Small active counters

The need for efficient counter architecture has arisen for the following two reasons. Firstly, a number of data streaming algorithms and network management applications require a large number of counters in order to identify important traffic characteristics. And secondly, at high speeds, current memory devices have significant limitations in terms of speed (DRAM) and size (SRAM). For some applications no information on counters is needed on a per-packet basis and several methods have been proposed to handle this problem with low SRAM memory requirements. However, for a number of applications it is essential to have the counter information on every packet arrival. In this paper we propose two, computationally and memory efficient, randomized algorithms for approximating the counter values. We prove that proposed estimators are unbiased and give variance bounds. A case study on Multistage Filters (MSF) over the real Internet traces shows a significant improvement by using the active counters architecture

Router-based algorithms for improving internet quality of service.

We begin this thesis by generalizing some results related to a recently proposed positive system model of TCP congestion control algorithms. Then, motivated by a mean ¯eld analysis of the positive system model, a novel, stateless, queue management scheme is designed: Multi-Level Comparisons with index l (MLC(l)). In the limit, MLC(l) enforces max-min fairness in a network of TCP flows. We go further, showing that counting past drops at a congested link provides su±cient information to enforce max-min fairness among long-lived flows and to reduce the flow completion times of short-lived flows. Analytical models are presented, and the accuracy of predictions are validated by packet level ns2 simulations. We then move our attention to e±cient measurement and monitoring techniques. A small active counter architecture is presented that addresses the problem of accurate approximation of statistics counter values at very-high speeds that can be both updated and estimated on a per-packet basis. These algorithms are necessary in the design of router-based flow control algorithms since on-chip Static RAM (SRAM) currently is a scarce resource, and being economical with its usage is an important task. A highly scalable method for heavy-hitter identifcation that uses our small active counters architecture is developed based on heuristic argument. Its performance is compared to several state-of-the-art algorithms and shown to out-perform them. In the last part of the thesis we discuss the delay-utilization tradeoff in the congested Internet links. While several groups of authors have recently analyzed this tradeoff, the lack of realistic assumption in their models and the extreme complexity in estimation of model parameters, reduces their applicability at real Internet links. We propose an adaptive scheme that regulates the available queue space to keep utilization at desired, high, level. As a consequence, in large-number-of-users regimes, sacrifcing 1-2% of bandwidth can result in queueing delays that are an order of magnitude smaller than in the standard BDP-bu®ering case. We go further and introduce an optimization framework for describing the problem of interest and propose an online algorithm for solving it

Small active counters

The need for efficient counter architecture has arisen for the following two reasons. Firstly, a number of data streaming algorithms and network management applications require a large number of counters in order to identify important traffic characteristics. And secondly, at high speeds, current memory devices have significant limitations in terms of speed (DRAM) and size (SRAM). For some applications no information on counters is needed on a per-packet basis and several methods have been proposed to handle this problem with low SRAM memory requirements. However, for a number of applications it is essential to have the counter information on every packet arrival. In this paper we propose two, computationally and memory efficient, randomized algorithms for approximating the counter values. We prove that proposed estimators are unbiased and give variance bounds. A case study on Multistage Filters (MSF) over the real Internet traces shows a significant improvement by using the active counters architecture

Router-based algorithms for improving internet quality of service.

We begin this thesis by generalizing some results related to a recently proposed positive system model of TCP congestion control algorithms. Then, motivated by a mean ¯eld analysis of the positive system model, a novel, stateless, queue management scheme is designed: Multi-Level Comparisons with index l (MLC(l)). In the limit, MLC(l) enforces max-min fairness in a network of TCP flows. We go further, showing that counting past drops at a congested link provides su±cient information to enforce max-min fairness among long-lived flows and to reduce the flow completion times of short-lived flows. Analytical models are presented, and the accuracy of predictions are validated by packet level ns2 simulations. We then move our attention to e±cient measurement and monitoring techniques. A small active counter architecture is presented that addresses the problem of accurate approximation of statistics counter values at very-high speeds that can be both updated and estimated on a per-packet basis. These algorithms are necessary in the design of router-based flow control algorithms since on-chip Static RAM (SRAM) currently is a scarce resource, and being economical with its usage is an important task. A highly scalable method for heavy-hitter identifcation that uses our small active counters architecture is developed based on heuristic argument. Its performance is compared to several state-of-the-art algorithms and shown to out-perform them. In the last part of the thesis we discuss the delay-utilization tradeoff in the congested Internet links. While several groups of authors have recently analyzed this tradeoff, the lack of realistic assumption in their models and the extreme complexity in estimation of model parameters, reduces their applicability at real Internet links. We propose an adaptive scheme that regulates the available queue space to keep utilization at desired, high, level. As a consequence, in large-number-of-users regimes, sacrifcing 1-2% of bandwidth can result in queueing delays that are an order of magnitude smaller than in the standard BDP-bu®ering case. We go further and introduce an optimization framework for describing the problem of interest and propose an online algorithm for solving it

