Proactive Auto-Scaling Algorithm (PASA) for Cloud Application

2017 ◽  
Vol 9 (3) ◽  
pp. 1-16 ◽  
Author(s):  
Mohammad Sadegh Aslanpour ◽  
Seyed Ebrahim Dashti
Keyword(s):  
User Satisfaction ◽  
Moving Average ◽  
Fibonacci Numbers ◽  
Arrival Rate ◽  
Cloud Resource ◽  
Double Exponential Smoothing ◽  
Application Hosting ◽  
The One ◽  
The Cost ◽  
Auto Scaling

Application providers (APs) leave their application hosting to cloud with the aim of reducing infrastructure purchase and maintenance costs. However, variation in the arrival rate of user application requests on the one hand, and the attractive cloud resource auto-scaling feature on the other hand, has made APs consider further savings in the cost of renting resources. Researchers generally seek to select parameters for scaling decision making, while it seems that analysis of the parameter history is more effective. This paper presents a proactive auto-scaling algorithm (PASA) equipped with a heuristic predictor. The predictor analyzes history with the help of the following techniques: (1) double exponential smoothing - DES, (2) weighted moving average - WMA and (3) Fibonacci numbers. The results of PASA simulation in CloudSim is indicative of its effectiveness in a way that the algorithm can reduce the AP's cost while maintaining web user satisfaction.

scholarly journals Dynamic Pricing for Resource Consumption in Cloud Service

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Bin Cao ◽  
Kai Wang ◽  
Jinting Xu ◽  
Chenyu Hou ◽  
Jing Fan ◽  
...  
Keyword(s):  
Dynamic Pricing ◽  
Service Providers ◽  
Cloud Service ◽  
Resource Consumption ◽  
Pricing Model ◽  
Cloud Resource ◽  
The One ◽  
The Cost ◽  
Demand Service ◽  
Cloud Resources

This paper studies dynamic pricing for cloud service where different resources are consumed by different users. The traditional cloud resource pricing models can be divided into two categories: on-demand service and reserved service. The former only takes the using time into account and is unfair for the users with long using time and little concurrency. The latter charges the same price to all the users and does not consider the resource consumption of users. Therefore, in this paper, we propose a flexible dynamic pricing model for cloud resources, which not only takes into account the occupying time and resource consumption of different users but also considers the maximal concurrency of resource consumption. As a result, on the one hand, this dynamic pricing model can help users save the cost of cloud resources. On the other hand, the profits of service providers are guaranteed. The key of the pricing model is how to efficiently calculate the maximal concurrency of resource consumption since the cost of providers is dynamically varied based on the maximal concurrency. To support this function in real time, we propose a data structure based on the classical B+ tree and the implementation for its corresponding basic operations like insertion, deletion, split, and query. Finally, the experiment results show that we can complete the dynamic pricing query on 10 million cloud resource usage records within 0.2 seconds on average.

scholarly journals adPerf

2021 ◽  
Vol 5 (1) ◽  
pp. 1-26
Author(s):  
Behnam Pourghassemi ◽  
Jordan Bonecutter ◽  
Zhou Li ◽  
Aparna Chandramowlishwaran
Keyword(s):  
User Satisfaction ◽  
Online Advertising ◽  
Third Party ◽  
Privacy And Security ◽  
Fine Grained ◽  
News Websites ◽  
Web Ads ◽  
The One ◽  
The Cost ◽  
The Web

