scholarly journals Profit Optimization in SLA-Aware Cloud Services with a Finite Capacity Queuing Model

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Yi-Ju Chiang ◽  
Yen-Chieh Ouyang

Cloud computing realizes a utility computing paradigm by offering shared resources through an Internet-based computing. However, how a system control can enhance profit and simultaneously satisfy the service level agreements (SLAs) has become one of the major interests for cloud providers. In this paper, a cloud server farm provided with finite capacity is modeled as anM/M/R/Kqueuing system. Revenue losses are estimated according to the system controls and impatient customer behaviors. Three important issues are solved in this paper. First, a profit function is developed in which both the system blocking loss and the user abandonment loss are evaluated in total revenue. A tradeoff between meeting system performances and reducing operating costs is conducted. Second, the effects of system capacity control and utilization on various performances of waiting time, loss probability, and final arrival rate are demonstrated. Finally, the proposed optimal profit control (OPC) policy allows a cloud provider to make the optimal decision in the number of servers and system capacity, so as to maximize profit. As compared to a system without applying the OPC policy, enhancing providers’ profit and improving system performances can be obtained.

2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Diana Khairani Sofyan ◽  
Sri Meutia

Gas stations Mawaddah Is one of the gas stations located in the Village Batuphat East Lhokseumawe. The gas station has 5 oil pumps consisting of premium with two pumps, diesel consists of two pumps, and pertamax consists of one pump. Preliminary data have been made regarding the arrival rate of vehicles in each pump, which is a two-wheeled premium filling pump of 195 vehicles, four or more 166 wheels or four wheels filling pumps, four or more diesel fuel pumps of 156 and a feeding pump of 138 vehicles. High vehicle arrival rate resulted in queue. To calculate the level of service has never been done so it is not known the maximum time for service on each pump. The research method used is queuing model related to arrival rate and service level, with result of research which obtained is vehicle arrival rate at each pump that is 2 wheel of premium gasoline pump is 2.59 minutes. The premium 4 wheels charging pump is 6.98. The 4 wheelers diesel fuel pump is 5.97 minutes and the first charging pump is 6.65 minutes with the facility number 1. Vehicle service rates of premium 2 and 4 wheelers are 15.52 minutes and 14.11 minutes, 4 wheel diesel fuel pump is 14.21 minutes and the first feed pump is 13.55 minutes with scenario design on each pump is Scenario 1 with 2 pumps, Probability of medium system empty 0.87500, Number of subscribers in the system and number of customers waiting in the queue of each 1 customer, the average customer time in the system 0.06696 minutes and waiting time as long as the customer in the queue 0.00030 minutes.Keywords: Queue, facility, arrival rate, service rate.


Author(s):  
Adil Maarouf ◽  
Mahmoud El Hamlaoui ◽  
Abderrahim Marzouk ◽  
Abdelkrim Haqiq

Establishing and monitoring SLA violations in real-time has become a critical issue for Cloud Computing. In this paper the authors investigate this issue and propose a model to express the SLA contract requirements using Model Driven Engineering (MDE), as a mean for establishing service level agreements between a cloud provider and cloud customer in the context of a particular service provision. The participation of a Trusted Third Party (TTP) may be necessary in order to resolve conflicts between prospective signatories, likewise to monitor SLA violations in real-time in the goal to ensure online monitoring cloud services and provide better than best-effort behavior for clouds. The main focus of this work is firstly to use MDE technology for the creation of the SLA contract and then to integrate TTP that should be able to apply an advanced penalty model that guarantees the performance and the reliability of the Cloud.


2019 ◽  
Vol 11 (7) ◽  
pp. 142 ◽  
Author(s):  
Loretta Mastroeni ◽  
Alessandro Mazzoccoli ◽  
Maurizio Naldi

Service Level Agreements are employed to set availability commitments in cloud services. When a violation occurs as in an outage, cloud providers may be called to compensate customers for the losses incurred. Such compensation may be so large as to erode cloud providers’ profit margins. Insurance may be used to protect cloud providers against such a danger. In this paper, closed formulas are provided through the expected utility paradigm to set the insurance premium under different outage models and QoS metrics (no. of outages, no. of long outages, and unavailability). When the cloud service is paid through a fixed fee, we also provide the maximum unit compensation that a cloud provider can offer so as to meet constraints on its profit loss. The unit compensation is shown to vary approximately as the inverse square of the service fee.


