scholarly journals Novel Heavy-Traffic Regimes for Large-Scale Service Systems

2015 ◽  
Vol 75 (2) ◽  
pp. 787-812 ◽  
Author(s):  
A.J.E.M. Janssen ◽  
J.S.H. van Leeuwaarden ◽  
B.W.J. Mathijsen
Keyword(s):  
Large Scale ◽  
Heavy Traffic ◽  
Service Systems

INFINITE-SERVER QUEUES WITH BATCH ARRIVALS AND DEPENDENT SERVICE TIMES

2012 ◽  
Vol 26 (2) ◽  
pp. 197-220 ◽  
Author(s):  
Guodong Pang ◽  
Ward Whitt
Keyword(s):  
Large Scale ◽  
Heavy Traffic ◽  
Arrival Rate ◽  
Arrival Process ◽  
Regularity Conditions ◽  
Time Varying ◽  
Performance Impact ◽  
Batch Arrivals ◽  
Infinite Server ◽  
Service Times

Motivated by large-scale service systems, we consider an infinite-server queue with batch arrivals, where the service times are dependent within each batch. We allow the arrival rate of batches to be time varying as well as constant. As regularity conditions, we require that the batch sizes be i.i.d. and independent of the arrival process of batches, and we require that the service times within different batches be independent. We exploit a recently established heavy-traffic limit for the number of busy servers to determine the performance impact of the dependence among the service times. The number of busy servers is approximately a Gaussian process. The dependence among the service times does not affect the mean number of busy servers, but it does affect the variance of the number of busy servers. Our approximations quantify the performance impact upon the variance. We conduct simulations to evaluate the heavy-traffic approximations for the stationary model and the model with a time-varying arrival rate. In the simulation experiments, we use the Marshall–Olkin multivariate exponential distribution to model dependent exponential service times within a batch. We also introduce a class of Marshall–Olkin multivariate hyperexponential distributions to model dependent hyper-exponential service times within a batch.

scholarly journals Accident Identification and Alerting System

2021 ◽  
pp. 766-774
Author(s):  
Dr. Pradnya Maturkar ◽  
Kunal Dudhe ◽  
Krishna Roy
Keyword(s):  
Embedded System ◽  
Traffic Control ◽  
Large Scale ◽  
Traffic Accidents ◽  
Emergency Services ◽  
Detection System ◽  
Human Life ◽  
Heavy Traffic ◽  
Significant Loss ◽  
Alerting System

Vehicle use is expanding dramatically, which means that vehicle-related risks are increasing as well. High speeds, driving while inebriated, distracted driving, overstress, and electronic gadgets are the leading causes of accidents. This work is about an accident detection system that occurs as a result of carelessness on the part of the driver. This introduces an accident alerting system, which notifies the driver of the vehicle. When an individual seems unable to control his or her car, an accident happens. This technology will transmit information to the registered mobile number once the car is involved in an accident. Our lives have been made easier by the rapid advancement of technology and infrastructure. The advancement of technology has also increased transportation risks, and road accidents are becoming more common, resulting in significant loss of life and property due to inadequate emergency services. Despite the presence of so many contemporary equipment in the field of vehicle design, large-scale road lane design and heavy traffic control mishaps do occur. Accidents are posing a greater threat to human life, with traffic accidents being the most common. Many people die as a result of medical services and family members failing to receive accident information in a timely manner. Any type of mishap that is detected is automatically transmitted to the relevant destination as an alert. When a vehicle's accident detecting equipment recognizes an accident, it sends SMS/ messages to the driver's family, police station, ambulance, and nearby hospital's pre-installed numbers. This is an embedded system. It may be used to track and retrieve the exact location of any car that has been involved in an accident. Using the Global Positioning System (GPS) and sensors, we were able to avoid an accident.

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