Call Blocking Probabilities under a Probabilistic Bandwidth Reservation Policy in Mobile Hotspots

In this paper we study a mobility-aware call admission control algorithm in a mobile hotspot. To this end, a vehicle is considered which has an access point with a fixed capacity. The vehicle alternates between stop and moving phases. When the vehicle is in the stop phase, it services new and handover calls by prioritizing them via a probabilistic bandwidth reservation (BR) policy. Based on this policy, new handover calls may enter the reservation space with a predefined probability. When the vehicle is in the moving phase, it services new calls only. In that phase, two different policies are considered: (a) the classical complete sharing (CS) policy, where new calls are accepted in the system whenever there exists available bandwidth, and (b) the probabilistic BR policy. Depending on the selected policy in the moving phase, we propose the probabilistic BR loss model (if the CS policy is selected) and the generalized probabilistic BR loss model (if the probabilistic BR policy is selected). In both stop and moving phases, where the call arrival process is Poisson, calls require a single bandwidth unit in order to be accepted in the system, while the service time is exponentially distributed. To analytically determine call blocking probabilities and the system’s utilization, we propose efficient iterative algorithms based on two-dimensional Markov chains. The accuracy of the proposed algorithms is verified via simulation.

Selective Channel Assignment Method in Cognitive Radio System

An Efficient Channel assignment method for cognitive radio system has been proposed in this paper, by considering primary and secondary calls separately in the network for the cases of with and without usage of converters. The proposed channel assignment method known as selective channel assignment method its performance is compared with the existing first fit assignment and uniformly distributed random assignment methods. Each of the models has variant for with conversion and without conversion of wavelength. The simulations are run for a network having 10, 20 channels, 12, 15 and 25 links and 8 Erlangs of load. By carrying out the simulations of the proposed and existing channel assignment methods, the blocking probabilities, throughput and channel usage frequencies are computed for each of the assignment methods. When the selective channel assignment method was used, the blocking probabilities are around 41% and 39% for 50% PU calls case and 64% and 26% for 75% PU calls case when there were no converters in the network. When converters are used, the blocking probabilities are around 30% and 36% for 50% PU calls case and 38% and 18% for 75% PU calls case. Our simulations validated the effectiveness of the proposed channel assignment scheme in terms of blocking probability, throughput and channel usage as performance parameters.

Sensitivity of mean-field fluctuations in Erlang loss models with randomized routing

In this paper we study a large system of N servers, each with capacity to process at most C simultaneous jobs; an incoming job is routed to a server if it has the lowest occupancy amongst d (out of N) randomly selected servers. A job that is routed to a server with no vacancy is assumed to be blocked and lost. Such randomized policies are referred to JSQ(d) (Join the Shortest Queue out of d) policies. Under the assumption that jobs arrive according to a Poisson process with rate $N\lambda^{(N)}$ where $\lambda^{(N)}=\sigma-\frac{\beta}{\sqrt{N}\,}$ , $\sigma\in\mathbb{R}_+$ and $\beta\in\mathbb{R}$ , we establish functional central limit theorems for the fluctuation process in both the transient and stationary regimes when service time distributions are exponential. In particular, we show that the limit is an Ornstein–Uhlenbeck process whose mean and variance depend on the mean field of the considered model. Using this, we obtain approximations to the blocking probabilities for large N, where we can precisely estimate the accuracy of first-order approximations.

Probabilistic Retry and Threshold Multirate Loss Models for Impatient Calls

In this paper, a link of fixed capacity is considered that services calls from different service-classes. Calls arrive in the link according to a Poisson process, have an initial (peak) bandwidth requirement while their service time is exponentially distributed. We model this system as a multirate loss system and analyze two different multirate loss models. In the first model, named probabilistic retry loss model, if there is no available link bandwidth, a new call is blocked but retries with a lower bandwidth requirement and increased service time. To allow for the fact that a blocked call may be impatient, we assume that it retries with a probability. In the second model, named probabilistic threshold loss model, a call may reduce its bandwidth requirement (before blocking occurs) based on the occupied link bandwidth. To determine call blocking probabilities in both multirate loss models, we show that approximate but recursive formulas do exist that provide quite satisfactory results compared to simulation.

Supporting Real-Time Data Transmissions in Cognitive Radio Networks Using Queue Shifting Mechanism

As cognitive radio networks are conceptualized to make use of the opportunistic spectrum access, the users of these networks may face problems in satisfying their quality of service (QoS) requirements. Some services of users like real-time audio and video which cannot tolerate inter-packet delays will be affected more due to this. The problem occurs due to the non-availability of channels to these applications at some instants. This problem can be addressed if the available channels are judiciously distributed among the competing users. One such mechanism that dynamically allocates the competing users to multiple queues, and shifting the users to higher-level queues as the time elapses is introduced in this work. This is found to help the users of cognitive radio networks to communicate reasonably well even when fewer channels are available for opportunistic use. Results are indicated in terms of blocking probabilities of real-time data. Markov chain-based analysis and discrete event simulation studies are carried out.

Best candidate routing algorithms integrated with minimum processing time and low blocking probability for modern parallel computing systems

<p>This study has clarified the best candidate routing algorithms integrated with minimum processing times and low blocking probabilities for modern parallel computing systems. Different methods were employed, such as the fast window method (FWM), fast bitwise window method (FBWM), and fast improved window method (FIWM), to upgrade the processing time and reduce the network delay time. In addition, different algorithms were studied such as the fast window ascending, the fast window descending, the fast window sequential algorithm, and the fast window sequential down algorithms; these were studied to show the numerical results of the networks’ blocking probabilities, processing times, and delay times.</p>

Modeling of Clos Switching Structures with Dynamically Variable Number of Active Switches in the Spine Stage

This article proposes a new analytical model of a switching structure using a Clos network topology. The assumption is that, in the structure under consideration, it is possible to switch off temporarily a certain number of spine switches (those in the middle stage of the switching fabric) depending on the current intensity of the offered traffic to reduce power consumption. The solution presented in the article can be used in present-day multiservice switching fabrics and in networks connecting servers in data centers. The developed analytical model allows the value of blocking probabilities for different stream classes of multiservice traffic to be evaluated in switching structures (switching fabrics) with a variable number of switches in the middle stage. The results obtained on the basis of the analytical model are compared with the results obtained as a result of relevant simulation experiments for a selected structure of the switching fabric. The study confirms high accuracy of the proposed model. This model can be used in further works to evaluate the effectiveness of energy-saving switching fabrics and the networks of data centers, as well as to construct energy-saving control algorithms that would control these switching structures, that is, algorithms that would change the topology of the switching fabric depending on changes in the offered traffic.