Admission control in shared memory switches
Cloud applications bring new challenges to the design of network elements, in particular the burstiness of traffic workloads. A shared memory switch is a good candidate architecture to exploit buffer capacity; in this work, we analyze the performance of this architecture. Our goal is to explore the impact of additional traffic characteristics such as varying processing requirements and packet values on objective functions. The outcome of this work is a better understanding of the relevant parameters for buffer management to achieve better performance in dynamic environments of data centers. We consider a model that captures more of the properties of the target architecture than previous work and consider several scheduling and buffer management algorithms that are specifically designed to optimize its performance. In particular, we provide analytic guarantees for the throughput performance of our algorithms that are independent from specific distributions of packet arrivals. We furthermore report on a comprehensive simulation study which validates our analytic results.
Modern network elements are increasingly required to deal with heterogeneous traffic. Recent works consider processing policies for buffers that hold packets with different processing requirements (number of processing cycles needed before a packet can be transmitted out) but uniform value, aiming to maximize the throughput, i.e., the number of transmitted packets. Other developments deal with packets of varying value but uniform processing requirement (each packet requires one processing cycle); the objective here is to maximize the total transmitted value. In this paper, we consider a more general problem, combining packets with both nonuniform processing and nonuniform values in the same queue. We study the properties of various processing orders in this setting. We show that in the general case, natural processing policies have poor performance guarantees, with linear lower bounds on their competitive ratio. Moreover, we show several adversarial lower bounds for every priority queue and even for every online policy. On the positive side, in the special case when only two different values are allowed, 1 and V , we present a policy that achieves competitive ratio (1+(W+2/V)) , where W is the maximal number of required processing cycles. We also consider copying costs during admission.
Modern network processors increasingly deal with packets that require heterogeneous processing. We consider a bounded size input queue buffer where each packet requires several rounds of processing before transmission. Usually the transmission order of packets is induced by processing order, but processing order can have significant impact on the performance of buffer management policies even if the transmission order is fixed. We introduce the class of Semi-FIFO policies that decouple processing order from transmission order, restricting the latter to First-In-First-Out (FIFO). We build a taxonomy of Semi-FIFO policies and provide worst case guarantees for different processing orders. We consider various special cases and properties of Semi-FIFO policies: greedy, work-conserving, lazy, and push-out policies, and show how these properties affect performance. We generalize our results to additional constraints related to copying cost and conduct a comprehensive simulation study that validates our results.
We consider the fundamental problem of managing a bounded size queue buffer where traffic consists of packets of varying size, each packet requires several rounds of processing before it can be transmitted out, and the goal is to maximize the throughput, i.e., total size of successfully transmitted packets. Our work addresses the tension between two conflicting algorithmic approaches: favoring packets with fewer processing requirements as opposed to packets of larger size. We present a novel model for studying such systems and study the performance of online algorithms that aim to maximize throughput.
Buffer management policies are online algorithms that control a limited buffer of packets with homogeneous or heterogeneous characteristics, deciding whether to accept new packets when they arrive, which packets to process and transmit, and possibly whether to push out packets already residing in the buffer. Although settings differ, the problem is always to achieve the best possible competitive ratio, i.e., find a policy with good worst-case guarantees in comparison with an optimal offline clairvoyant algorithm.
Packet processing increasingly involves heterogeneous requirements. We consider the well-known model of a shared memory switch with bounded-size buffer and generalize it in two directions. First, we consider unit-sized packets labeled with an output port and a processing requirement (i.e., packets with heterogeneous processing), maximizing the number of transmitted packets. We analyze the performance of buffer management policies under various characteristics via competitive analysis that provides uniform guarantees across traffic patterns (Borodin and ElYaniv 1998). We propose the Longest-Work-Drop policy and show that it is at most 2-competitive and at least -competitive. Second, we consider another generalization, posed as an open problem in Goldwasser (2010), where each unit-sized packet is labeled with an output port and intrinsic value, and the goal is to maximize the total value of transmitted packets. We show first results in this direction and define a scheduling policy that, as we conjecture, may achieve constant competitive ratio. We also present a comprehensive simulation study that validates our results.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Generalized error-locating codes are discussed. An algorithm for calculation of the upper bound of the probability of erroneous decoding for known code parameters and the input error probability is given. Based on this algorithm, an algorithm for selection of the code parameters for a specified design and input and output error probabilities is constructed. The lower bound of the probability of erroneous decoding is given. Examples of the dependence of the probability of erroneous decoding on the input error probability are given and the behavior of the obtained curves is explained.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The Handbook of CO₂ in Power Systems' objective is to include the state-of-the-art developments that occurred in power systems taking CO₂ emission into account. The book includes power systems operation modeling with CO₂ emissions considerations, CO₂ market mechanism modeling, CO₂ regulation policy modeling, carbon price forecasting, and carbon capture modeling. For each of the subjects, at least one article authored by a world specialist on the specific domain is included.