Monetizing websites and web apps through online advertising is widespread in the web ecosystem, creating a billion-dollar market. This has led to the emergence of a vast network of tertiary ad providers and ad syndication to facilitate this growing market. Nowadays, the online advertising ecosystem forces publishers to integrate ads from these third-party domains. On the one hand, this raises several privacy and security concerns that are actively being studied in recent years. On the other hand, the ability of today's browsers to load dynamic web pages with complex animations and Javascript has also transformed online advertising. This can have a significant impact on webpage performance. The latter is a critical metric for optimization since it ultimately impacts user satisfaction. Unfortunately, there are limited literature studies on understanding the performance impacts of online advertising which we argue is as important as privacy and security. In this paper, we apply an in-depth and first-of-a-kind performance evaluation of web ads. Unlike prior efforts that rely primarily on adblockers, we perform a fine-grained analysis on the web browser's page loading process to demystify the performance cost of web ads. We aim to characterize the cost by every component of an ad, so the publisher, ad syndicate, and advertiser can improve the ad's performance with detailed guidance. For this purpose, we develop a tool, adPerf, for the Chrome browser that classifies page loading workloads into ad-related and main-content at the granularity of browser activities. Our evaluations show that online advertising entails more than 15% of browser page loading workload and approximately 88% of that is spent on JavaScript. On smartphones, this additional cost of ads is 7% lower since mobile pages include fewer and well-optimized ads. We also track the sources and delivery chain of web ads and analyze performance considering the origin of the ad contents. We observe that 2 of the well-known third-party ad domains contribute to 35% of the ads performance cost and surprisingly, top news websites implicitly include unknown third-party ads which in some cases build up to more than 37% of the ads performance cost.

scholarly journals A Study on the Feasibility of Anaerobic Co-Digestion of Raw Cheese Whey with Coffee Pulp Residues

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3611
Author(s):  
Sandra Gonzalez-Piedra ◽  
Héctor Hernández-García ◽  
Juan M. Perez-Morales ◽  
Laura Acosta-Domínguez ◽  
Juan-Rodrigo Bastidas-Oyanedel ◽  
...  
Keyword(s):  
Methane Production ◽  
Kinetic Models ◽  
Cheese Whey ◽  
Maximum Yield ◽  
Gompertz Model ◽  
Coffee Pulp ◽  
The One ◽  
The Cost ◽  
Best Fit ◽  
Cheese Production

In this paper, a study on the feasibility of the treatment of raw cheese whey by anaerobic co-digestion using coffee pulp residues as a co-substrate is presented. It considers raw whey generated in artisanal cheese markers, which is generally not treated, thus causing environmental pollution problems. An experimental design was carried out evaluating the effect of pH and the substrate ratio on methane production at 35 °C (i.e., mesophilic conditions). The interaction of the parameters on the co-substrate degradation and the methane production was analyzed using a response surface analysis. Furthermore, two kinetic models were proposed (first order and modified Gompertz models) to determine the dynamic profiles of methane yield. The results show that co-digestion of the raw whey is favored at pH = 6, reaching a maximum yield of 71.54 mLCH4 gVSrem−1 (31.5% VS removed) for raw cheese whey and coffee pulp ratio of 1 gVSwhey gVSCoffe−1. The proposed kinetic models successfully fit the experimental methane production data, the Gompertz model being the one that showed the best fit. Then, the results show that anaerobic co-digestion can be used to reduce the environmental impact of raw whey. Likewise, the methane obtained can be integrated into the cheese production process, which could contribute to reducing the cost per energy consumption.

scholarly journals Electoral Incentives and the Allocation of Public Funds

2020 ◽  
Author(s):  
Frederico Finan ◽  
Maurizio Mazzocco
Keyword(s):  
Electoral System ◽  
Policy Reforms ◽  
Public Funds ◽  
Term Limit ◽  
The Public ◽  
Public Projects ◽  
Electoral Incentives ◽  
Using Data ◽  
The One ◽  
The Cost

Abstract Politicians allocate public resources in ways that maximize political gains, and potentially at the cost of lower welfare. In this paper, we quantify these welfare costs in the context of Brazil’s federal legislature, which grants its members a budget to fund public projects within their states. Using data from the state of Roraima, we estimate a model of politicians’ allocation decisions and find that 26.8% of the public funds allocated by legislators are distorted relative to a social planner’s allocation. We then use the model to simulate three potential policy reforms to the electoral system: the adoption of approval voting, imposing a one-term limit, and redistricting. We find that a one-term limit and redistricting are both effective at reducing distortions. The one-term limit policy, however, increases corruption, which makes it a welfare-reducing policy.

scholarly journals Choosing between identification schemes in noisy-news models

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Joshua C. C. Chan ◽  
Eric Eisenstat ◽  
Gary Koop
Keyword(s):  
Bayesian Methods ◽  
Moving Average ◽  
Autoregressive Moving Average ◽  
Structural Shocks ◽  
Vector Autoregressive ◽  
Identification Scheme ◽  
Identification Schemes ◽  
The One ◽  
Small Models ◽  
Structural Vector

