Results 101 to 110 of about 1,233,375 (277)

Nearly periodic behavior in the overloaded G/D/s+GI queue

Stochastic Systems, 2011
Under general conditions, the number of customers in a GI/D/s+GI many-server queue at time t converges to a unique stationary distribution as t → ∞. However, simulations show that the sample paths routinely exhibit nearly periodic behavior over long time
Ward Whitt, Yunan Liu
doaj  

Does Economic Growth Drive Equitable Water and Sanitation Access? Assessing Inequality Reduction Across 64 Nations

Sustainable Development, EarlyView.
ABSTRACT This article examines whether economic growth reduces inequalities in access to water and sanitation across 64 countries over an average period of 13.5 years. Drawing on disaggregated data by income quintiles and rural–urban location, and employing ordinary least squares (OLS), two‐stage least squares (2SLS), and Seemingly Unrelated Regression
Marcos García‐López, Samara López‐Ruiz, Gabriela Cuadrado‐Quesada   +2 more
wiley   +1 more source

Predicting Runtime in Spark‐Like Systems With Allocation‐Aware Deterministic Models

Software: Practice and Experience, EarlyView.
ABSTRACT Objectives Apache Spark is widely used for distributed data processing, but accurately predicting application execution time remains challenging because performance depends on application structure, resource configuration, and executor‐allocation behavior.
Hina Tariq, Olivia Das
wiley   +1 more source

Extremes and fluid queues.

, 2006
In queueing theory, the main entity is a station where service is provided; examples include counters, call centers, elevators, and traffic lights. Customers seeking this service arrive at the system, where they wait if the service facility cannot immediately allocate the required amount of service. They depart after being served.
openaire   +3 more sources

Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions

Software: Practice and Experience, EarlyView.
ABSTRACT Context The rapid increase in cyber threats, coupled with increasingly sophisticated attack strategies and the exponential growth of data in recent years, has exposed significant limitations in classical machine learning, rule‐based, and signature‐based defense mechanisms.
Siva Sai, Ishika Goyal, Shubham Sharma, Sri Harshita Manuri, Vinay Chamola, Rajkumar Buyya   +5 more
wiley   +1 more source

An ODE for an overloaded X model involving a stochastic averaging principle

Stochastic Systems, 2011
We study an ordinary differential equation (ODE) arising as the many-server heavy-traffic fluid limit of a sequence of overloaded Markovian queueing models with two customer classes and two service pools.
Ward Whitt, Ohad Perry
doaj  

Deploying Soft Operations Research Techniques in Hybrid Modelling: The Role of Qualitative System Dynamics in Sustainability Analysis

Systems Research and Behavioral Science, EarlyView.
ABSTRACT Organisations increasingly need modelling approaches that can support sustainable development decisions across economic, environmental and social dimensions. The triple bottom line (TBL) perspective provides a useful basis for such analysis, but it also introduces modelling challenges because the relevant dimensions are often interdependent ...
Masoud Fakhimi, Navonil Mustafee, Lampros Stergioulas   +2 more
wiley   +1 more source

“Who Is Watching me?”: Recovering the Grammar of Stigma in Interaction

Symbolic Interaction, EarlyView.
This article offers a praxeological respecification of stigma. I argue that the term “stigma” is a category term and glossing device, used to gather together and stand in for a diverse range of interactional experiences, including, but not limited to, degradation, discrediting, discrimination, marginalization, and being demeaned.
Phil Hutchinson
wiley   +1 more source

Size-Aware Dispatching to Fluid Queues

ACM SIGMETRICS Performance Evaluation Review
We develop a fluid-flow model for routing problems, where fluid consists of different size particles and the task is to route the incoming fluid to n parallel servers using the size information in order to minimize the mean latency. The problem corresponds to the dispatching problem of (discrete) jobs arriving according to a ...
Runhan Xie, Esa Hyytiä, Rhonda Righter
openaire   +3 more sources

What Is the Return on Investment of Digital Engineering for Complex Systems Development Schedules? Findings From a Mixed‐Methods Case Study on the Post‐Production Design Change Processes of Navy Assets

Systems Engineering, EarlyView.
ABSTRACT Complex engineered systems routinely face schedule and cost overruns, along with poor post‐deployment performance. Both INCOSE and the U.S. Department of Defense (DoD) have championed Digital Engineering (DE) as a potential remedy, yet most of DE's purported benefits remain anecdotal, and its return on investment (ROI) remains poorly ...
Jannatul Shefa, Taylan G. Topcu
wiley   +1 more source