Modelling handoff and dynamic channel allocation using Petri nets

Modeling and analysis tools are essential for the design and evaluation of complex systems. This is particularly true for cellular systems, where, for instance, a variety of handoff, channel allocation, and data-transmission algorithms have been proposed. The capabilities of Petri nets (PNs) are used as a novel approach in the analysis of handoff, dynamic channel allocation (DCA), and cellular digital packet data resource management problems. The generalized stochastic PN (GSPN) models are obtained and analyzed as continuous-time Markov chains (MCs) derived from the reachability graphs. Solution of the MC results in performance indicators, which show the impacts of different algorithms on the system behavior.

From Rio to Iragua--sustainability versus efficiency and equity for preventive health interventions.

High Altitude Platforms (HAPs) is the name of a new technology to provide wireless narrowband and broadband services. A unique property of HAPs is the ability of preparing emergency telecommunication facilities once the catastrophic events occur. In these situations efficient use of limited spectrum resources would be of great importance. This paper presented a fuzzy channel allocation scheme in HAPs for emergency mobile communications. The suggested scheme is based on guard channel policy. It dynamically adjusts optimum number of reserved channels according to important quality of service (QoS) parameters to make an efficient use of resources, while prioritizes on-going calls over new calls. Simulation compares the proposed fuzzy scheme with fixed guard channel scheme and complete sharing scheme. Results show that, the fuzzy scheme is able to achieve a better grade of service (GoS), while can keep handoff failures low as network traffic load changes.

In cellular networks, communication among mobile devices is accomplished through base stations (fixed antennas). A base station allocates communication channels whenever a mobile device (a cell phone, for example) in its coverage area requests communication with some other device (mobile or fixed). With the rapidly growing number of mobile devices, the use of communication channels available in cellular networks needs to be optimized. To efficiently optimize the use of communication channels in cellular networks dynamic (on-the-fly) channel allocation may be used, using algorithms for that purpose; however such algorithms demand previous knowledge of the number of mobile devices in the area of coverage of a given base station. In this paper, we propose a strategy to support dynamic channel allocation in cellular networks by predicting the number of mobile devices in the area covered by a base station at any given moment. The proposed strategy is based on an indexing mechanism for mobile objects. The results obtained through experiments prove the efficiency of the proposed strategy

The global economic impact of basketball is measured in tens of billions of dollars and requires the efficient use of resources to maximize success on and off the court. Today, coaches, players, investors, and owners need to take full advantage of modern analytical methods and digital video software capabilities to make the most efficient use of a teams resources. This research is the first in a series that makes full use of modern analytic methods and begins to define new defensive and offensive criteria to supplement the decades old game box score performance information. Data envelopment analysis and statistical methods are used to evaluate two new defensive performance metrics on defensive efficiency. The two new defensive metrics are contested and uncontested passes that are fully defined in the articles appendix. Future research will expand the sample size and allow for more comprehensive models of basketball team defensive efficiency.

There is general agreement among the major stakeholders—providers, consumers, payors, and managed behavioral health companies—that managed care poses significant challenges for behavioral health professionals, particularly those whose primary work has been in independent practice rather than organized care settings. In traditional independent practice, clinicians were free to employ relatively unstructured, goal-free approaches to care with an emphasis on patient insight and self-knowledge. Formal written treatment plans were a rarity and there was little external pressure on clinicians to complete treatment within any specified period of time. Often, little attention was paid to the efficient use of financial and service resources, and decisions to begin and end treatment were the purview of the therapist and the patient. Patients were generally seen as financially responsible for their treatment regardless of employment based benefits. Indeed, such an approach to practice was consistent with the ways in which most behavioral health professionals were trained. In contrast, clinicians practicing in today's managed care environment are typically required to develop written, goal-focused, time limited treatment plans emphasizing the return of the patient to an adequate level of day-to-day functioning while making efficient use of resources (Austad & Berman, 1991). Decisions to begin and end treatment, at least the part to be paid for through the benefit plan, are made by the therapist and patient together with a third party—the managed care entity. In order to work effectively within this context, clinicians must be both willing and able to change their practice patterns, to at least accommodate

