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EATMON, DEDRA Evaluating Placement Algorithms with the DREAM Framework for Recon gurable Hardware Devices Under the direction of Dr. Clay. S. Gloster, Jr. The eld programmable gate array FPGA has become one of the most utilized con... more
Multiprocessor task scheduling is a well known NP-hard problem and numerous methods have been proposed to optimally solve it. The objective is makespan minimization, i.e. we want the last task to complete as early as possible. Simulated... more
Cloud computing is the requirement based on clients and provides many resources that aim to share it as a service through the internet. For optimal use, Cloud computing resources such as storage, application, and other services need... more
Cloud computing offers on-demand access to shared resources, with user costs based on resource usage and execution time. To attract users, cloud providers need efficient schedulers that minimize these costs. Achieving cost minimization is... more
Cloud computing is becoming increasingly important to developers and companies because to the rapid development of information technology and the wide availability of internet applications. Every information technology industry has a... more
This paper presents the hybridization of two metaheuristic algorithms which belongs to different categories, for optimizing the tasks scheduling in cloud environment. Hybridization of a game-based metaheuristic algorithm namely, darts... more
Abstract—This paper examines the critical trade-offs between energy efficiency and performance inherent in choosing between Bare Metal, Real-Time Operating System (RTOS), and Full Operating System (Full OS) architectures for Internet of... more
Grid computing is a recently developed technology. Although the developmental tools and techniques for the grid have been extensively studied, yet some important issues, e.g., grid service reliability and task scheduling in the grid, have... more
Scheduling refers to the process of allocating cloud resources to several users according to a schedule that has been established in advance. It is not possible to get acceptable performance in settings that are distributed without proper... more
In the recent years, many researchers have showed a great deal of interest to improve the scheduling of workload in the cloud platforms. On the other hand, to carry out the execution of the scientific workloads in the cloud environment,... more
Reconfigurable hardware can be used to build a multitasking system where tasks are assigned to HW resources at run-time according to the requirements of the running applications. These tasks are frequently represented as direct acyclic... more
Una entre las metaheurísticas más exitosas que aparecieron en los últimos aos del siglo pasado es GRASP, un método multi-arranque diseñado para resolver problemas difíciles en optimización combinatoria. En su versión básica cada iteración... more
Cloud computing represents an evolved form of cluster, client server, and grid computing, enabling users to seamlessly access resources over the internet. The quality and reliability of the cloud computing services are depends on the... more
We give a new formulation for the problem of task scheduling into unrelated processors under precedence constraints. This formulation has a polynomial number of variables and does not require that the processing times be integer valued.
The increasing complexity and energy demands of modern cloud data centers have necessitated intelligent resource management strategies that balance efficiency with Quality of Service (QoS). Central to maintaining this balance are Service... more
The increasing complexity and energy demands of modern cloud data centers have necessitated intelligent resource management strategies that balance efficiency with Quality of Service (QoS). Central to maintaining this balance are Service... more
Mr. N. Abid Ali Khan * and Prof. K. Ushadevi ** ... *R&D Engineer-Embedded Systems & Lecturer, TIFAC-CORE, SASTRA University, Thanjavur-613402, Tamil Nadu, India. abid_ms@rediffmail.com ... ** Dean-School of Computing &... more
The aim of this paper is to provide a description of machine learning based scheduling approach for high-loaded distributed systems that have patterns of tasks/queries that occur recurrently in workflow. The core of this approach is to... more
The aim of this paper is to provide a description of deep-learning-based scheduling approach for academicpurpose high-performance computing systems. Academicpurpose distributed computing systems' (DCS) share reaches 17.4% amongst TOP500... more
Contemporary healthcare settings need optimal availability, safe data management, and sophisticated analytics to successfully address crises and provide continuous care provision. This study tackles the difficulty of constructing robust... more
The Cloud Computing is a most recent computing paradigm where IT services are provided and delivered over the Internet on demand and pay as you go. On the other hands, the task scheduling problem is considered one of the main challenges... more
We present in this article a method of validation for "serial transaction". The serial transaction model has been proposed in order to validate a concrete real-time application. This model is typically a task reading serial information... more
In this paper we present a new search method for par- titioning and scheduling a set of periodic tasks on a multi- processor or distributed architecture. The schedule is fixed- priority driven and task migration is not allowed. The aim of... more
