Oleg Gusak

Performance Evaluation of the 802.16 Medium Access Control Layer

In this work we investigate performance of the medium access control layer of an 802.16 wireless network consisting of 100 subscriber stations (SSs) and a single base stati on (BS). Experimental results show that the average packet queuing delay was virtually the same for weighted round robin and weighted fair queuing scheduling algorithms. Another interesting finding is that adapting the uplink/downlink ratio plays a crucial role in performance as the network load increases and channel conditions change. On the other hand, experiments show that for a higher network load, segmentation of large packets is a necessity in order to achieve performance and QoS conformance. We also observed a smaller average queuing delay for smaller values of frame duration.

Stochastic Automata Networks and Near Complete Decomposability

Stochastic automata networks (SANs) have been developed and used in the last fifteen years as a modeling formalism for large systems that can be decomposed into loosely connected components. In this work, we extend the near complete decomposability concept of Markov chains (MCs) to SANs so that the inherent difficulty associated with solving the underlying MC can be forecasted and solution techniques based on this concept can be investigated. A straightforward approach to finding a nearly completely decomposable (NCD) partitioning of the MC underlying a SAN requires the computation of the nonzero elements of its global generator. This is not feasible for very large systems even in sparse matrix representation due to memory and execution time constraints. We devise an efficient decompositional solution algorithm to this problem that is based on analyzing the NCD structure of each component of a given SAN. Numerical results show that the given algorithm performs much better than the straightforward approach.

Iterative disaggregation for a class of lumpable discrete-time stochastic automata networks

Stochastic automata networks (SANs) have been developed and used in the last 15 years as a modeling formalism for large systems that can be decomposed into loosely connected components. In this work, we concentrate on the not so much emphasized discrete-time SANs. First, we remodel and extend an SAN that arises in wireless communications. Second, for an SAN with functional transitions, we derive conditions for a special case of ordinary lumpability in which aggregation is done automaton by automaton. Finally, for this class of lumpable discrete-time SANs we devise an efficient aggregation-iterative disaggregation algorithm and demonstrate its performance on the SAN model of interest.

Lumpable continuous-time stochastic automata networks

Abstract The generator matrix of a continuous-time stochastic automata network (SAN) is a sum of tensor products of smaller matrices, which may have entries that are functions of the global state space. This paper specifies easy to check conditions for a class of ordinarily lumpable partitionings of the generator of a continuous-time SAN in which aggregation is performed automaton by automaton. When there exists a lumpable partitioning induced by the tensor representation of the generator, it is shown that an efficient aggregation-iterative disaggregation algorithm may be employed to compute the steady-state distribution. The results of experiments with two SAN models show that the proposed algorithm performs better than the highly competitive block Gauss–Seidel in terms of both the number of iterations and the time to converge to the solution.

Performance Analysis of Packet Encapsulation and Aggregation

In an attempt to increase data throughput, many modern data transmission protocols provide capabilities for aggregating transmitted data fragments into larger packets at the time of encapsulation in a particular OSI layer. The decision and ability to aggregate packets into a single frame can have significant impact on the performance of the communication system. The impact can be even more substantial when the system operates under a heavy load. In this paper, we present a queuing model which describes a packet encapsulation and aggregation process. We assume Poisson arrivals and phase-type service time distributions for the transmitted packets. Using the proposed queuing model, we provide analysis of the end-to-end delay of a packet transmitted by the system. We verify analytical results with a simulation model of the system. Based on results of experiments with the analytical model, we provide the maximum number of packets in a single frame for which packet aggregation minimizes the average total delay of a packet for various system loads and sizes of the packet header. It is numerically shown that when the load is high, the higher the variability of the packet service time, the higher the maximum allowed number of packets in the frame should be to achieve the minimum average total packet delay. On the other hand, the impact of the variability of the packet service time is insignificant when the system load is moderate or low.

Analysis of blocking probability in WDM all-optical networks with non-Poisson traffic statistics

We study blocking probability in wavelength division multiplexing (WDM) optical networks. We consider two type of networks: with and without wavelength conversion, and two types of wavelength assignment policies: random wavelength assignment and first fit. We have shown that difference between values of blocking probability is significant for the cases when input flow characteristics are distributed according to memoryless and general distribution. We have found that values of blocking probability for models with general distribution are upperbounded by the values of memoryless distribution case. We have also considered a model with non-uniformly distributed destination node for an incoming connection request.

A model of a packet aggregation system

The decision and ability to aggregate packets can have significant impact on the performance of a communication system. The impact can be even more substantial when the system operates under a heavy load. In this paper, we present a queuing model which describes a packet encapsulation and aggregation process. Using this model, we provide analysis of the end-to-end delay of a packet transmitted by the system. The analytical model is verified by a simulation model of the system. We calculate the maximum number of packets in a single frame for which packet aggregation minimizes the average total delay of a packet. It is numerically shown that when the load is high, the higher the variability of the packet service time, the higher the maximum allowed number of packets in the frame should be to achieve the minimum average total packet delay. However, the impact of the variability of the packet service time is insignificant when the system load is moderate or low.

Performance Analysis of Packet Schedulers in High-Speed Serial Switches

In this work we examine the performance of arbitration algorithms for core high-speed serial switches (HSSS). Taking Infiniband as an example, experimental results show that, for a homogeneous network load, the average queuing delay for the switch output ports under the weighted round-robin (WRR) algorithm defined for InfiniBand is similar to the average queuing delay resulting from the largest delay-first (LDF) or first-in-first-out (FIFO) algorithms. For a 4-port switch, when the average load is high (close to 95% of the network capacity) and unbalanced with respect to the WRR weights, the difference in average delay between WRR and LDF or FIFO is large. However, for a 20-port switch and the same high unbalanced average network load, this difference is less than half of that of the 4-port switch. Further, the average queuing delay difference between WRR and LDF or FIFO diminishes quickly as the average load decreases. Hence, even for a fairly high average load, LDF or FIFO can be suggested for arbitration in core HSSS.