A low redundancy and high time efficiency large-scale task assignment strategy for heterogeneous service-oriented cloud computing systems

2020 ◽  
Author(s):  
Jiang Zhu ◽  
Lizan Wang ◽  
Guoqi Xie ◽  
Tingrui Pei ◽  
Sangyoon Oh ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Task Assignment ◽  
High Time ◽  
Computing Systems ◽  
Time Efficiency ◽  
Service Oriented ◽  
Assignment Strategy ◽  
Heterogeneous Service

The Cloud@Home Volunteer and Interoperable Cloud through the Future Internet

2012 ◽  
pp. 79-96
Author(s):  
Salvatore Distefano ◽  
Antonio Puliafito
Keyword(s):  
Cloud Computing ◽  
Business Model ◽  
Hierarchical Clustering ◽  
Large Scale ◽  
Future Internet ◽  
Cloud Infrastructure ◽  
The Future ◽  
Service Oriented

Cloud computing is the new consolidated trend in ICT, often considered as the panacea to all the problems of existing large-scale distributed paradigms such as Grid and hierarchical clustering. The Cloud breakthrough is the service oriented perspective of providing everything “as a service”. Different from the others large-scale distributed paradigms, it was born from commercial contexts, with the aim of selling the temporarily unexploited computing resources of huge datacenters in order to reduce the costs. Since this business model is really attractive and convenient for both providers and consumers, the Cloud paradigm is quickly growing and widely spreading, even in non commercial context. In fact, several activities on the Cloud, such as Nimbus, Eucalyptus, OpenNEbula, and Reservoir, etc., have been undertaken, aiming at specifying open Cloud infrastructure middleware.

Dynamic Dependent Tasks Assignment for Grid Computing

2011 ◽  
Vol 3 (2) ◽  
pp. 44-58 ◽  
Author(s):  
Meriem Meddeber ◽  
Belabbas Yagoubi
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Large Scale ◽  
Task Assignment ◽  
Considerable Effect ◽  
Distributed Applications ◽  
Grid Middleware ◽  
Assignment Strategy ◽  
Transfer Cost ◽  
Dependent Tasks

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Task assignment as a part of resource management has a considerable effect on the grid middleware performance. In grid computing, task execution time is dependent on the machine to which it is assigned, and task precedence constraints are represented by a directed acyclic graph. This paper proposes a hybrid assignment strategy of dependent tasks in Grids which integrate static and dynamic assignment technologies. Grid computing is considered a set of clusters formed by a set of computing elements and a cluster manager. The main objective is to arrive at a method of task assignment that could achieve minimum response time and reduce the transfer cost, inducing by the tasks transfer respecting the dependency constraints.

scholarly journals Contextual Contracts for Component-Based Resource Abstraction in a Cloud of HPC Services

2019 ◽  
Author(s):  
Wagner Al Alam ◽  
Francisco Carvalho Junior
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Large Scale ◽  
Matrix Multiplication ◽  
Small Scale ◽  
Computing Systems ◽  
Computing Platform ◽  
Computing Platforms

The efforts to make cloud computing suitable for the requirements of HPC applications have motivated us to design HPC Shelf, a cloud computing platform of services for building and deploying parallel computing systems for large-scale parallel processing. We introduce Alite, the system of contextual contracts of HPC Shelf, aimed at selecting component implementations according to requirements of applications, features of targeting parallel computing platforms (e.g. clusters), QoS (Quality-of-Service) properties and cost restrictions. It is evaluated through a small-scale case study employing a componentbased framework for matrix-multiplication based on the BLAS library.

scholarly journals Hierarchical Task Assignment Strategy for Heterogeneous Multi-UAV System in Large-Scale Search and Rescue Scenarios

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Jie Chen ◽  
Kai Xiao ◽  
Kai You ◽  
Xianguo Qing ◽  
Fang Ye ◽  
...  
Keyword(s):  
Large Scale ◽  
Cluster Head ◽  
Task Assignment ◽  
Search And Rescue ◽  
Small Scale ◽  
Assignment Strategy ◽  
Negotiation Mechanism ◽  
Decoupling Algorithm ◽  
Task Assignment Problem ◽  
Multi Uav

