Modelling of the access part of a multi-service mobile network with service priorities

Hanczewski, Sławomir; Stasiak, Maciej; Zwierzykowski, Piotr

doi:10.1186/s13638-015-0420-4

Cited by 27 publications

(16 citation statements)

References 46 publications

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“…Figure 2A shows the theoretical probability mass function of the total number of tries required before a successful connection is established according to Equation 16. For the first case, the order of technologies is VHF, wired, microwave, wired with microwave, and VSAT.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…For the second case, the order of technologies is wired, VHF, microwave, wired with microwave, and VSAT. Figure 2A shows the theoretical probability mass function of the total number of tries required before a successful connection is established according to Equation 16. Figure 2B is the normalized histogram (20 bins) of the total number of (A) Probability mass function for number of attempts from theoretical model (i.e., Equation (16) .…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In Logothetis et al, 15 the authors have developed teletraffic loss models for call-level performance evaluation for upstream passive optical network (PON) connections. Whereas in Hanczewski et al, 16 the authors have presented a methodology for modeling and optimizing third generation (3G) mobile networks analysis. For these papers and others, the authors have examined only a single transmission technology or single network type.…”

Section: General Communication Link Modellingmentioning

confidence: 99%

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Analytical models for communication links in emergency management simulation

Adams

Singh

2018

Int J Communication

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Emergency response involves the management of several different types of critical infrastructures and resources. Because of the interdependent nature of these systems, it is often very difficult for human decision makers to determine what the second-or third-order effects of their decisions or actions might be. This has resulted in the development of several simulation tools that could be used to evaluate decisions or behaviours and better inform decision makers about the potential impacts of their decisions. One area that remains underdeveloped in this regard is the engagement of communication technologies by human agents, which has the potential to seriously affect delay times in response coordination.Given the size and complexity of simulating the interconnection of heterogeneous systems, developing reduced-order simulation models has become important to maintain reasonable computation times. This paper describes the derivation of the distribution of the total connection time for a communication link where multiple technologies are engaged. Results show that communication link simulation times, which are among the most time-consuming simulation routines can be significantly reduced by using the closed-form distributions. KEYWORDS analytical communication models, complex systems, disaster communications, disaster response simulation, emergency procedures INTRODUCTIONDisasters affect millions worldwide and cause economic damage in billions of US dollars on a yearly basis. 1,2 Consequently, a large amount of prior preparation goes into building a resilient system, both in terms of structural integrity of physical infrastructures and population education surrounding disasters. Once an event has occurred, however, the ability to properly coordinate the ensuing response effort becomes critical. The system as a whole consists of many different types of resources and infrastructures, all with their own distribution networks, operation procedures, and physical dynamics. Decisions, such as allocating resources to one place instead of another can have noticeable effects on the disaster response. Given the multidimensional nature of the problem, it is extremely difficult for humans to make informed decisions since they are generally unable to assess second-or third-order effects of decisions in a complex interconnected system of systems. 3 To help decision makers understand the potential impacts of their decisions, a number of simulation tools have been developed such as I2Sim, 4 CIPDSS, 5 HAZUS, 6 and ADMS. 7 Complex interdependencies are evident even within the operations of a single infrastructure. The communication system, for example, which is one of the most critical of infrastructures, 8 can be viewed as a highly interconnected Int J Commun Syst. 2018;31:e3500.wileyonlinelibrary.com/journal/dac

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Section: General Communication Link Modellingmentioning

confidence: 99%

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Analytical models for communication links in emergency management simulation

Adams

Singh

2018

Int J Communication

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“…Just as in the case of the limited-availability group with reservation, Formulas (15), (21), (22) and (23) form a system of confounded equations. To solve them, the iterative process proposed in [57] has to be applied.…”

Section: Model Of An Output Group With Threshold Mechanismsmentioning

confidence: 99%

“…These mechanisms are executed by reservation algorithms and threshold algorithms and make it possible to shape the quality policy (e.g., differentiation of access to limited resources [22]), improve the effectiveness of resource usage (e.g., spectrum efficiency and energy efficiency [23]) and increase the stability of operation of network devices (e.g., load balancing [24]). At the same time, the mechanisms allow streaming, elastic and adaptive services to be performed [1].…”

Section: Introductionmentioning

confidence: 99%

Analytical modelling of multiservice switching networks with multiservice sources and resource management mechanisms

Głąbowski

Sobieraj

2017

Telecommun Syst

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This article proposes a new analytical method of determining occupancy distribution and blocking probability in multiservice switching networks with admission control mechanisms and resource management mechanisms. The proposed method is a universal one, which allows for determining blocking probability using the same model, regardless of the type of admission control mechanisms and resource management mechanisms. The versatility of the method is demonstrated in the article for two selected mechanisms, i.e. a threshold mechanism and a resource reservation mechanisms. The switching networks under consideration are offered multiservice traffic streams, generated by the so-called multiservice sources, according to Erlang, Engset and Pascal distributions. The proposed method is based on a generalised way of determining traffic characteristics for inter-stage links of switching networks with resource and call management mechanisms. Particular attention is given to determining the influence of the introduced mechanisms in outgoing links of the switching network on the traffic properties of inter-stage links of the network. The results of analytical calculations are then compared with the results obtained in digital simulation for a number of selected switching networks.

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The Erlang Multirate Loss Model

2019

Efficient Multirate Teletraffic Loss Models Beyond Erlang

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Modelling of the access part of a multi-service mobile network with service priorities

Cited by 27 publications

References 46 publications

Analytical models for communication links in emergency management simulation

Analytical models for communication links in emergency management simulation

Analytical modelling of multiservice switching networks with multiservice sources and resource management mechanisms

The Erlang Multirate Loss Model

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