Load balancing vs. distributed rate limiting: an unifying framework for cloud control

With the expansion of cloud-based services, the question as to how to control usage of such large distributed systems has become increasingly important. Load balancing (LB), and recently proposed distributed rate limiting (DRL) have been used independently to reduce costs and to fairly allocate distributed resources. In this paper we propose a new mechanism for cloud control that unifies the use of LB and DRL: LB is used to minimize the associated costs and DRL makes sure that the resource allocation is fair. From an analytical standpoint, modelling the dynamics of DRL in dynamic workloads (resulting from LB cost-minimization scheme) is a challenging problem. Our theoretical analysis yields a condition that ensures convergence to the desired working regime. Analytical results are then validated empirically through several illustrative simulations. The closed- form nature of our result also allows simple design rules which, together with extremely low computational and communication overhead, makes the presented algorithm practical and easy to deploy

Trading link utilization for queueing delays: an adaptive approach

Understanding the relationship between queueing delays and link utilization for general traffic conditions is an important open problem in networking research. Difficulties in understanding this relationship stem from the fact that it depends on the complex nature of arriving traffic and the problems associated with modelling such traffic. Existing AQM schemes achieve a "low delay" and "high utilization" by responding early to congestion without considering the exact relationship between delay and utilization. However, in the context of exploiting the delay/utilization tradeoff, the optimal choice of a queueing scheme's control parameter depends on the cost associated with the relative importance of queueing delay and utilization. The optimal choice of control parameter is the one that maximizes a benefit that can be defined as the difference between utilization and cost associated with queuing delay. We present two practical algorithms, Optimal Drop-Tail (ODT) and Optimal BLUE (OB), that are designed with a common performance goal: namely, maximizing this benefit. Their novelty lies in fact that they maximize the benefit in an online manner, without requiring knowledge of the traffic conditions, specific delay-utilization models, nor do they require complex parameter estimation. Packet level ns2 simulations are given to demonstrate the efficacy of the proposed algorithms and the framework in which they are designed

Drop counters are enough.

Small Flow Completion Time (FCT) of short-lived flows, and fair bandwidth allocation of long-lived flows have been two major, usually concurrent, goals in the design of resource allocation algorithms. In this paper we present a framework that naturally unifies these two objectives under a single umbrella; namely by proposing resource allocation algorithm Markov Active Yield (MAY). Based on a probabilistic strategy: "drop proportional to the amount of past drops", MAY achieves very small FCT among short-lived flows as well as max-min fair bandwidth allocation among long-lived flows, using only the information of short history of already dropped packets. It turns out that extremely small amount of on-chip SRAM (roughly 1 bit per flow in Pareto-like flow size distributions) is enough for storing this drop history. Analytical models are presented and analyzed and accuracy of results is verified experimentally using packet level ns2 simulations

Adaptive Tuning of Drop-Tail Buffers for Reducing Queueing Delays.

Internet router buffers are used to accommodate packets that arrive in bursts and to maintain high utilization of the egress link. Such buffers can lead to large queueing delays. We propose a simple algorithm, Active Drop-Tail (ADT), which regulates the queue size, based on prevailing traffic conditions, to a minimum size that still allows for a desired (high) level of utilization. Packet level ns2 simulations are provided to show that Adaptive Drop-Tail achieves significantly smaller queues than current approaches at the expense of 1-2% of the link utilization

Farmakoekonomska evaluacija fakoemulzifikacije i ekstrakapsularne ekstrakcije u operaciji katarakte

