vol 12 (11) ◽

pp. 1523-1533

Author(s):

Bidush Kumar Sahoo , Et. al.

Keyword(s):

Cloud Computing ◽

Fault Tolerance ◽

Load Balancing ◽

South India ◽

Analysis Tool ◽

Factors Affecting ◽

Software Firms ◽

Statistical Analysis Tool ◽

Cost Efficient ◽

Support Cost

Cloud computing is built upon the advancement of virtualization and distributed computing to support cost-efficient usage of computing resources and to provide on demand services. After methodical analysis on various factors affecting fault tolerance during load balancing is performed and it is concluded that the factors influencing fault tolerance in load balancing are cloud security, adaptability etc. in comparatively more software firms. In this paper, we have created a model for various IT industries for checking the fault tolerance during Load balancing. An exploration is done with the help of some renowned IT farms and industries in South India. This work consists of 20 hypotheses which may affect the fault tolerance during load balancing in South India. It is verified by using potential statistical analysis tool i.e. Statistical Package for Social Science (SPSS).

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Peer-to-Peer Service Discovery for Grid Computing

Grid and Cloud Computing ◽

10.4018/978-1-4666-0879-5.ch111 ◽

2012 ◽

pp. 232-259

Author(s):

Eddy Caron ◽

Frédéric Desprez ◽

Franck Petit ◽

Cédric Tedeschi

Keyword(s):

Fault Tolerance ◽

Load Balancing ◽

Service Discovery ◽

Large Scale ◽

Dynamic Networks ◽

Peer To Peer ◽

Indexing System ◽

Key Points ◽

Computing Platforms ◽

Traditional Approaches

Within distributed computing platforms, some computing abilities (or services) are offered to clients. To build dynamic applications using such services as basic blocks, a critical prerequisite is to discover those services. Traditional approaches to the service discovery problem have historically relied upon centralized solutions, unable to scale well in large unreliable platforms. In this chapter, we will first give an overview of the state of the art of service discovery solutions based on peer-to-peer (P2P) technologies that allow such a functionality to remain efficient at large scale. We then focus on one of these approaches: the Distributed Lexicographic Placement Table (DLPT) architecture, that provide particular mechanisms for load balancing and fault-tolerance. This solution centers around three key points. First, it calls upon an indexing system structured as a prefix tree, allowing multi-attribute range queries. Second, it allows the mapping of such structures onto heterogeneous and dynamic networks and proposes some load balancing heuristics for it. Third, as our target platform is dynamic and unreliable, we describe its powerful fault-tolerance mechanisms, based on self-stabilization. Finally, we present the software prototype of this architecture and its early experiments.

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On the Viability of Entropy for Improving Fault Tolerance and Load Balancing in Grid Computing

Advances in Intelligent Systems and Computing - Advanced Machine Learning Technologies and Applications ◽

10.1007/978-3-030-69717-4_28 ◽

2021 ◽

pp. 275-285

Author(s):

Hossam Selim ◽

Saad M. Darwish

Keyword(s):

Fault Tolerance ◽

Load Balancing ◽

Grid Computing

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Integrating Fault Tolerance and Load Balancing in Distributed Systems Based on CORBA

Dependable Computing - EDCC 5 - Lecture Notes in Computer Science ◽

10.1007/11408901_11 ◽

2005 ◽

pp. 154-166 ◽

Cited By ~ 2

Author(s):

A. V. Singh ◽

L. E. Moser ◽

P. M. Melliar-Smith

Keyword(s):

Distributed Systems ◽

Fault Tolerance ◽

Load Balancing

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A Comprehensive Study of Load Balancing Approaches in the Cloud Computing Environment and a Novel Fault Tolerance Approach

IEEE Access ◽

10.1109/access.2020.3009184 ◽

2020 ◽

Vol 8 ◽

pp. 130500-130526

Author(s):

Muhammad Asim Shahid ◽

Noman Islam ◽

Muhammad Mansoor Alam ◽

Mazliham Mohd Su'ud ◽

Shahrulniza Musa

Keyword(s):

Cloud Computing ◽

Fault Tolerance ◽

Load Balancing ◽

Computing Environment ◽

Cloud Computing Environment ◽

Tolerance Approach ◽

Comprehensive Study

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A Comparative Analysis of Performance of Shared Memory Cluster Computing Interconnection Systems

Journal of Computer Networks and Communications ◽

10.1155/2014/128438 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9

Author(s):

Minakshi Tripathy ◽

C. R. Tripathy

Keyword(s):

Comparative Analysis ◽

Fault Tolerance ◽

Load Balancing ◽

Shared Memory ◽

Cluster Computing ◽

Distributed Shared Memory ◽

System Size ◽

Cluster Architecture ◽

Analysis Of Performance ◽

Made In

In recent past, many types of shared memory cluster computing interconnection systems have been proposed. Each of these systems has its own advantages and limitations. With the increase in system size of the cluster interconnection systems, the comparative analysis of their various performance measures becomes quite inevitable. The cluster architecture, load balancing, and fault tolerance are some of the important aspects, which need to be addressed. The comparison needs to be made in order to choose the best one for a particular application. In this paper, a detailed comparative study on four important and different classes of shared memory cluster architectures has been made. The systems taken up for the purpose of the study are shared memory clusters, hierarchical shared memory clusters, distributed shared memory clusters, and the virtual distributed shared memory clusters. These clusters are analyzed and compared on the basis of the architecture, load balancing, and fault tolerance aspects. The results of comparison are reported.

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