AbstractThis paper is about identifying structural shocks in noisy-news models using structural vector autoregressive moving average (SVARMA) models. We develop a new identification scheme and efficient Bayesian methods for estimating the resulting SVARMA. We discuss how our identification scheme differs from the one which is used in existing theoretical and empirical models. Our main contributions lie in the development of methods for choosing between identification schemes. We estimate specifications with up to 20 variables using US macroeconomic data. We find that our identification scheme is preferred by the data, particularly as the size of the system is increased and that noise shocks generally play a negligible role. However, small models may overstate the importance of noise shocks.

scholarly journals A MEAN FIELD GAME ANALYSIS OF SIR DYNAMICS WITH VACCINATION

2020 ◽  
pp. 1-18
Author(s):  
Josu Doncel ◽  
Nicolas Gast ◽  
Bruno Gaujal
Keyword(s):  
Mean Field ◽  
Vaccination Strategy ◽  
Game Analysis ◽  
Total Cost ◽  
Mean Field Game ◽  
Vaccination Behavior ◽  
Switching Curve ◽  
The One ◽  
The Cost ◽  
Vaccination Period

We analyze a mean field game model of SIR dynamics (Susceptible, Infected, and Recovered) where players choose when to vaccinate. We show that this game admits a unique mean field equilibrium (MFE) that consists in vaccinating at a maximal rate until a given time and then not vaccinating. The vaccination strategy that minimizes the total cost has the same structure as the MFE. We prove that the vaccination period of the MFE is always smaller than the one minimizing the total cost. This implies that, to encourage optimal vaccination behavior, vaccination should always be subsidized. Finally, we provide numerical experiments to study the convergence of the equilibrium when the system is composed by a finite number of agents ( $N$ ) to the MFE. These experiments show that the convergence rate of the cost is $1/N$ and the convergence of the switching curve is monotone.

Machine Learning and statistic predictive modeling for road traffic flow

2021 ◽  
Vol 03 (01) ◽  
pp. 17-24
Author(s):  
Nadia Slimani ◽  
Ilham Slimani ◽  
Nawal Sbiti ◽  
Mustapha Amghar
Keyword(s):  
Road Traffic ◽  
Smart Cities ◽  
Moving Average ◽  
Ann Model ◽  
Important Place ◽  
Traffic Forecasting ◽  
Absolute Relative Error ◽  
History Of ◽  
The One ◽  
Motorized Vehicles

Traffic forecasting is a research topic debated by several researchers affiliated to a range of disciplines. It is becoming increasingly important given the growth of motorized vehicles on the one hand, and the scarcity of lands for new transportation infrastructure on the other. Indeed, in the context of smart cities and with the uninterrupted increase of the number of vehicles, road congestion is taking up an important place in research. In this context, the ability to provide highly accurate traffic forecasts is of fundamental importance to manage traffic, especially in the context of smart cities. This work is in line with this perspective and aims to solve this problem. The proposed methodology plans to forecast day-by-day traffic stream using three different models: the Multilayer Perceptron of Artificial Neural Networks (ANN), the Seasonal Autoregressive Integrated Moving Average (SARIMA) and the Support Machine Regression (SMOreg). Using those three models, the forecast is realized based on a history of real traffic data recorded on a road section over 42 months. Besides, a recognized traffic manager in Morocco provides this dataset; the performance is then tested based on predefined criteria. From the experiment results, it is clear that the proposed ANN model achieves highest prediction accuracy with the lowest absolute relative error of 0.57%.

Hiding Data in Plain Sight: Towards Provably Unbreakable Encryption with Short Secret Keys and One-Way Functions

2021 ◽  
Author(s):  
Mircea-Adrian Digulescu
Keyword(s):  
Encryption Scheme ◽  
Secret Key ◽  
Small Probability ◽  
Random Data ◽  
Computing Power ◽  
Plain Text ◽  
Secret Keys ◽  
The One ◽  
One Way Function ◽  
The Cost