The international guidelines for surveillance following the finding of a small tubular adenoma vary between no surveillance or colonoscopy at 5 or 10 years, whereas surveillance after an advanced adenoma is 3 years. Optimization of surveillance reduces the risk of colorectal cancer (CRC) with efficient use of colonoscopy resources. We assessed the risks of advanced colorectal neoplasia following a baseline finding of a small adenoma compared with advanced adenoma. A retrospective audit was undertaken of patients enrolled in a CRC surveillance program, wherein regular colonoscopies and screening with faecal immunochemical test (FIT) were provided. Patients diagnosed with either small or advanced adenoma followed by at least one surveillance colonoscopy were included. Advanced adenoma included adenomas with features of villous change, size of at least 10 mm, high-grade dysplasia, three or more small tubular adenomas and traditional and sessile serrated adenomas. Subdistribution hazard ratios were calculated for advanced neoplasia (CRC or advanced adenoma). Overall, 378 patients (62.6±11.2 years, 57.9% male) were included, with 44.2% diagnosed with small adenoma and 55.5% with advanced adenoma at baseline. The crude cumulative incidence of advanced neoplasia at first surveillance was 13.2 and 18.5% after small and advanced adenoma (P=0.16) (at 45.9 and 35.6 months, respectively), which became significant for advanced adenoma after adjustment (subdistribution hazard ratio=2.55, 95% confidence interval=1.49-4.35, P<001). A positive FIT was the only independent predictor of advanced neoplasia after a small adenoma at baseline colonoscopy (odds ratio=5.05, 95% confidence interval=1.27-20.02, P=0.02). The risk of advanced neoplasia following a small adenoma was lower than that following an advanced adenoma, but was strongly predicted by a positive FIT. Reducing frequency of colonoscopy while providing regular FIT might be a more efficient use of resources for this population.

This article reviews the principles involved in establishing the cost effectiveness of mass drug therapy for the major intestinal nematodes and the intestinal form of schistosomiasis, as well as the extent to which the available studies have provided definitive answers. For governments or agencies that have decided to introduce a control programme, there is considerable evidence about the comparative cost effectiveness of different types of delivery strategies. For example, mass treatment is more cost effective than selective treatment (treatment after individual screening) in high prevalence areas and at observed prices. Mass treatment targeted at known high risk groups, such as schoolchildren, for the major intestinal helminths (apart from hookworm) can be more cost effective than population-based mass treatment. However, this raises the question whether any form of mass anthelmintic chemotherapy is an efficient use of scare health resources in view of the competing demands for scarce public funds, and for the scarce resources of other funders of healthcare including donors, nongovernmental organisations and missions. Some evidence that it is an efficient use of resources is available; this article concludes by outlining the type of information that is required to strengthen the argument for mass therapy.

The ever-increasing number of customers and the need for higher data rates and multimedia services require the deployment of Small Cell Networks. In this paper, we propose a new computational approach to study performance and reliability of Small Cell Networks, taking into account the retrial phenomenon, the finite number of customers (mobiles) served in a cell and the random breakdowns of the base station channels, using the Generalized Stochastic Petri Nets (GSPNs) model as a support. However, one of the major drawbacks of this high-level formalism in performance evaluation of large networks is the state space explosion problem which increases when considering repeated calls and multiple unreliable channels. Hence, the novelty of this investigation is the presentation of an approach which allows a direct computing of the infinitesimal generator describing the customers behavior and channels allocation in as small cell, without generating nor storing the reachability set. In addition, we develop the formulas of the main stationary reliability and performance indices as a function of the network parameters, the stationary probabilities and independently of the reachability set markings.

Resource use efficiency (RUE) is an ecological concept that measures the proportion of supplied resources, which is converted into new biomass, i.e. it relates realized to potential productivity. It is also commonly perceived as one of the main mechanisms linking biodiversity to ecosystem functioning based on the assumption that higher species numbers lead to more complementary and consequently more efficient use of the available resources. While there exists a large body of literature lending theoretical and experimental support to this hypothesis, there are a number of inconsistencies regarding its application: First, empirical tests use highly divergent approaches to calculate RUE. Second, the quantification of RUE is commonly based on measures of standing stock instead of productivity rates and total pools of nutrients instead of their bioavailable fractions, which both vary across systems and therefore can introduce considerable bias. Third, conceptual studies suggest that the relationship between biodiversity, productivity and RUE involves many more mechanisms than complementary resource use, resulting in variable magnitude and direction of biodiversity effects on productivity. Moreover, RUE has mainly been applied to single elements, ignoring stoichiometric or metabolic constraints that lead to co-limitation by multiple resources. In this review we illustrate and discuss the use of RUE within and across systems and highlight how the various drivers of RUE affect the diversity-productivity relationship with increasing temporal and spatial scales as well as under anthropogenic global change. We illustrate how resource supply, resource uptake and RUE interactively determine ecosystem productivity. In addition, we illustrate how in the context of biodiversity and ecosystem functioning, the addition of a species will only result in more efficient resource use and consequently higher community productivity if the species’ traits related to resource uptake and RUE are positively correlated.

