相关论文: Economic-based Distributed Resource Management and…

Edge computing has become a promising computing paradigm for building IoT (Internet of Things) applications, particularly for applications with specific constraints such as latency or privacy requirements. Due to resource constraints at the…

Under several emerging application scenarios, such as in smart cities, operational monitoring of large infrastructure, wearable assistance, and Internet of Things, continuous data streams must be processed under very short delays. Several…

This paper presents a comprehensive literature review on applications of economic and pricing models for resource management in cloud networking. To achieve sustainable profit advantage, cost reduction, and flexibility in provisioning of…

With the rapid development in wide area networks and low cost, powerful computational resources, grid computing has gained its popularity. With the advent of grid computing, space limitations of conventional distributed systems can be…

This paper proposes an optimization framework for distributed resource logistics system design to support future multimission space exploration. The performance and impact of distributed In-Situ Resource Utilization (ISRU) systems in…

Executing distributed cyber-physical software processes on edge devices that maintains the resiliency of the overall system while adhering to resource constraints is quite a challenging trade-off to consider for developers. Current…

Cloud-based computing infrastructure provides an efficient means to support real-time processing workloads, e.g., virtualized base station processing, and collaborative video conferencing. This paper addresses resource allocation for a…

In this work, we propose distributed and networked energy management scenarios to optimize the production and reservation of energy among a set of distributed energy nodes. In other words, the idea is to optimally allocate the generated and…

In this paper, a method for efficient scheduling to obtain optimum job throughput in a distributed campus grid environment is presented; Traditional job schedulers determine job scheduling using user and job resource attributes. User…

Deploying applications across the computing continuum requires selecting infrastructure nodes from geographically distributed and heterogeneous environments while satisfying constraints (e.g., performance, location). This decision problem…

Grid technologies aim at enabling a coordinated resource-sharing and problem-solving capabilities over local and wide area networks and span locations, organizations, machine architectures and software boundaries. The heterogeneity of…

With the explosive growth of big data, workloads tend to get more complex and computationally demanding. Such applications are processed on distributed interconnected resources that are becoming larger in scale and computational capacity.…

Edge computing has emerged as a distributed computing paradigm to overcome practical scalability limits of cloud computing. The main principle of edge computing is to leverage on computational resources outside of the cloud for performing…

We propose integrating the edge-computing paradigm into the multi-robot collaborative scheduling to maximize resource utilization for complex collaborative tasks, which many robots must perform together. Examples include collaborative…

Cloud Computing is a paradigm of both parallel processing and distributed computing. It offers computing facilities as a utility service in pay as par use manner. Virtualization, self service provisioning, elasticity and pay per use are the…

With recent increasing computational and data requirements of scientific applications, the use of large clustered systems as well as distributed resources is inevitable. Although executing large applications in these environments brings…

"Grid" computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high-performance orientation. In this…

Grid computing is a distributed computing paradigm which aims to aggregate several heterogeneous and distributed resources, belonging to different and independent organizations, in a dynamic, transparent and coordinated way. Since its…

This paper addresses the problem of management and coordination of energy resources in a typical microgrid, including smart buildings as flexible loads, energy storages, and renewables. The overall goal is to provide a comprehensive and…

Grid computing (GC) systems are large-scale virtual machines, built upon a massive pool of resources (processing time, storage, software) that often span multiple distributed domains. Concurrent users interact with the grid by adding new…