It has long been known that cryptographic schemes offering provably unbreakable security exist, namely the One Time Pad (OTP). The OTP, however, comes at the cost of a very long secret key - as long as the plain-text itself. In this paper we propose an encryption scheme which we (boldly) claim offers the same level of security as the OTP, while allowing for much shorter keys, of size polylogarithmic in the computing power available to the adversary. The Scheme requires a large sequence of truly random words, of length polynomial in the both plain-text size and the logarithm of the computing power the adversary has. We claim that it ensures such an attacker cannot discern the cipher output from random data, except with small probability. We also show how it can be adapted to allow for several plain-texts to be encrypted in the same cipher output, with almost independent keys. Also, we describe how it can be used in lieu of a One Way Function.

scholarly journals Farm Gate Prices for Non-Varietal Wine in Argentina: A Multilevel Comparison of the Prices Paid by Cooperatives and Investor-Oriented Firms

2017 ◽  
Vol 16 (1) ◽  
Author(s):  
Agustina Malvido Perez Carletti ◽  
Markus Hanisch ◽  
Jens Rommel ◽  
Murray Fulton
Keyword(s):  
Multilevel Regression ◽  
Data Set ◽  
Unique Data ◽  
Market Shares ◽  
Price Effects ◽  
Theoretical Predictions ◽  
The One ◽  
The Cost ◽  
Price Differences ◽  
Multilevel Regression Model

AbstractIn this paper, we use a unique data set of the prices paid to farmers in Argentina for grapes to examine the prices paid by non-varietal wine processing cooperatives and investor-oriented firms (IOFs). Motivated by contrasting theoretical predictions of cooperative price effects generated by the yardstick of competition and property rights theories, we apply a multilevel regression model to identify price differences at the transaction level and the departmental level. On average, farmers selling to cooperatives receive a 3.4 % lower price than farmers selling to IOFs. However, we find cooperatives pay approximately 2.4 % more in departments where cooperatives have larger market shares. We suggest that the inability of cooperatives to pay a price equal to or greater than the one paid by IOFs can be explained by the market structure for non-varietal wine in Argentina. Specifically, there is evidence that cooperative members differ from other farmers in terms of size, assets and the cost of accessing the market. We conclude that the analysis of cooperative pricing cannot solely focus on the price differential between cooperatives and IOFs, but instead must consider other factors that are important to the members.

The ‘Pistola’ of Cerveri de Girona

Traditio ◽  
1948 ◽  
Vol 6 ◽  
pp. 161-185
Author(s):  
Kurt Lewent
Keyword(s):  
The Other ◽  
Love Affair ◽  
Other Hand ◽  
Good Taste ◽  
Moral Argumentation ◽  
The Subject ◽  
Way Of Thinking ◽  
The One ◽  
The Cost ◽  
Troubadour Poetry

Cerveri was decidedly no poetical genius, and often enough he follows the trodden paths of troubadour poetry. However, there is no denying that again and again he tries to escape that poetical routine. In many cases these attempts result in odd and eccentric compositions, where the unusual is reached at the cost of good taste and poetical values. On the other hand, it must be admitted that Cerveri's efforts in this respect were not always futile. His is, e.g. an amusing satire upon bad women. One of his love songs, characteristically called libel by the MS (Sg), assumes the form of a complaint submitted to the king as the supreme earthly judge, in which the defendant is the lady whose charms torture the lover and have made him a prisoner. This poem combines the traditional praise of the beloved and a flattery addressed to the king. Its slightly humoristic tone is also found in a song entitled lo vers del vassayll leyal. Here Cerveri, basing himself on a certain legend connected with St. Mark, gives the king advice in his love affair. Again the poet kills two birds with one stone, flattering the sovereign and pointing, for obvious purposes, to his own poverty. The latter is the only topic of a remarkably personal poem in which the author complains bitterly that, while many of his playmates have become rich in later years, the only wealth he himself did amass were the chans gays and sonetz agradans which he composed for other people to enjoy. Cerveri even tries to renew the traditional genre of the chanson de la mal mariée by adding motifs of—presumably—his own invention. This tendency towards a more independent way of thinking and greater originality in its poetical presentation could not be better illustrated than by the two poems which the MS calls Lo vers de la terra de Preste Johan and Pistola The one puts the poet's moral argumentation against the background of the medieval legend of Prester John, the other, which forms the subject of the present study, sets its teachings in a still more solemn framework, the liturgy of the Mass.

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