scholarly journals Providing Predictable Quality of Service in a Cloud-Based Web System

2021 ◽  
Vol 11 (7) ◽  
pp. 2896
Author(s):  
Krzysztof Zatwarnicki

Cloud-computing web systems and services revolutionized the web. Nowadays, they are the most important part of the Internet. Cloud-computing systems provide the opportunity for businesses to undergo digital transformation in order to improve efficiency and reduce costs. The sudden shutdown of schools and offices during the pandemic of Covid 19 significantly increased the demand for cloud solutions. Load balancing and sharing mechanisms are implemented in order to reduce the costs and increase the quality of web service. The usage of those methods with adaptive intelligent algorithms can deliver the highest and a predictable quality of service. In this article, a new HTTP request-distribution method in a two-layer architecture of a cluster-based web system is presented. This method allows for the provision of efficient processing and predictable quality by servicing requests in adopted time constraints. The proposed decision algorithms utilize fuzzy-neural models allowing service times to be estimated. This article provides a description of this new solution. It also contains the results of experiments in which the proposed method is compared with other intelligent approaches such as Fuzzy-Neural Request Distribution, and distribution methods often used in production systems.

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1400
Author(s):  
Muhammad Adnan ◽  
Jawaid Iqbal ◽  
Abdul Waheed ◽  
Noor Ul Amin ◽  
Mahdi Zareei ◽  
...  

Modern vehicles are equipped with various sensors, onboard units, and devices such as Application Unit (AU) that support routing and communication. In VANETs, traffic management and Quality of Service (QoS) are the main research dimensions to be considered while designing VANETs architectures. To cope with the issues of QoS faced by the VANETs, we design an efficient SDN-based architecture where we focus on the QoS of VANETs. In this paper, QoS is achieved by a priority-based scheduling algorithm in which we prioritize traffic flow messages in the safety queue and non-safety queue. In the safety queue, the messages are prioritized based on deadline and size using the New Deadline and Size of data method (NDS) with constrained location and deadline. In contrast, the non-safety queue is prioritized based on First Come First Serve (FCFS) method. For the simulation of our proposed scheduling algorithm, we use a well-known cloud computing framework CloudSim toolkit. The simulation results of safety messages show better performance than non-safety messages in terms of execution time.


Author(s):  
Muhammad Usman Ashraf ◽  
◽  
Sabah Arif ◽  
Abdul Basit ◽  
Malik Sheraaz Khan

Author(s):  
Mohamed M. Ould Deye ◽  
Mamadou Thiongane ◽  
Mbaye Sene

Auto-scaling is one of the most important features in Cloud computing. This feature promises cloud computing customers the ability to best adapt the capacity of their systems to the load they are facing while maintaining the Quality of Service (QoS). This adaptation will be done automatically by increasing or decreasing the amount of resources being leveraged against the workload’s resource demands. There are two types and several techniques of auto-scaling proposed in the literature. However, regardless the type or technique of auto-scaling used, over-provisioning or under-provisioning problem is often observed. In this paper, we model the auto-scaling mechanism with the Stochastic Well-formed coloured Nets (SWN). The simulation of the SWN model allows us to find the state of the system (the number of requests to be dispatched, the idle times of the started resources) from which the auto-scaling mechanism must be operated in order to minimize the amount of used resources without violating the service-level agreements (SLA).


2020 ◽  
Vol 178 ◽  
pp. 375-385
Author(s):  
Ismail Zahraddeen Yakubu ◽  
Zainab Aliyu Musa ◽  
Lele Muhammed ◽  
Badamasi Ja’afaru ◽  
Fatima Shittu ◽  
...  

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