Stability in Web Server Performance with Heavy-Tailed Distribution

2005 ◽  
pp. 575-581 ◽  
Author(s):  
Takuo Nakashima ◽  
Mamoru Tsuichihara
Keyword(s):  
Web Server ◽  
Heavy Tailed Distribution ◽  
Heavy Tailed ◽  
Web Server Performance

scholarly journals A Bias-Reduced Estimator for the Mean of a Heavy-Tailed Distribution with an Infinite Second Moment

2012 ◽  
Author(s):  
Brahim Brahimi ◽  
Djamel Meraghni ◽  
Necir Abdelhakim ◽  
Yahia Djabrane
Keyword(s):  
Second Moment ◽  
Heavy Tailed Distribution ◽  
The Mean ◽  
Heavy Tailed

scholarly journals A New Right-Skewed Upside Down Bathtub Shaped Heavy-tailed Distribution and its Applications

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Sandeep Kumar Maurya ◽  
Sanjay K Singh ◽  
Umesh Singh
Keyword(s):  
Maximum Likelihood ◽  
Real Data ◽  
Statistical Properties ◽  
New Right ◽  
Data Sets ◽  
Proposed Model ◽  
Heavy Tailed Distribution ◽  
Heavy Tailed

A one parameter right skewed, upside down bathtub type, heavy-tailed distribution is derived. Various statistical properties and maximum likelihood approaches for estimation purpose are studied. Five different real data sets with four different models are considered to illustrate the suitability of the proposed model.

scholarly journals Web Server Performance Improvement Using Dynamic Load Balancing Techniques: A Review

2021 ◽  
pp. 47-62
Author(s):  
Ibrahim Mahmood Ibrahim ◽  
Siddeeq Y. Ameen ◽  
Hajar Maseeh Yasin ◽  
Naaman Omar ◽  
Shakir Fattah Kak ◽  
...  
Keyword(s):  
Load Balancing ◽  
Response Time ◽  
Performance Improvement ◽  
Web Server ◽  
Dynamic Load Balancing ◽  
The Internet ◽  
Web Servers ◽  
Web Server Performance ◽  
Server Clusters ◽  
The Web

Today, web services rapidly increased and are accessed by many users, leading to massive traffic on the Internet. Hence, the web server suffers from this problem, and it becomes challenging to manage the total traffic with growing users. It will be overloaded and show response time and bottleneck, so this massive traffic must be shared among several servers. Therefore, the load balancing technologies and server clusters are potent methods for dealing with server bottlenecks. Load balancing techniques distribute the load among servers in the cluster so that it balances all web servers. The motivation of this paper is to give an overview of the several load balancing techniques used to enhance the efficiency of web servers in terms of response time, throughput, and resource utilization. Different algorithms are addressed by researchers and get good results like the pending job, and IP hash algorithms achieve better performance.

Heavy-tailed distributions for building stock data

2018 ◽  
Vol 46 (7) ◽  
pp. 1281-1296 ◽  
Author(s):  
Patrick Erik Bradley ◽  
Martin Behnisch
Keyword(s):  
Power Law ◽  
Building Stock ◽  
Underlying Distribution ◽  
Large Cities ◽  
Statistical Framework ◽  
Heavy Tailed Distributions ◽  
Heavy Tailed Distribution ◽  
Event Histories ◽  
Heavy Tailed ◽  
Log Normal

The question of inferring the owner of a set of building stocks (e.g. from which country the buildings are taken) from building-related quantities like number of buildings or types of building event histories necessitates the knowledge of their distributions in order to compare them. If the distribution function is a power law, then a version of the 80/20 rule can be applied to describe the variable. This distribution is an example of a heavy-tailed distribution; another example is the log-normal distribution. Heavy-tailed distributions have the property that studying the effects of the few large values already yields most of the overall effect of the whole quantity. For example, if reducing the CO2 emissions of the buildings of a country is the issue, then in case of a heavy-tailed distribution, only the effects of the relatively few large cities need to be considered. It is shown that the number of buildings in German municipalities or counties or the number of building-related event histories of a certain vanished building stock follow a heavy-tailed distribution and give evidence for the type of underlying distribution. The methodology used is a recent statistical framework for discerning power law and other heavy-tailed distributions in empirical data.

scholarly journals RPM-Oriented Query Rewriting Framework for E-commerce Keyword-Based Sponsored Search (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13769-13770
Author(s):  
Xiuying Chen ◽  
Daorui Xiao ◽  
Shen Gao ◽  
Guojun Liu ◽  
Wei Lin ◽  
...  
Keyword(s):  
Statistical Models ◽  
Large Scale ◽  
Query Rewriting ◽  
Sponsored Search ◽  
Search System ◽  
Oriented Sample ◽  
Search Models ◽  
Proposed Model ◽  
Heavy Tailed Distribution ◽  
Heavy Tailed

Sponsored search optimizes revenue and relevance, which is estimated by Revenue Per Mille (RPM). Existing sponsored search models are all based on traditional statistical models, which have poor RPM performance when queries follow a heavy-tailed distribution. Here, we propose an RPMoriented Query Rewriting Framework (RQRF) which outputs related bid keywords that can yield high RPM. RQRF embeds both queries and bid keywords to vectors in the same implicit space, converting the rewriting probability between each query and keyword to the distance between the two vectors. For label construction, we propose an RPM-oriented sample construction method, labeling keywords based on whether or not they can lead to high RPM. Extensive experiments are conducted to evaluate performance of RQRF. In a one month large-scale real-world traffic of e-commerce sponsored search system, the proposed model significantly outperforms traditional baseline.

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