In this paper, a novel scheduling algorithm has been presented that is more efficient and has more reliability comparing similar algorithms. DSQGG is a novel algorithm that by defining new parameters and metrics, has decreased the delay... more
Large-scale parallel applications with complex global data dependencies beyond those of reductions pose significant scalability challenges in an asynchronous runtime system. Internodal challenges include identifying the all-to-all... more
In multi-agent domains, agents can be given planning or scheduling autonomy through coordination. However, plan coordination discards available scheduling information, while schedule coordination possibly over-constrains the problem from... more
Multi-agent planning and scheduling concerns finding a joint plan to achieve some set of common goals with several independent agents each aiming to find a plan or schedule for their part of the goals. To avoid conflicts in these... more
In this article we address the problem of scheduling on realistic high performance computing facilities using incomplete information about tasks execution times. We introduce a variation of our previous Penalty Scheduling Policy,... more
We consider the problem of executing a dynamically changing set of tasks on a reconfigurable system, made upon a processor and a reconfigurable device. Task execution on such a platform is managed by a scheduler that can allocate tasks... more
In this work dynamic module selection is integrated in a scheduling and placement flow of tasks for a Dynamic Network-on-Chip. Several implementations (modules) of a task are considered, which differ in size and execution time. In... more
except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known... more
except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known... more
Cooperative problem solving with shared resources is important in practical multi-agent systems. Resource constraints are necessary to handle practical problems such as distributed task scheduling with limited resource availability. As a... more
Containers have completely changed how modern applications are designed and delivered by offering an extremely modular, scalable, and efficient environment. Scheduling and allocating resources-like CPU, memory, and network bandwidth-into... more
For many applications, a microservices architecture promises better performance and flexibility compared to a conventional monolithic architecture. In spite of the advantages of a microservices architecture, deploying microservices poses... more
Semantic web and cloud technology systems have been critical components in creating and deploying applications in various fields. Although they are self-contained, they can be combined in various ways to create solutions, which has... more
In the last few years, the traditional ways to keep the increase of hardware performance to the rate predicted by the Moore's Law have vanished. When uni-cores were the norm, hardware design was decoupled from the software stack thanks to... more
In this article, we present a design technique that facilitates the work of extracting and defining the tasks scheduling problem for a multiagent system. We also compare a centralized scheduling approach to a decentralized scheduling... more
This paper generalizes the notion of utilization bounds for schedulability of aperiodic tasks to the case of distributed resource systems. In the basic model, aperiodically arriving tasks are processed by multiple stages of a resource... more
Distributed, Real-time, Embedded (DRE) systems present numerous challenges with respect to certification of their real-time behavior. Ideally, to address these we would like to build a model of our system that captures relevant... more
Efficient load balancing in cloud environments is critical to ensuring low response time, optimal execution time, high resource utilization, and evenly distributed server workloads. Inadequate load balancing, often due to limited... more
Efficient cloud resource management is crucial for optimizing performance, reducing costs, and ensuring scalability in dynamic cloud environments. This paper proposes a novel framework that integrates ARIMA (Auto Regressive Integrated... more
The telecom industry is undergoing a change because to the combination of Big Data analytics and Robotic Process Automation (RPA), which boosts customer happiness, operational efficiency, and strategic decision-making. While big data... more
Efficient resource allocation is crucial for cloud data centers performance, scalability, and cost effectiveness. Traditional load balancing systems frequently fail to adjust changing workloads resulting in poor resource use, increased... more
The primary aim is to build a trust prediction model that incorporates deep learning and Bayesian inference into it to make decisions in the cloud environment better. This model is real-time trust assessment, enhancing security with risk... more
In an effort to improve operational effectiveness and strategic decision-making, this study explores how Big Data Analytics (BDA) and the Internet of Things (IoT) can be integrated inside the Business Intelligence (BI) framework. In order... more
Strong, low-latency communication frameworks are required for Medical Internet of Things (MIoT) applications due to the growing need for real-time data processing in the healthcare industry. The strict latency and reliability requirements... more
Background Machine learning has become critical in AI software development, speeding up data processing and improving predictive insights. Optimized ML pipelines increase accuracy and efficiency, which benefits industries such as... more