Background/Aim. Cataract surgery is one of the most often performed surgical interventions. The predominant method in Western countries is phacoemulsification, while in developing countries, the extracapsular cataract extraction (ECCE) method remains popular. The aim of the study was to evaluate the cost- effectiveness of these two cataract surgery techniques from the provider’s perspective if operation complications were the out- come of the interest. Methods. The data were obtained from the Department of Ophthalmology of the General Hospital Kruševac during a one-year period. A total of 1,179 surgeries by five surgeons were performed. The cost-effectiveness was evaluated using the decision tree. All probabilities were calcu- lated based on the likelihood of the occurrence during the study period. Only direct costs were considered, and values were taken from the documentation at the hospital and the of- ficial price list of health services. One- and two-way sensitivity analyses were performed. Results. The total cost per patient in the phacoemulsification group was 71,008.70 Serbian dinars (RSD), while the total cost in the ECCE group was 74,340.36 RSD. At the same time, phacoemulsification shows higher ef- fectiveness than the ECCE method, with 87% and 57% of pa- tients without complications, respectively. With these results, phacoemulsification was the dominant strategy compared to ECCE. The sensitivity analysis revealed that the results are sen- sitive to the number of performed operations per year. Con- clusion. The phacoemulsification technique seems to be the preferred technique for cataract surgery. All the investment in phacoemulsification equipment and consumables is justified if the number of surgeries per year exceeds 350.Uvod/Cilj. Operacija katarakte predstavlja jednu od najčešće primenjivanih hirurških intervencija. U zapadnim zemljama, dominantna tehnika je fakoemulzifikacija, dok je u zemljama u razvoju najzastupljenija tehnika ekstrakapsularne ekstrakcije (ECCE). Cilj rada bio je da se proceni ekonomska isplativost te dve tehnike operacije katarakte iz perspektive pružaoca usluge, ukoliko se kao ishod posmatraju komplikacije. Metode. Podaci su dobijeni sa Očnog odeljenja Opšte bolnice Kruševac tokom jednogodišnjeg perioda. Ukupno je izvedeno 1 179 operacija od strane pet hirurga. Ekonomska isplativost je procenjena primenom „drveta odlučivanja“. Verovatnoće za događaje su izračunate na osnovu verovatnoće pojavljivanja tokom navedenog perioda. U analizi su razmatrani samo direktni troškovi, a vrednosti su preuzete iz prateće dokumentacije i zvaničnog cenovnika zdravstvenih usluga. Sprovedena je jednosmerna i dvosmerna analiza osetljivosti. Rezultati.Ukupni troškovi u grupi koja je bila podvrgnuta fakoemulzifikaciji iznosili su 71 008.70 srpskih dinara (RSD), dok su u ECC E grupi oni iznosili 74 340.36 RSD. Istovremeno, fakoemulzifikacija je pokazala višu efikasnost u odnosu na ECCE, 87% i 57% bolesnika bez komplikacija, redom. Na osnovu dobijenih rezultata, fakoemulzifikacija je bila dominantna strategija u poređenju sa ECCE. Analiza osetljivosti pokazala je da su rezultati osetljivi na broj izvršenih intervencija na godišnjem nivou. Zaključak. Fakoemulzifikacija je ekonomski isplativija tehnika operacije katarakte u odnosu na ECCE. Sva ulaganje u opremu i potrošni materijal za fakoemulzifikaciju opravdani su ukoliko je broj izvedenih operacija na godišnjem nivou preko 350

Analysis of optimal costs for reserves of spare parts for agricultural machines

Managing reserves of spare parts for agricultural machinery in agricultural farms represents one of the most important activities in securing smooth functioning, especially having in mind the imperative of continuous agricultural production. Aims of this study were to show how efficiency of the agricultural farms as a business subject can be secured by determining timely purchase of spare parts by using a stochastic model of supplies on one side and reduce the time of malfunction of agricultural machinery on the other. Study of optimal inventory level was conducted in agricultural holdings on the territory Banat in 2015 based on data on spare parts purchase and malfunction of agricultural machinery. Acquired data was related to frequency of defects and the need for spare parts, as well as the price of spare parts, where the data was processed with the use of stochastic model of supplies. The optimal number of spare parts for the observed equipment in the observed period was y*=4 with the probability of 85% that this amount of spare parts will be sufficient for all malfunctions on the equipment to be eliminated, while taking a 15% risk that one or two spare parts will be acquired with emergency procurements in case of extraordinary circumstances. The model of managing supplies represented in such a way provides an opportunity to be easily applied in agricultural farms, where the values of an optimal solution would be effectively got with previously chosen values of suitable parameters, thus minimizing total expected costs, which would include fixed costs, expenses caused by unsatisfied requests, where the time of waiting for the observed equipment to be fixed would be taken into account