scholarly journals Analysis of Effective Load Balancing Techniques in Distributed Environment

2020 ◽  
Author(s):  
Anju Shukla ◽  
Shishir Kumar ◽  
Harikesh Singh
Keyword(s):  
Distributed Computing ◽  
Load Balancing ◽  
Performance Optimization ◽  
Resource Selection ◽  
High Performance ◽  
Distributed Environment ◽  
Distributed Resources ◽  
Heterogeneous Services ◽  
Future Extension ◽  
Geographically Distributed

Computational approaches contribute a significance role in various fields such as medical applications, astronomy, and weather science, to perform complex calculations in speedy manner. Today, personal computers are very powerful but underutilized. Most of the computer resources are idle; 75% of the time and server are often unproductive. This brings the sense of distributed computing, in which the idea is to use the geographically distributed resources to meet the demand of high-performance computing. The Internet facilitates users to access heterogeneous services and run applications over a distributed environment. Due to openness and heterogeneous nature of distributed computing, the developer must deal with several issues like load balancing, interoperability, fault occurrence, resource selection, and task scheduling. Load balancing is the mechanism to distribute the load among resources optimally. The objective of this chapter is to discuss need and issues of load balancing that evolves the research scope. Various load balancing algorithms and scheduling methods are analyzed that are used for performance optimization of web resources. A systematic literature with their solutions and limitations has been presented. The chapter provides a concise narrative of the problems encountered and dimensions for future extension.

Load Balancing to Increase the Consistency of Replicas in Data Grids

2012 ◽  
pp. 42-57
Author(s):  
Ghalem Belalem ◽  
Naima Belayachi ◽  
Radjaa Behidji ◽  
Belabbes Yagoubi
Keyword(s):  
Load Balancing ◽  
Large Scale ◽  
Data Grids ◽  
Distributed Resources ◽  
Data Set ◽  
Large Scale Systems ◽  
Consistency Management ◽  
Geographically Distributed ◽  
Replication Technique ◽  
Improve Service Quality

Data grids are current solutions to the needs of large scale systems and provide a set of different geographically distributed resources. Their goal is to offer an important capacity of parallel calculation, ensure a data effective and rapid access, improve the availability, and tolerate the breakdowns. In such systems, however, these advantages are possible only by using the replication technique. The use of this technique raises the problem of maintaining consistency of replicas of the same data set. In order to guarantee replica set reliability, it is necessary to have high coherence. This fact, however, penalizes performance. In this paper, the authors propose studying balancing influence on replica quality. For this reason, a service of hybrid consistency management is developed, which combines the pessimistic and optimistic approaches and is extended by a load balancing service to improve service quality. This service is articulated on a hierarchical model with two levels.

scholarly journals Portable Library of Migratable Sockets

2001 ◽  
Vol 9 (4) ◽  
pp. 211-222 ◽  
Author(s):  
Marian Bubak ◽  
Dariusz Żbik ◽  
Dick van Albada ◽  
Kamil Iskra ◽  
Peter Sloot
Keyword(s):  
Parallel Computing ◽  
Distributed Computing ◽  
Load Balancing ◽  
High Performance ◽  
Internal Communication ◽  
Network Interface ◽  
Prototype Implementation ◽  
Computing Environments ◽  
User Space ◽  
Socket Interface

Efficient load balancing is essential for parallel distributed computing. Many parallel computing environments use TCP or UDP through the socket interface as a communication mechanism. This paper presents the design and development of a prototype implementation of a network interface that can preserve communication between processes during process migration. This new communication library is a substitution for the well-known socket interface. It is implemented in user — space; it is portable, and no modifications of user applications are required. TCP/IP is applied for internal communication, which guarantees relatively high performance and portability.

Load Balancing to Increase the Consistency of Replicas in Data Grids

2010 ◽  
Vol 1 (4) ◽  
pp. 42-57 ◽  
Author(s):  
Ghalem Belalem ◽  
Naima Belayachi ◽  
Radjaa Behidji ◽  
Belabbes Yagoubi
Keyword(s):  
Load Balancing ◽  
Large Scale ◽  
Data Grids ◽  
Distributed Resources ◽  
Data Set ◽  
Large Scale Systems ◽  
Consistency Management ◽  
Geographically Distributed ◽  
Replication Technique ◽  
Improve Service Quality

Data grids are current solutions to the needs of large scale systems and provide a set of different geographically distributed resources. Their goal is to offer an important capacity of parallel calculation, ensure a data effective and rapid access, improve the availability, and tolerate the breakdowns. In such systems, however, these advantages are possible only by using the replication technique. The use of this technique raises the problem of maintaining consistency of replicas of the same data set. In order to guarantee replica set reliability, it is necessary to have high coherence. This fact, however, penalizes performance. In this paper, the authors propose studying balancing influence on replica quality. For this reason, a service of hybrid consistency management is developed, which combines the pessimistic and optimistic approaches and is extended by a load balancing service to improve service quality. This service is articulated on a hierarchical model with two levels.

