Derivatives of Blocking Probabilities for Multi-service Loss Systems and Their Applications

Iversen, Villy Bæk; Stepanov, S. N.

doi:10.1007/978-3-540-74833-5_22

Cited by 12 publications

(7 citation statements)

References 5 publications

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“…The proposed system model has been conceived for voice traffic in TDMA/FDMA systems. The model can be extended to multiple services by the multi-rate Erlang loss model, for which effective methods exist to compute the blocking probability and its derivatives, [46,47]. Such a model is insensitive to the service time distribution and can consider a mixture of not only Poissonian but also smoother or more bursty traffic, [48].…”

Section: Discussionmentioning

confidence: 99%

Optimal Traffic Sharing in GERAN

Luna-Ramírez

Toril

Fernández-Navarro

et al. 2009

Wireless Pers Commun

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In a mobile communications network, the uneven spatial distribution of traffic demand can be dealt with by redefining cell service areas. When resizing cells, network operators often aim at equalizing call blocking rates throughout the network in the hope that this will maximize the total carried traffic in the network. In this paper, an analytical teletraffic model for the traffic sharing problem in GSM-EDGE radio access network (GERAN) is presented. From this model, a closed-form expression is derived for the optimal traffic sharing criterion between cells. Using this expression, it can be shown that balancing call blocking rate between adjacent cells is not the optimal strategy. Results show that using the optimal traffic sharing criterion instead of balancing blocking rates across the network can increase network capacity, even under restrictions in the cell resizing process.

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Section: Discussionmentioning

confidence: 99%

Optimal Traffic Sharing in GERAN

Luna-Ramírez

Toril

Fernández-Navarro

et al. 2009

Wireless Pers Commun

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“…In Formula (4), the parameter [P n ] V is the state probability, i.e., the probability of the event that there are n-occupied BBUs in the system, and σ c (n) is the probability of admission of the class c call to the service when the system is found in the state n. Equation (4) results directly from the first work concerning the so-called full-availability group (a system with a complete sharing policy) with multi-rate traffic, i.e., [34][35][36][37]. If σ c (n) = 1, for each state of a given system, then the generalized Kaufman-Roberts recursion (4) is reduced to the Kaufman-Roberts recursion [35,36].…”

Section: Blocking Probability Calculationsmentioning

confidence: 99%

Analytical Model of the Connection Handoff in 5G Mobile Networks with Call Admission Control Mechanisms

Głąbowski,

Sobieraj,

Stasiak

2024

Sensors

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Handoff mechanisms are very important in fifth-generation (5G) mobile networks because of the cellular architecture employed to maximize spectrum utilization. Together with call admission control (CAC) mechanisms, they enable better optimization of bandwidth use. The primary objective of the research presented in this article is to analyze traffic levels, aiming to optimize traffic management and handling. This article considers the two most popular CAC mechanisms: the resource reservation mechanism and the threshold mechanism. It presents an analytical approach to occupancy distribution and blocking probability calculation in 5G mobile networks, incorporating connection handoff and CAC mechanisms for managing multiple traffic streams generated by multi-service sources. Due to the fact that the developed analytical model is an approximate model, its accuracy was also examined. For this purpose, the results of analytical calculations of the blocking probability in a group of 5G cells are compared with the simulation data. This paper is an extended version of our paper published in 17th ConTEL 2023.

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“…Notice that Kaufman-Roberts algorithm is used in both of the proposed frameworks and the complexity of this algorithm is O(CJ) which provides a considerable improvement over solving the LoLP through (28) which has a complexity of O(C J ) [24], [25]. For the pricing-based control problem, we compute the derivatives of multi-rate blocking probabilities using the convolution-based algorithm [32] and similar to Kaufman-Roberts algorithm, the order of complexity is O(CJ).…”

Section: Computing Loss-of-load-probabilitiesmentioning

confidence: 99%

“…In the proposed multi-class customer model, there is no explicit formulae for performance measures (LoLP) in terms of input parameters (C, λ j ,µ j , etc.). In this paper we follow the methods based on convolution algorithms [32] to compute the derivatives of the LoLP. To that end the derivative of the LoLP associated with customer type j with respect to the traffic intensity of another class j 1 = j 2 can be computed by using the function α(•) as follows.…”

Section: Computing Loss-of-load-probabilitiesmentioning

confidence: 99%

Capacity Planning Frameworks for Electric Vehicle Charging Stations With Multiclass Customers

Bayram

Tajer

Abdallah

et al. 2015

IEEE Trans. Smart Grid

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Abstract-In order to foster electric vehicle (EV) adoption, there is a strong need for designing and developing charging stations that can accommodate different customer classes, distinguished by their charging preferences, needs, and technologies. By growing such charging station networks, the power grid becomes more congested and, therefore, controlling of charging demands should be carefully aligned with the available resources. This paper focuses on an EV charging network equipped with different charging technologies and proposes two frameworks. In the first framework, appropriate for large networks, the EV population is expected to constitute a sizable portion of the light duty fleets. This which necessitates controlling the EV charging operations to prevent potential grid failures and distribute the resources efficiently. This framework leverages pricing dynamics in order to control the EV customer request rates and to provide a charging service with the best level of quality of service. The second framework, on the other hand, is more appropriate for smaller networks, in which the objective is to compute the minimum amount of resources required to provide certain levels of quality of service to each class. The results show that the proposed frameworks ensure grid reliability and lead to significant savings in capacity planning.

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Derivatives of Blocking Probabilities for Multi-service Loss Systems and Their Applications

Cited by 12 publications

References 5 publications

Optimal Traffic Sharing in GERAN

Optimal Traffic Sharing in GERAN

Analytical Model of the Connection Handoff in 5G Mobile Networks with Call Admission Control Mechanisms

Capacity Planning Frameworks for Electric Vehicle Charging Stations With Multiclass Customers

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