Affinity-Based Task Scheduling on Heterogeneous Multicore Systems Using CBS and QBICTM

This work presents the grouping of dependent tasks into a cluster using the Bayesian analysis model to solve the affinity scheduling problem in heterogeneous multicore systems. The non-affinity scheduling of tasks has a negative impact as the overall execution time for the tasks increases. Furthermore, non-affinity-based scheduling also limits the potential for data reuse in the caches so it becomes necessary to bring the same data into the caches multiple times. In heterogeneous multicore systems, it is essential to address the load balancing problem as all cores are operating at varying frequencies. We propose two techniques to solve the load balancing issue, one being designated “chunk-based scheduler” (CBS) which is applied to the heterogeneous systems while the other system is “quantum-based intra-core task migration” (QBICTM) where each task is given a fair and equal chance to run on the fastest core. Results show 30–55% improvement in the average execution time of the tasks by applying our CBS or QBICTM scheduler compare to other traditional schedulers when compared using the same operating system.

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A New Approach of Dynamic Load Balancing Scheduling Algorithm for Homogeneous Multiprocessor System

International Journal of Applied Evolutionary Computation ◽

10.4018/ijaec.2016040104 ◽

2016 ◽

Vol 7 (2) ◽

pp. 61-75 ◽

Cited By ~ 5

Author(s):

Mahfooz Alam ◽

Ankur Kumar Varshney

Keyword(s):

Load Balancing ◽

Dynamic Load ◽

Execution Time ◽

Interconnection Network ◽

Scheduling Algorithm ◽

Heterogeneous Systems ◽

Dynamic Load Balancing ◽

Multiprocessor System ◽

Load Imbalance ◽

Crossed Cube

Load balancing of parallel tasks in homogeneous as well as heterogeneous systems are major trouble for researches of both industry and academia. Load balancing were broadly classified into two categories namely static load balancing and dynamic load balancing. Nowadays, numerous of researches focus towards dynamic load balancing schemes for multiprocessor system. In this paper, the authors propose a dynamic load balancing strategy for homogeneous multiprocessor system and apply on cube based interconnection network named as Folded Crossed Cube network. The performance of folded crossed cube network gives better result in terms of diameter. Experimental results show that lesser load imbalance factor has been achieved along with execution time. By this algorithm, parallel jobs are solved with largest number of tasks. The merit of this algorithm is that when the number of tasks increases, the execution time decreases with lesser load imbalance factor.

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Lightweight Blockchain Processing. Case Study: Scanned Document Tracking on Tezos Blockchain

Applied Sciences ◽

10.3390/app11157169 ◽

2021 ◽

Vol 11 (15) ◽

pp. 7169

Author(s):

Mohamed Allouche ◽

Tarek Frikha ◽

Mihai Mitrea ◽

Gérard Memmi ◽

Faten Chaabane

Keyword(s):

Load Balancing ◽

Relative Error ◽

Execution Time ◽

General Purpose ◽

Experimental Results ◽

Raspberry Pi ◽

Embedded Platform ◽

Memory Resources ◽

Processing Solution

To bridge the current gap between the Blockchain expectancies and their intensive computation constraints, the present paper advances a lightweight processing solution, based on a load-balancing architecture, compatible with the lightweight/embedding processing paradigms. In this way, the execution of complex operations is securely delegated to an off-chain general-purpose computing machine while the intimate Blockchain operations are kept on-chain. The illustrations correspond to an on-chain Tezos configuration and to a multiprocessor ARM embedded platform (integrated into a Raspberry Pi). The performances are assessed in terms of security, execution time, and CPU consumption when achieving a visual document fingerprint task. It is thus demonstrated that the advanced solution makes it possible for a computing intensive application to be deployed under severely constrained computation and memory resources, as set by a Raspberry Pi 3. The experimental results show that up to nine Tezos nodes can be deployed on a single Raspberry Pi 3 and that the limitation is not derived from the memory but from the computation resources. The execution time with a limited number of fingerprints is 40% higher than using a classical PC solution (value computed with 95% relative error lower than 5%).