scholarly journals The architectures analyzing for computational workflows designing in a distributed environment

2020 ◽  
Keyword(s):  
Cloud Computing ◽  
High Performance Computing ◽  
High Performance ◽  
Business Processes ◽  
Service Oriented Architecture ◽  
Distributed Environment ◽  
End User ◽  
Distributed Resources ◽  
Computing Architecture ◽  
Performance Computing

The paper presents a model of computational workflows based on end-user understanding and provides an overview of various computational architectures, such as computing cluster, Grid, Cloud Computing, and SOA, for building workflows in a distributed environment. A comparative analysis of the capabilities of the architectures for the implementation of computational workflows have been shown that the workflows should be implemented based on SOA, since it meets all the requirements for the basic infrastructure and provides a high degree of compute nodes distribution, as well as their migration and integration with other systems in a heterogeneous environment. The Cloud Computing architecture using may be efficient when building a basic information infrastructure for the organization of distributed high-performance computing, since it supports the general and coordinated usage of dynamically allocated distributed resources, allows in geographically dispersed data centers to create and virtualize high-performance computing systems that are able to independently support the necessary QoS level and, if necessary, to use the Software as a Service (SaaS) model for end-users. The advantages of the Cloud Computing architecture do not allow the end user to realize business processes design automatically, designing them "on the fly". At the same time, there is the obvious need to create semantically oriented computing workflows based on a service-oriented architecture using a microservices approach, ontologies and metadata structures, which will allow to create workflows “on the fly” in accordance with the current request requirements.

scholarly journals Fault Tolerance Based Load Balancing Approach for Web Resources in Cloud Environment

2019 ◽  
Vol 17 (2) ◽  
pp. 225-232 ◽  
Author(s):  
Anju Shukla ◽  
Shishir Kumar ◽  
Harikesh Singh
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Resource Selection ◽  
High Performance ◽  
Low Cost ◽  
Area Network ◽  
Wide Area Network ◽  
Task Execution ◽  
Index Value

Cloud computing consists group of heterogeneous resources scattered around the world connected through the network. Since high performance computing is strongly interlinked with geographically distributed service to interact with each other in wide area network, Cloud computing makes the architecture consistent, low-cost, and well-suited with concurrent services. This paper presents a fault tolerance load balancing technique based on resource load and fault index value. The proposed technique works in two phases: resource selection and task execution. The resource selection phase selects the suitable resource for task execution. A resource with least resource load and fault index value is selected for task execution. Further task execution phase sets checkpoints at various intervals for saving the task state periodically. The checkpoints are set at various intervals based on resource fault index. When a task is executed on a resource, fault index value of selected resource is updated accordingly. This reduces the checkpoint overhead by avoiding unnecessary placements of checkpoints. The proposed model is validated on CloudSim and provides improved performance in terms of response time, makespan, throughput and checkpoint overhead in comparison to other state-of-the-art methods.

scholarly journals Optimization of tomographic reconstruction workflows on geographically distributed resources

2016 ◽  
Vol 23 (4) ◽  
pp. 997-1005 ◽  
Author(s):  
Tekin Bicer ◽  
Dogˇa Gürsoy ◽  
Rajkumar Kettimuthu ◽  
Francesco De Carlo ◽  
Ian T. Foster
Keyword(s):  
Management System ◽  
High Performance ◽  
Data Transfer ◽  
Tomographic Reconstruction ◽  
Workflow Management ◽  
Workflow Management System ◽  
Distributed Resources ◽  
Geographically Distributed ◽  
Execution Times ◽  
Computational Resources

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modeling of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i)data transferbetween storage and computational resources, (i)wait/queuetime of reconstruction jobs at compute resources, and (iii)computationof reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizesGlobusto perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Moreover, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.

scholarly journals CRIC: a unified information system for WLCG and beyond

2019 ◽  
Vol 214 ◽  
pp. 03003 ◽  
Author(s):  
Alexey Anisenkov ◽  
Julia Andreeva ◽  
Alessandro Di Girolamo ◽  
Panos Paparrigopoulos ◽  
Aresh Vedaee
Keyword(s):  
Information System ◽  
Distributed Computing ◽  
User Interfaces ◽  
Service Discovery ◽  
Large Scale ◽  
Atlas Collaboration ◽  
Distributed Environment ◽  
Distributed Resources ◽  
Level Information ◽  
High Level