The author describes an efficient numerical algorithm for calculating transient solutions of generalized stochastic Petri net (GSPN) models. The method described is based on the randomization technique and a stable calculation of Poisson probabilities. A complete redesign and reimplementation of the appropriate components of the software package GreatSPN lead to a significant savings in computation time and memory space. The benefit of employing the described solution algorithm is illustrated by a GSPN model for the M/M/1/K queueing system. This example shows that transient solutions of GSPN models are calculated with significantly less computational effort and better error control by the algorithm described than by the method implemented in version 1.4 of the analysis tool GreatSPN. >

In this paper, we extend Petri Nets including Queueing Networks (PNiQs) with several job classes and define Multi Class-PNiQs (MC-PNiQ). A MC-PNiQ is a Generalized Stochastic Petri Net (GSPN) which contains multiclass queueing networks (MC-QNs). This approach allows to combine the advantages of both concepts on the modelling level as well as on the analysis level. The use of MC-QNs permits concise modelling of waiting room, server and queueing and offers many fast analysis algorithms for large multiclass systems. Additionally, GSPN provide the expressiveness and flexibility for modelling of more complicated structures like fork/join, etc. The definition of MC-PNiQs is especially designed to allow a qualitative analysis based on a reduced state space, as well as automated approximate analysis by aggregation of the multi-class queueing nets and replacing them with GSPN elements. The resulting GSPN can then be analyzed with state-of-the-art methods and tools.

This paper presents a distributed reinforcement learning solution to the problem of dynamic channel allocation for cellular telecommunication networks in the presence of mobile call handoffs. The performance of various dynamic channel allocation schemes are compared via extensive computer simulations, and it is shown that a reduced-state SARSA reinforcement learning algorithm can achieve superior new call and handoff blocking probabilities. A new distributed reduced state SARSA algorithm is also developed which uses only local environment information readily available to the learning agent. By way of computer simulations, the distributed SARSA algorithm is shown to be capable of producing call blocking probabilities that are comparable to those obtained by the centralised learning agent.

The performance of flow lines is significantly affected by the failures and the repair activities that the machines go through. The manufacturing process models based on Petri nets with time are developed for single work station, including a stochastic failure process and a repair process. The models consider two failure detection modes and three interrupted-job-handling policies. To study the influence of failures upon flow lines, the generalized stochastic Petri net (GSPN) models with two work stations are constructed for performance evaluation and simulation. A performance comparison among three cases is made. It is concluded that the repairing sequence rule considering system states exhibits much better performance in reducing the productive loss of time and cost due to failures. Finally, conclusions are drawn and some future researches are discussed.

Dynamic Channel Allocation (DCA) schemes based on Artificial Neural Network (ANN) technology were seen as performing better overall than conventional statistically based Channel Allocation!DCA Channel Allocation!DCA Channel Allocation!DCA Channel Allocation!DCA DCA schemes. Furthermore, some papers report that within the ANN schemes adopted as Channel Allocators (CA), the Neural Network!HNN Neural Network!HNN Neural Network!HNN Neural Network!HNN Neural Network!Hopfield Neural Network!Hopfield Neural Network!Hopfield Neural Network!Hopfield Hopfield Neural Network (HNN) performs considerably better than the conventional non-Neural Network!HNN HNN methods. The work reported in this paper is a summary of research where a new HNNCA is proposed and simulated to check the validity of the argument itself. The simulation of the project was done through non-uniform traffic to simulate extreme conditions and have a more realistic approach; the number of prerecorded patterns was also a subject of the simulation. The simulation’s results recorded different correlated situations and there have been substantial conclusions that can be made from the simulation itself.