On optimal service capacity allocation policy in an advance selling environment in continuous time

2010 ◽  
Vol 203 (2) ◽  
pp. 505-512 ◽  
Author(s):  
Hani I. Mesak ◽  
Hongkai Zhang ◽  
Joe M. Pullis
Keyword(s):  
Continuous Time ◽  
Capacity Allocation ◽  
Service Capacity ◽  
Advance Selling ◽  
Allocation Policy ◽  
Optimal Service

scholarly journals Optimal service-capacity allocation in a loss system

2015 ◽  
Vol 62 (2) ◽  
pp. 81-97 ◽  
Author(s):  
Refael Hassin ◽  
Yair Y. Shaki ◽  
Uri Yovel
Keyword(s):  
Capacity Allocation ◽  
Service Capacity ◽  
Loss System ◽  
Optimal Service

Dynamic Scheduling of Multiclass Many-Server Queues with Abandonment: The Generalized cμ/h Rule

2020 ◽  
Vol 68 (4) ◽  
pp. 1218-1230
Author(s):  
Zhenghua Long ◽  
Nahum Shimkin ◽  
Hailun Zhang ◽  
Jiheng Zhang
Keyword(s):  
Queue Length ◽  
Dynamic Scheduling ◽  
Cost Functions ◽  
Hazard Rates ◽  
Service Capacity ◽  
Allocation Policy ◽  
Many Server Queues ◽  
Priority Order ◽  
General Cost Functions ◽  
Queues With Abandonment

In “Dynamic Scheduling of Multiclass Many-Server Queues with Abandonment: The Generalized cμ/h Rule,” Long, Shimkin, Zhang, and Zhang propose three scheduling policies to cope with any general cost functions and general patience-time distributions. Their first contribution is to introduce the target-allocation policy, which assigns higher priority to customer classes with larger deviation from the desired allocation of the service capacity and prove its optimality for any general queue-length cost functions and patience-time distributions. The Gcμ/h rule, which extends the well-known Gcμ rule by taking abandonment into account, is shown to be optimal for the case of convex queue-length costs and nonincreasing hazard rates of patience. For the case of concave queue-length costs but nondecreasing hazard rates of patience, it is optimal to apply a fixed-priority policy, and a knapsack-like problem is developed to determine the optimal priority order efficiently.

scholarly journals Exact overflow asymptotics for queues with many Gaussian inputs

2003 ◽  
Vol 40 (3) ◽  
pp. 704-720 ◽  
Author(s):  
Krzysztof Dębicki ◽  
Michel Mandjes
Keyword(s):  
Brownian Motion ◽  
Gaussian Processes ◽  
Continuous Time ◽  
Time Horizon ◽  
Exact Results ◽  
Service Capacity ◽  
Stationary Increments ◽  
Overflow Probability ◽  
Finite Time Horizon ◽  
Transient Probability

In this paper we consider a queue fed by a large number of independent continuous-time Gaussian processes with stationary increments. After scaling the buffer exceedance threshold and the (constant) service capacity by the number of sources, we present asymptotically exact results for the probability that the buffer threshold is exceeded. We consider both the stationary overflow probability and the (transient) probability of overflow at a finite time horizon. We give detailed results for the practically important cases in which the inputs are fractional Brownian motion processes or integrated Gaussian processes.

scholarly journals Exact overflow asymptotics for queues with many Gaussian inputs

2003 ◽  
Vol 40 (03) ◽  
pp. 704-720 ◽  
Author(s):  
Krzysztof Dębicki ◽  
Michel Mandjes
Keyword(s):  
Brownian Motion ◽  
Gaussian Processes ◽  
Continuous Time ◽  
Time Horizon ◽  
Exact Results ◽  
Service Capacity ◽  
Stationary Increments ◽  
Overflow Probability ◽  
Finite Time Horizon ◽  
Transient Probability

In this paper we consider a queue fed by a large number of independent continuous-time Gaussian processes with stationary increments. After scaling the buffer exceedance threshold and the (constant) service capacity by the number of sources, we present asymptotically exact results for the probability that the buffer threshold is exceeded. We consider both the stationary overflow probability and the (transient) probability of overflow at a finite time horizon. We give detailed results for the practically important cases in which the inputs are fractional Brownian motion processes or integrated Gaussian processes.

scholarly journals Addressing Bandwidth-Driven Flow Allocationin RINA

Computers ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 63 ◽  
Author(s):  
Michal Koutenský ◽  
Vladimír Veselý ◽  
Vincenzo Maffione
Keyword(s):  
Quality Of Service ◽  
Network Flow ◽  
Capacity Allocation ◽  
Effective Capacity ◽  
Allocation Policy ◽  
Flexible Control ◽  
Service Guarantees ◽  
Link Data ◽  
Standing Problem

Effective capacity allocation is essential for a network to operate properly, providing predictable quality of service guarantees and avoiding bottlenecks. Achieving capacity allocation fairness is a long-standing problem extensively researched in the frame of transport and network layer protocols such as TCP/IP. The Recursive InterNetwork Architecture offers programmable policies that enable more flexible control on the mechanics of network flow allocation. In this paper, we present our version of one of these policies, which provides flow allocation according to the bandwidth requirements of requesting applications. We implement the bandwidth-aware flow allocation policy by extending rlite, an open source RINA implementation. Our evaluation shows how the policy can prevent links from becoming oversaturated and use alternate paths to achieve high total link data-rate use.

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