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Preemptive Scheduling for Two-Processor Systems

Fundamenta Informaticae ◽

10.3233/fi-1988-11102 ◽

1988 ◽

Vol 11 (1) ◽

pp. 1-19

Author(s):

Andrzej Rowicki

Keyword(s):

Execution Time ◽

Preemptive Scheduling ◽

Total Execution Time ◽

Schedule Length ◽

Execution Times ◽

Dependent Tasks

The purpose of the paper is to consider an algorithm for preemptive scheduling for two-processor systems with identical processors. Computations submitted to the systems are composed of dependent tasks with arbitrary execution times and contain no loops and have only one output. We assume that preemptions times are completely unconstrained, and preemptions consume no time. Moreover, the algorithm determines the total execution time of the computation. It has been proved that this algorithm is optimal, that is, the total execution time of the computation (schedule length) is minimized.

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Load balancing strategy for multicore systems

2015 13th International Conference on Emerging eLearning Technologies and Applications (ICETA) ◽

10.1109/iceta.2015.7558473 ◽

2015 ◽

Cited By ~ 1

Author(s):

E. Chovancova ◽

J. Mihal'ov

Keyword(s):

Load Balancing ◽

Multicore Systems

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Agent Based Load Balancing in Grid Computing

10.5772/intechopen.94219 ◽

2020 ◽

Author(s):

Wided Ali ◽

Fatima Bouakkaz

Keyword(s):

Load Balancing ◽

Heterogeneous Systems ◽

Agent Based ◽

Selection Policy ◽

Development Framework ◽

Policy Selection ◽

Proposed Model ◽

Multi Agent ◽

Location Policy ◽

System Characteristics

Load-Balancing is an important problem in distributed heterogeneous systems. In this paper, an Agent-based load-balancing model is developed for implementation in a grid environment. Load balancing is realized via migration of worker agents from overloaded resources to underloaded ones. The proposed model purposes to take benefit of the multi-agent system characteristics to create an autonomous system. The Agent-based load balancing model is implemented using JADE (Java Agent Development Framework) and Alea 2 as a grid simulator. The use of MAS is discussed, concerning the solutions adopted for gathering information policy, location policy, selection policy, worker agents migration, and load balancing.

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The Treatment of Industrial Waste by Recycling in Tunisia

Journal of Economics and Management Sciences ◽

10.30560/jems.v1n1p13 ◽

2018 ◽

Vol 1 (1) ◽

pp. p13

Author(s):

Lamia Jamel

Keyword(s):

Waste Management ◽

Environmental Protection ◽

Industrial Waste ◽

Solid Waste Management ◽

Negative Impact ◽

Positive Impact ◽

Urban Expansion ◽

Waste Recycling ◽

Analysis Model ◽

Industrial Waste Management

Waste management in Tunisia is currently one of the priorities of environmental protection and is one of the main pillars of sustainable development. Thus, Tunisia has opted for a comprehensive and progressive policy of environmental protection in order to manage with the current state of the object affected by the strong economic growth and the environment rapid urban expansion in recent years. The area of waste management has received attention currently given the quantity produced changes in the multiplicity of forms and aspects of pollution caused by waste, and limited resources used in the field of solid waste management. During this, our research has been devoted to the study of the phenomenon of industrial waste management by recycling in Tunisia. We employ a model based on a time series analysis model for a period of 17 years from 2000 to 2016. Additionally, we estimate the ability to manage industrial waste recycling based on variables related to the business of recycling industrial waste, variables related to the intervention of Tunisia policy in the management of industrial waste recycling and macroeconomic indicators. From the empirical findings, we conclude that the macro-economic indicators have a negative impact on the dependent variable. The variables related to the intervention of Tunisia policy in industrial waste management through recycling have a positive impact and a negative impact depending on the nature of the waste. And finally, the variable relative to the activity of recycling industrial waste TRDI has a positive impact and DIG variable has a negative impact.

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