2018 ◽  
Vol 7 (3.27) ◽  
pp. 223
Author(s):  
A Banushri ◽  
R A. Karthika

To enjoy the full benefits of cloud computing, it is necessary to have built-in security, privacy, compliance and legal requirements for the cloud implementation and use. Each industry has its own risk levels that it could work within. A company, which is planning to use public cloud services, should be conscious of the regulations and industry risks and need to monitor it and abide by the same. This is due to multi-tenant and open to all nature of public cloud. A thorough risk analysis must be done initially with a public cloud provider. The main objective is to identify the existing vulnerabilities and to implement the measures to counter those threats. There are a variety of risks such as vendor lock-in, non-compliance, poor provisioning, unauthorized access, loss of control, Service Level Agreement (SLA) violations, Internet attacks, etc. To alleviate the risks, there are several measures that could be deployed. This paper deals with mitigation mechanism, security requirements and various risks associated with public cloud.  


2021 ◽  
Vol 10 (2) ◽  
pp. 34
Author(s):  
Alessio Botta ◽  
Jonathan Cacace ◽  
Riccardo De Vivo ◽  
Bruno Siciliano ◽  
Giorgio Ventre

With the advances in networking technologies, robots can use the almost unlimited resources of large data centers, overcoming the severe limitations imposed by onboard resources: this is the vision of Cloud Robotics. In this context, we present DewROS, a framework based on the Robot Operating System (ROS) which embodies the three-layer, Dew-Robotics architecture, where computation and storage can be distributed among the robot, the network devices close to it, and the Cloud. After presenting the design and implementation of DewROS, we show its application in a real use-case called SHERPA, which foresees a mixed ground and aerial robotic platform for search and rescue in an alpine environment. We used DewROS to analyze the video acquired by the drones in the Cloud and quickly spot signs of human beings in danger. We perform a wide experimental evaluation using different network technologies and Cloud services from Google and Amazon. We evaluated the impact of several variables on the performance of the system. Our results show that, for example, the video length has a minimal impact on the response time with respect to the video size. In addition, we show that the response time depends on the Round Trip Time (RTT) of the network connection when the video is already loaded into the Cloud provider side. Finally, we present a model of the annotation time that considers the RTT of the connection used to reach the Cloud, discussing results and insights into how to improve current Cloud Robotics applications.


Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lantian Li ◽  
Bahareh Pahlevanzadeh

PurposeCloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and compliance. This paper aims to maximize the covered human resource (HR) vulnerabilities and minimize the security costs in the enterprise cloud using a fuzzy-based method and firefly optimization algorithm.Design/methodology/approachCloud computing provides a platform to improve the quality and availability of IT resources. It changes the way people communicate and conduct their businesses. However, some security concerns continue to derail the expansion of cloud-based systems into all parts of human life. Enterprise cloud security is a vital component in ensuring the long-term stability of cloud technology by instilling trust. In this paper, a fuzzy-based method and firefly optimization algorithm are suggested for optimizing HR vulnerabilities while mitigating security expenses in organizational cloud environments. MATLAB is employed as a simulation tool to assess the efficiency of the suggested recommendation algorithm. The suggested approach is based on the firefly algorithm (FA) since it is swift and reduces randomization throughout the lookup for an optimal solution, resulting in improved performance.FindingsThe fuzzy-based method and FA unveil better performance than existing met heuristic algorithms. Using a simulation, all the results are verified. The study findings showed that this method could simulate complex and dynamic security problems in cloud services.Practical implicationsThe findings may be utilized to assist the cloud provider or tenant of the cloud infrastructure system in taking appropriate risk mitigation steps.Originality/valueUsing a fuzzy-based method and FA to maximize the covered HR vulnerabilities and minimize the security costs in the enterprise cloud is the main novelty of this paper.


