Automatic Differentiation for Iterative Process and Its Applications in Network Performance Analysis

In this paper we focus on the application of automatic differentiation (AD)technique on iterative processes. We review some of the results on theconvergence of general iterative processes and the convergence of thederivative code of such iterative processes. We are especially interestedin a class of fixed point iteration problems and we extended some of thoseresults to discuss this class of problems. Finally we apply an AD packageADIC to a network performance evaluation problem for numerical experimentsto get sensitivities of network blocking probabilities w.r.t. networkoffered traffic load

Performance Analysis and Multi-Objective Design for Multirate Multihop Loss Networks

In this paper, we consider a class of loss networks where multipletraffic classes are present, each has different bandwidth requirement,and each traffic stream is routed according to an adaptive routingscheme.We propose a fixed-point method, a.k.a. reduced load approximation,to estimate the end-to-end blocking probability for such networks.The approximation scheme is shownto be asymptotically correct in a natural limiting regime, and it givesconservative estimates of blocking probabilities under heavy trafficload.Simulation results are provided to compare performance estimatesobtained from our analytical approximation scheme and discrete eventsimulations.We also show how this analytical approximation scheme can be linked withnumerical mathematical programming tools to help design a network,by selecting network design parameters via trade-off analysis, evenwith several design objectives.In one application we use the multi-objective optimization toolCONSOL-OPTCAD to design trunk reservation parameters and balance linkcapacity. In another application we use automatic differentiationto get sensitivities of blocking probabilities w.r.t. offered trafficload

Hierarchical Loss Network Model for Performance Evaluation

In this paper we present a hierarchical loss network model for estimatingthe end-to-end blocking probabilities for large networks. As networks grow in size, nodes tendto form clusters geographically and hierarchical routing schemes are morecommonly used. Loss network and reduced load models are often used toapproximate end-to-endcall blocking probabilities, and hence, throughput. However so far all workbeing done in this area is for flat networks with flat routing schemes.We aim at developing a more efficient approximation method for networksthat have a natural hierarchy and/or when some form of hierarchical routingpolicy is used. We present two hierarchical models in detail for fixedhierarchical routing and dynamic hierarchical routing policies,respectively, via the notion of network abstraction, route segmentation, traffic segregationand aggregation. Computation is done separately within each cluster (local)and among clusters (global), and the fixed point is obtained by iterationbetween local and global computations. We also present numerical resultsfor the first case

Hierarchical Modeling for Network Performance Evaluation

In this paper we present a hierarchical network model to estimatethe connection blocking for large hierarchical networks.As networks grow in size, nodes tendto form clusters geographically and hierarchical routing schemes are morecommonly used, and it is important that network modeling methods havescale-up capabilities. Loss networks and reduced load/fixed point modelsare often used toapproximate call blocking probabilities and hence throughput in a circuitswitched network. We use the same idea for estimating connection blockingin a data network with certain QoS routing schemes. However so far most workbeing done in this area is for flat networks with flat routing schemes.We aim at developing a more efficient approximation method for networksthat have a natural hierarchy and/or when some form of hierarchical routingpolicy is used. We present hierarchical models in detail for fixedhierarchical routing and dynamic hierarchical routing policies,respectively, viathe notion of network abstraction, route segmentation, traffic segregationand aggregation. Computation is done separately within each cluster (local)and among clusters (global), and the fixed point is obtained by iterationbetween local and global computations. We present results from bothnumerical experiments and discrete event simulations

Performance Evaluation in Multi-Rate, Multi-Hop Communication Networks with Adaptive Routing

Accurate performance evaluation has always been an important issue in network design and analysis. Discrete event simulation has been known to be accurate but very time consuming. A particular performance metric of interest is the end-to-end blocking probability in a circuit-switched loss network. Various analytical approaches and approximation schemes have been suggested and among them, the fixed-point method, or reduced load method, has been receiving much attention. However, most of these schemes either consider only single traffic rate situations or multi-rate traffic under fixed routing. We develop an approximation scheme to estimate end-to-end blocking probability in a multi-rate multi-hop network with an adaptive routing scheme. The approximation results are compared with that of discrete event simulation. An example of application is also provided in which the proposed scheme is linked to the optimization tool CONSOL-OPTCAD to get network design trade-offs. This paper was presented at the "ATIRP ARL Federal Laboratory 2nd Annual Conference," February 5-6, 1998, University of Maryland, College Park campus

