Real-time systems are becoming pervasive with the growing global connectivity and rising consumer demands. The need for real-time processing has become a crucial part of many business applications worldwide. A key fac...
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Real-time systems are becoming pervasive with the growing global connectivity and rising consumer demands. The need for real-time processing has become a crucial part of many business applications worldwide. A key factor that determines the time taken for an application to give out the result hinges on its ability to prioritize, manage, and execute real-time workloads. However, there are several difficulties and constraints connected with implementing tasks in a real-time context. This research study primarily focuses on load balancing for mixed real-time tasks on a multi-core system, one of the major challenges for executing real-time workloads. The purpose of load balancing is to distribute the load evenly among the processor(s) and maximize their utility while minimizing overall execution time. The goal of this paper is to present a critical analysis of existing load balancing techniques for both periodic and aperiodic tasks. The paper explores several factors including throughput, performance, migration time, response time, overhead, resource utilization, scalability, fault tolerance, power efficiency, and other variables that play a crucial role in assessing the efficacy of load balancing in real-time systems. The proposed has contributed in four folds. Firstly, the state-of-the-art of various load balancing algorithms are discussed followed by the architecture involved in real-time multi-core systems. Later, different load balancing based scheduling algorithms were compared on the basis of different schemas and metrics for algorithm evaluation is also provided. Finally, the paper also identifies areas that warrant further exploration or investigation, suggesting potential avenues for future research, and highlighting emerging trends or developments that may shape the field.
Recent results in the application of scheduling theory to hard real-time systems are reviewed in this paper. The review takes the form of an analysis of the problems presented by different application requirements and...
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Recent results in the application of scheduling theory to hard real-time systems are reviewed in this paper. The review takes the form of an analysis of the problems presented by different application requirements and characteristics. Issues covered include uniprocessor and multiprocessor systems, periodic and aperiodic processes, static and dynamic algorithms, transient overloads and resource usage. Protocols that limit and reduce blocking are discussed. Consideration is also given to scheduling Ada tasks.
An edge-weighted directed graph is referred to as a network in this paper, and an edge operation is an operation that increases or decreases an edge weight. Decreasing an edge weight from the infinite to a finite valu...
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An edge-weighted directed graph is referred to as a network in this paper, and an edge operation is an operation that increases or decreases an edge weight. Decreasing an edge weight from the infinite to a finite value or increasing any edge weight from a finite one to the infinite corresponds to addition or deletion of this edge, respectively. The dynamic shortest path problem (DSPP for short) is defined by "Given any network with a specified vertex (denoted as s), and any sequence of edge operations, construct a shortest path tree of each network obtained by executing those edge operations one by one in the order of the sequence." As an application, fast routing for an interior network using link state protocols, such as OSPF and IS-IS, requires solving DSPP efficiently. In this paper, among as many existing algorithms as possible, including those which execute several edge operations simultaneously, fundamental and/or important algorithms are implemented and their capability is evaluated based on the results of computational experiments.
With the expansion of the network and increasing their users, as well as emerging new technologies, such as cloud computing and big data, managing traditional networks is difficult, where the VM load has increased as ...
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ISBN:
(纸本)9781728172194
With the expansion of the network and increasing their users, as well as emerging new technologies, such as cloud computing and big data, managing traditional networks is difficult, where the VM load has increased as well as the required task processing time. Therefore, it is necessary to change the traditional network architecture. Lately, to address this issue, a notion named software-defined network (SDN) has been proposed, which makes network management more conformable. Network resources limitations and requirements fulfilment leads to the important need of load balancing that helps in distributing traffic via several resources to improve network resources efficiency and reliability. Many researchers have worked previously on this task, proposing several algorithms with advantages and disadvantages. This paper focuses on cloud computing load balancing concepts, and represents benefits and some weaknesses regarding to the selected load balancing algorithms and investigates the metrics of their algorithms. In addition, the important challenges of these algorithms have been reviewed to provide future researchers with better load balancing techniques.
Reinforcement learning has emerged as a prominent technique for enhancing robot obstacle avoidance capabilities in recent years. This research provides a comprehensive overview of reinforcement learning methods, focus...
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