scholarly journals Dynamic Scalable Stochastic Petri Net: A Novel Model for Designing and Analysis of Resource Scheduling in Cloud Computing

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Hua He ◽  
Shanchen Pang ◽  
Zenghua Zhao
Keyword(s):  
Cloud Computing ◽  
Petri Net ◽  
Performance Indicators ◽  
Large Scale ◽  
Computing Systems ◽  
Average Completion Time ◽  
Stochastic Petri Net ◽  
Fair Scheduling ◽  
And Performance ◽  
Improved Algorithm

Performance evaluation of cloud computing systems studies the relationships among system configuration, system load, and performance indicators. However, such evaluation is not feasible by dint of measurement methods or simulation methods, due to the properties of cloud computing, such as large scale, diversity, and dynamics. To overcome those challenges, we present a novel Dynamic Scalable Stochastic Petri Net (DSSPN) to model and analyze the performance of cloud computing systems. DSSPN can not only clearly depict system dynamic behaviors in an intuitive and efficient way but also easily discover performance deficiencies and bottlenecks of systems. In this study, we further elaborate some properties of DSSPN. In addition, we improve fair scheduling taking into consideration job diversity and resource heterogeneity. To validate the improved algorithm and the applicability of DSSPN, we conduct extensive experiments through Stochastic Petri Net Package (SPNP). The performance results show that the improved algorithm is better than fair scheduling in some key performance indicators, such as average throughput, response time, and average completion time.

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.

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.

A GENERALIZED STOCHASTIC PETRI-NET MODEL FOR PERFORMANCE ANALYSIS AND ALLOCATION OPTIMIZATION OF A PARTICULAR REPAIR SYSTEM

2013 ◽  
Vol 30 (01) ◽  
pp. 1250042 ◽  
Author(s):  
BINFENG LI ◽  
XIAOBIN LI ◽  
WEIHONG GUO ◽  
SU WU
Keyword(s):  
Performance Analysis ◽  
Petri Net ◽  
High Speed ◽  
Real Field ◽  
Repair System ◽  
Repair Service ◽  
Stochastic Petri Net ◽  
Multiple Parameters ◽  
And Performance ◽  
Generalized Stochastic Petri Net

This paper presents a generalized stochastic Petri-net model for performance analysis and allocation optimization of a repair system with interchangeable inventory. A repair system with interchangeable-inventory is an important type of repair-service, which features components that are assembled circularly with interchangeable-component inventory. Despite improved efficiency, major difficulties in model formulation and performance analysis arise due to a complex fork/join structure and the presence of interchangeable-component inventory. In this study, by applying a generalized stochastic Petri-net to model the fork/join structure and interchangeable inventory, a system with one overhaul center and one interchangeable-component repair shop was defined in the Petri-net by places, transitions and tokens. A performance analysis with single and multiple parameters and simulation experiments was performed according to the real field data of high-speed railway locomotives overhaul. With appropriate weights on each portion of the system resources, the optimal design scenario for the allocation of a specific repair system was achieved to control the overall expenditure.

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