Modeling and Simulation of Large Hybrid Networks

This paper describes a modeling and simulation framework for large hybridnetworks that include satellites, terrestrial wireless and mobile ad hocnetworks. The purpose of the simulation framework is to parallel the actualimplementation of a testbed network currently being constructed at ARL.The modeling framework uses the performance measures generated bythe simulation to analytically study larger scaled versions of thetestbed networks. The combination of the two methodologies allows thefeasibility of the testbed architecture's widespread implementation to bestudied without the associated costs of performing such experiments withactual equipment. Additionally, technological tradeoffs and interoperabilityissues can be studied so that informed decisions can be made about theimplementation of future military communication networks.This paper has been published in the Proceedings of 2nd Annual ATIRP Conference(ATIRP'99). </I

Tactical and Strategic Communication Network Simulation and Performance Analysis

We describe a framework for the efficient modeling and performance evaluation of large networks consisting of mixture of strategic and tactical components. The method emphasizes hierarchical, layered techniques that are fed parametric models at the lower level. In addition to the algorithmic structure, and some initial algorithms we describe an object oriented software architecture that is under development to support these algorithmic methods in a distributed environment

RNA-Seq of Human Neurons Derived from iPS Cells Reveals Candidate Long Non-Coding RNAs Involved in Neurogenesis and Neuropsychiatric Disorders

Genome-wide expression analysis using next generation sequencing (RNA-Seq) provides an opportunity for in-depth molecular profiling of fundamental biological processes, such as cellular differentiation and malignant transformation. Differentiating human neurons derived from induced pluripotent stem cells (iPSCs) provide an ideal system for RNA-Seq since defective neurogenesis caused by abnormalities in transcription factors, DNA methylation, and chromatin modifiers lie at the heart of some neuropsychiatric disorders. As a preliminary step towards applying next generation sequencing using neurons derived from patient-specific iPSCs, we have carried out an RNA-Seq analysis on control human neurons. Dramatic changes in the expression of coding genes, long non-coding RNAs (lncRNAs), pseudogenes, and splice isoforms were seen during the transition from pluripotent stem cells to early differentiating neurons. A number of genes that undergo radical changes in expression during this transition include candidates for schizophrenia (SZ), bipolar disorder (BD) and autism spectrum disorders (ASD) that function as transcription factors and chromatin modifiers, such as POU3F2 and ZNF804A, and genes coding for cell adhesion proteins implicated in these conditions including NRXN1 and NLGN1. In addition, a number of novel lncRNAs were found to undergo dramatic changes in expression, one of which is HOTAIRM1, a regulator of several HOXA genes during myelopoiesis. The increase we observed in differentiating neurons suggests a role in neurogenesis as well. Finally, several lncRNAs that map near SNPs associated with SZ in genome wide association studies also increase during neuronal differentiation, suggesting that these novel transcripts may be abnormally regulated in a subgroup of patients

Network Performance Modeling, Design and Dimensioning Technologies

Providing accurate estimates of performance in large heterogeneousinternetworks, for the purposes of network design and planning andfor service provisioning has become a critical problem. This is dueto the heterogeneity of the physical medium, the size of currentand future networks and the different quality of service requirementsfor multimedia services. In this thesis we describe our work onthe development of connection level mathematical models used forestimating network performance characteristics such as throughput,delay and blocking probability. The type of models we use andinvestigate are of the "Loss Network" type, which have been usedwidely in legacy telephone networks and in cellular networks forestimating "availability". These network models can also be used inestimating performance in general packet-switched networks usingeffective bandwidth concepts. In particular, these models are directlyapplicable in studying connection blocking for networks using QoSrouting schemes. Computational complexity is a serioususability bottleneck for such algorithms. We describe fast (twoto three orders of magnitude faster than discrete event simulation)approximation algorithms we have developed for accurately estimatingblocking probability in a random topology network, using state-dependentrouting, with multiple classes of traffic. We describe even fasteralgorithms based on a hierarchical loss network model we have developed.The latter are well matched to networks that have a natural hierarchicalarchitecture, or which use some form of hierarchical routing to furtherreduce computational cost. We also developed models for networks usingdelay-based QoS routing. An important objective of our work is todemonstrate the utility of these models for effective design anddimensioning of a large network so that a certain set of QoS requirementsare met. We show how typical design and dimensioning problems can beformulated as a multi-objective constrained optimization problem, usingperformance estimation network models; an approach that leads naturallyto very useful trade-off analysis. We describe our research in thedevelopment of a general network design and dimensioning methodology bylinking our performance models with Automatic Differentiation andmulti-objective optimization algorithms and tools. We presentexamples and applications that demonstrate the speed and versatility ofour methodology and algorithms

User's Guide for ADIFFSQP Version 0.91

ADIFFSQP is a utility program that allows to user of the FFSQP[1] constrained nonlinear optimization routines to invoke the computational differentiation (or automatic differentiation:AD) preprocessor ADIFOR2.0 [2] convenientl