For the large-scale search and rescue (S&R) scenarios, the centralized and distributed multi-UAV multitask assignment algorithms for multi-UAV systems have the problems of heavy computational load and massive communication burden, which make it hard to guarantee the effectiveness and convergence speed of their task assignment results. To address this issue, this paper proposes a hierarchical task assignment strategy. Firstly, a model decoupling algorithm based on density clustering and negotiation mechanism is raised to decompose the large-scale task assignment problem into several nonintersection and complete small-scale task assignment problems, which effectively reduces the required computational amount and communication cost. Then, a cluster head selection method based on multiattribute decision is put forward to select the cluster head for each UAV team. These cluster heads will communicate with the central control station about the latest assignment information to guarantee the completion of S&R mission. At last, considering that a few targets cannot be effectively allocated due to UAVs’ limited and unbalanced resources, an auction-based task sharing scheme among UAV teams is presented to guarantee the mission coverage of the multi-UAV system. Simulation results and analyses comprehensively verify the feasibility and effectiveness of the proposed hierarchical task assignment strategy in large-scale S&R scenarios with dispersed clustering targets.

Improving Failure Tolerance in Large-Scale Cloud Computing Systems

2019 ◽  
Vol 68 (2) ◽  
pp. 620-632 ◽  
Author(s):  
Liang Luo ◽  
Sa Meng ◽  
Xiwei Qiu ◽  
Yuanshun Dai
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Computing Systems ◽  
Failure Tolerance

Cloud Computing Security

2012 ◽  
Vol 4 (1) ◽  
pp. 52-66 ◽  
Author(s):  
Junaid Arshad ◽  
Paul Townend ◽  
Jie Xu ◽  
Wei Jie
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
State Of The Art ◽  
Emerging Technology ◽  
The State ◽  
Computing Systems ◽  
Cloud Computing Security ◽  
On Demand ◽  
Cloud Computing Adoption ◽  
Security Challenges

The evolution of modern computing systems has lead to the emergence of Cloud computing. Cloud computing facilitates on-demand establishment of dynamic, large scale, flexible, and highly scalable computing infrastructures. However, as with any other emerging technology, security underpins widespread adoption of Cloud computing. This paper presents the state-of-the-art about Cloud computing along with its different deployment models. The authors also describe various security challenges that can affect an organization’s decision to adopt Cloud computing. Finally, the authors list recommendations to mitigate with these challenges. Such review of state-of-the-art about Cloud computing security can serve as a useful barometer for an organization to make an informed decision about Cloud computing adoption.

scholarly journals An Optimal Task Assignment Strategy in Cloud-Fog Computing Environment

2021 ◽  
Vol 11 (4) ◽  
pp. 1909
Author(s):  
Jung-Fa Tsai ◽  
Chun-Hua Huang ◽  
Ming-Hua Lin
Keyword(s):  
Internet Of Things ◽  
Assignment Problem ◽  
Fog Computing ◽  
Task Assignment ◽  
The Internet ◽  
Computing Environment ◽  
Computing Systems ◽  
Assignment Strategy ◽  
The Internet Of Things ◽  
Task Assignment Problem

With the advent of the Internet of Things era, more and more emerging applications need to provide real-time interactive services. Although cloud computing has many advantages, the massive expansion of the Internet of Things devices and the explosive growth of data may induce network congestion and add network latency. Cloud-fog computing processes some data locally on edge devices to reduce the network delay. This paper investigates the optimal task assignment strategy by considering the execution time and operating costs in a cloud-fog computing environment. Linear transformation techniques are used to solve the nonlinear mathematical programming model of the task assignment problem in cloud-fog computing systems. The proposed method can determine the globally optimal solution for the task assignment problem based on the requirements of the tasks, the processing speed of nodes, and the resource usage cost of nodes in cloud-fog computing systems.

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