2020 ◽  
Vol 17 (12) ◽  
pp. 5296-5306
Author(s):  
N. Keerthana ◽  
Viji Vinod ◽  
Sudhakar Sengan

Data in the Cloud, which applies to data as a cloud service provider (CSP), transmits stores, or manages it. The company will enforce the same definition of data usage while the data is resident within the enterprise and thus extend the required cryptographic security criteria to data collected, exchanged, or handled by CSP. The CSP Service Level Agreements cannot override the cryptographic access measures. When the data is transferred securely to CSP, it can be securely collected, distributed, and interpreted. Data at the rest position applies to data as it is processed internally in organized and in the unstructured ways like databases and file cabinets. The Data at the Rest example includes the use of cryptography for preserving the integrity of valuable data when processed. For cloud services, computing takes multiple forms from recording units, repositories, and many unstructured items. This paper presents a secure model for Data at rest. The TF-Sec model suggested is planned for use with Slicing, Tokenization, and Encryption. The model encrypts the given cloud data using AES 256 encryption, and then the encrypted block is sliced into the chunks of data fragments using HD-Slicer. Then it applies tokenization algorithm TKNZ to each chunk of data, applies erasure coding technique to tokens, applies the data dispersion technique to scramble encrypted data fragments, and allocates to storage nodes of the multiple CSP. In taking the above steps, this study aims to resolve the cloud security problems found and to guarantee the confidentiality of their data to cloud users due to encryption of data fragments would be of little benefit to a CSP.


2019 ◽  
Vol 2 (1) ◽  
pp. 1-12
Author(s):  
Doddy - Lombardo ◽  
Edward Rosyidi

ABSTRACTION   PT Jasa Marga (Persero), Tbk is a company engaged in the development and movement of toll roads having a Current, Safe and Comfortable Quality Policy increasingly demanded to improve the quality of its services. The number of substations that have been repaired at the Kuningan Toll Gate 2 against 4 substations cannot receive currents that increase during rush hour. The queue exceeds the service standards set by the government for a maximum of 5 vehicles for each substation. In this study used the FIFO Queue Model and Distribution testing using the Promodel 7.0 Version of Student Software to find out the distribution of arrival rate and service level data. To test the average value is used the One-way ANOVA test which was previously carried out also the test of adequacy, uniformity and normality of the data. Data collection is taken when a long queue is carried out at the Toll Gate. After passing the test, the next data ? is equal to 2,004 vehicles / hour and ? is = 417 vehicles / hour with Service Time = 8.63 seconds / vehicle, if it is done with Queuing Theory. Results Processing data with queuing theory obtained N (optimal) = 6 and n (Number of vehicles in the system) = 5 vehicles, q (Number of vehicles in queue) = 4 vehicles, d (Time of vehicle in system) = 43.37 seconds, w (Time of vehicle in queue) = 34.74 seconds. The results of data preparation are further processed to obtain optimal Employee Scheduling using tables so that there will be 3 employees in shift 1, 9 in Shift 2 and 2 in shift 3. on weekdays and 3 people on shift 1, 3 on Shift 2 and 2 on shift 3 on holidays. Keywords: Queue Method, Toll Gate, Planning, Optimization                                                                                     


2013 ◽  
pp. 814-834
Author(s):  
Hassan Takabi ◽  
James B.D. Joshi

Cloud computing paradigm is still an evolving paradigm but has recently gained tremendous momentum due to its potential for significant cost reduction and increased operating efficiencies in computing. However, its unique aspects exacerbate security and privacy challenges that pose as the key roadblock to its fast adoption. Cloud computing has already become very popular, and practitioners need to provide security mechanisms to ensure its secure adoption. In this chapter, the authors discuss access control systems and policy management in cloud computing environments. The cloud computing environments may not allow use of a single access control system, single policy language, or single management tool for the various cloud services that it offers. Currently, users must use diverse access control solutions available for each cloud service provider to secure data. Access control policies may be composed in incompatible ways because of diverse policy languages that are maintained separately at every cloud provider. Heterogeneity and distribution of these policies pose problems in managing access policy rules for a cloud environment. In this chapter, the authors discuss challenges of policy management and introduce a cloud based policy management framework that is designed to give users a unified control point for managing access policies to control access to their resources no matter where they are stored.


Author(s):  
Ovunc Kocabas ◽  
Regina Gyampoh-Vidogah ◽  
Tolga Soyata

This chapter describes the concepts and cost models used for determining the cost of providing cloud services to mobile applications using different pricing models. Two recently implemented mobile-cloud applications are studied in terms of both the cost of providing such services by the cloud operator, and the cost of operating them by the cloud user. Computing resource requirements of both applications are identified and worksheets are presented to demonstrate how businesses can estimate the operational cost of implementing such real-time mobile cloud applications at a large scale, as well as how much cloud operators can profit from providing resources for these applications. In addition, the nature of available service level agreements (SLA) and the importance of quality of service (QoS) specifications within these SLAs are emphasized and explained for mobile cloud application deployment.


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