The Worldwide LHC Computing Grid (WLCG) is an innovative distributed environment which is deployed through the use of grid computing technologiesin order to provide computing and storage resources to the LHC experimentsfor data processing and physics analysis. Following increasing demands of LHC computing needs toward high luminosity era, the experiments are engagdin an ambitious program to extend the capability of WLCG distributed environment, for instance including opportunistically used resources such as High-Performance Computers (HPCs), cloud platforms and volunteer computer. norder to be effectively used by the LHC experiments, all these diverse distributed resources should be described in detail. This implies easy service discovery of shared physical resources, detailed description of service configurations and experiment-specific data structures is needed. In this contribution, we present a high-level information component of a distributed computing environment, the Computing Resource Information Catalogue (CRIC) which aims to facilitate distributed computing operations for the LHC experiments and consolidate WLCG topology information. In addition, CRIC performs data validation and provides coherent view and topology descriptinto the LHC VOs for service discovery and configuration. CRIC represents teevolution of ATLAS Grid Information System (AGIS) into the common experiment independent high-level information framework. CRIC’s mission is to serve not just ATLAS Collaboration needs for the description of the distributed environment but any other virtual organization relying on large scale distributed infrastructure as well as the WLCG on the global scope. The contribution describes CRIC architecture, implementation of data model,collectors, user interfaces, advanced authentication and access control components of the system.

Thermal Management Considerations for Geographically Distributed Computing Infrastructures

2010 ◽  
Author(s):  
Amip Shah ◽  
Cullen Bash ◽  
Martin Arlitt ◽  
Yuan Chen ◽  
Daniel Gmach ◽  
...  
Keyword(s):  
Distributed Computing ◽  
Thermal Management ◽  
Thermal Performance ◽  
Data Centers ◽  
Service Level ◽  
Distributed Environment ◽  
Distribution Of Resources ◽  
Geographically Distributed ◽  
Dynamic Resource ◽  
Distributed Computing Infrastructures

This paper discusses an approach for optimizing the infrastructure thermal performance related to a geographically distributed computing service. Beginning by modeling the total energy costs associated with cooling a distributed environment, the cooling efficiency of a service is evaluated by superposing the piecewise IT workloads that may be delivered from various locations. We find that the total service-level thermal performance can be distinct from the facility- or infrastructure-level thermal performance, which requires a different global thermal management strategy relative to that of single-site environments. The approach is illustrated for a hypothetical example wherein a service is delivered from three different data centers in geographically diverse locations. Depending on the workload characteristics, the optimal distribution of resources across the data centers varies; but through dynamic resource allocation, it becomes possible to support the same service at increased energy efficiencies.

Resource-aware load balancing model for batch of tasks (BoT) with best fit migration policy on heterogeneous distributed computing systems

2020 ◽  
Vol 16 (2) ◽  
pp. 113-141
Author(s):  
Mahfooz Alam ◽  
Raza Abbas Haidri ◽  
Mohammad Shahid
Keyword(s):  
Distributed Computing ◽  
Load Balancing ◽  
Superior Performance ◽  
Distributed Environment ◽  
Distributed Computing Systems ◽  
Content Type ◽  
Real Model ◽  
Heterogeneous Distributed Computing ◽  
Resource Aware ◽  
Best Fit

Purpose Load balancing is an important issue for a heterogeneous distributed computing system environment that has been proven to be a nondeterministic polynomial time hard problem. This paper aims to propose a resource-aware load balancing (REAL) model for a batch of independent tasks with a centralized load balancer to make the solution appropriate for a practical heterogeneous distributed environment having a migration cost with the objective of maximizing the level of load balancing considering bandwidth requirements for migration of the tasks. Design/methodology/approach To achieve the effective schedule, load balancing issues should be addressed and tackled through efficient workload distribution. In this approach, the migration has been carried out in two phases, namely, initial migration and best-fit migration. Using the best-fit policy in migrations helps in the possible performance improvement by minimizing the remaining idle slots on underloaded nodes that remain unentertained during the initial migration. Findings The experimental results reveal that the proposed model exhibits a superior performance among the other strategies on considered parameters such as makespan, average utilization and level of load balancing under study for a heterogeneous distributed environment. Originality/value Design of the REAL model and a comparative performance evaluation with LBSM and ITSLB have been conducted by using MATLAB 8.5.0.

Matlab and Parallel Computing

2012 ◽  
Vol 17 (4) ◽  
pp. 207-216 ◽  
Author(s):  
Magdalena Szymczyk ◽  
Piotr Szymczyk
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Parallel Computing ◽  
Distributed Computing ◽  
Control Systems ◽  
High Performance ◽  
Parallel Applications ◽  
Process Simulations ◽  
Key Features ◽  
Financial Process

Abstract The MATLAB is a technical computing language used in a variety of fields, such as control systems, image and signal processing, visualization, financial process simulations in an easy-to-use environment. MATLAB offers "toolboxes" which are specialized libraries for variety scientific domains, and a simplified interface to high-performance libraries (LAPACK, BLAS, FFTW too). Now MATLAB is enriched by the possibility of parallel computing with the Parallel Computing ToolboxTM and MATLAB Distributed Computing ServerTM. In this article we present some of the key features of MATLAB parallel applications focused on using GPU processors for image processing.

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