15724188
Instability and performance limits of distributed simulators of feedforward queueing networks
In this article we study the performance of distributed simulation of open feedforward queueing networks, by analyzing queueing models of message flows in distributed discrete event simulators. We view each logical process in a distributed simulation as comprising a message sequencer with associated message queues, followed aby an event processor. We introduce the idealized, but analytically useful, comcept of maximum lookahead. We show that, with quite general stochatstic assumptions for message arrival and time-stamp processes, the meassage queues are unstable for conservative sequencing, and for conservative sequencing with maximum lookahead and hence for optimistic resequencing, and for any resequenceing algorithm that does not employ interprocessor flow control. Finally, we provide formulas for the throughput of distributed simulators of feedforward queueing networks.
5368108
A stochastic approximation approach for max-min fair adaptive rate control of ABR sessions with MCRs
The available bit rate (ABR) sessions in an ATM network share the bandwidth left over after guaranteeing service to constant bit rate (CBR) and variable bit rate (VBR) traffic. Hence the bandwidth available to ABR sessions is randomly varying. This bandwidth must be shared by the sessions in a max-min fair fashion. Our point of departure in this paper is to formulate the problem of determining the max-min fair session rates as the problem of finding the root of a certain nonlinear vector equation; the same formulation also arises with our notion of max-min fairness with positive minimum cell rates (MCRs). This formulation allows us to use a stochastic approximation algorithm for online distributed computation of the max-min fair rates. We use the well known ordinary differential equation technique to prove convergence of the algorithm in the synchronous update case. We provide simulation results using the NIST simulator to show that the algorithm is able to track the max-min fair rates for slowly varying random available link bandwidths.
43715944
Performance Analysis and Scheduling of Stochastic Fork-Join Jobs in a Multicomputer System
The authors model a parallel processing system comprising several homogeneous computers interconnected by a communication network. Jobs arriving to this system have a linear fork-join structure. Each fork of the job gives rise to a random number of tasks that can be processed independently on any of the computers. Since exact analysis of fork-join models is known to be intractable, the authors resort to obtaining analytical bounds to the mean job response time of the fork-join job. For jobs with a single fork-join and, probabilistic allocation of tasks of the job to the N processors, they obtain upper and lower bounds to the mean job response time. Upper bounds are obtained using the concept of associated random variables and are found to be a good approximation to the mean job response time. A simple lower bound is obtained by neglecting queueing delays. They also find two lower bounds that include queueing delays. For multiple fork-join jobs, they study an approximation based on associated random variables. Finally, two versions of the join-the-shortest-queue (JSQ) allocation policy (i.e., JSQ by batch and JSQ by task) are studied and compared, via simulations and diffusion limits. >
6212998
Performance of TCP congestion control with explicit rate feedback
We consider a modification of TCP congestion control in which the congestion window is adapted to explicit bottleneck rate feedback; we call this RATCP (Rate Adaptive TCP). Our goal in this paper is to study and compare the performance of RATCP and TCP in various network scenarios with a view to understanding the possibilities and limits of providing better feedback to TCP than just implicit feedback via packet loss. To understand the dynamics of rate feedback and window control, we develop and analyze a model for a long-lived RATCP (and TCP) session that gets a time-varying rate on a bottleneck link. We also conduct experiments on a Linux based test-bed to study issues such as fairness, random losses, and randomly arriving short file transfers. We find that the analysis matches well with the results from the test-bed. For large file transfers, under low background load, ideal fair rate feedback improves the performance of TCP by 15%-20%. For small randomly arriving file transfers, though RATCP performs only slightly better than TCP it reduces losses and variability of throughputs across sessions. RATCP distinguishes between congestion and corruption losses, and ensures fairness for sessions with different round trip times sharing the bottleneck link. We believe that rate feedback mechanisms can be implemented using distributed flow control and recently proposed REM in which case, ECN bit itself can be used to provide the rate feedback.
17761375
Comparative performance analysis of versions of TCP in a local network with a lossy link
We use a stochastic model to study the throughput performance of various transport control protocol (TCP) versions (Tahoe (including its older version that we call OldTahoe), Reno, and NewReno) in the presence of random losses on a wireless link in a local network. We model the cyclic evolution of TCP, each cycle starting at the epoch at which recovery starts from the losses in the previous cycle. TCP throughput is computed as the reward rate in a certain Markov renewal-reward process. Our model allows us to study the performance implications of various protocol features, such as fast retransmit and fast recovery. We show the impact of coarse timeouts. In the local network environment the key issue is to avoid a coarse timeout after a loss occurs. We show the effect of reducing the number of duplicate acknowledgements (ACKs) for triggering a fast retransmit. A large coarse timeout granularity seriously affects the performance of TCP, and the various protocol versions differ in their ability to avoid a coarse timeout when random loss occurs; we quantify these differences. We show that, for large packet-loss probabilities, TCP-Reno performs no better, or worse, than TCP-Tahoe. TCP-NewReno is a considerable improvement over TCP-Tahoe, and reducing the fast-retransmit threshold from three to one yields a large gain in throughput; this is similar to one of the modifications in the TCP-Vegas proposal. We explain some of these observations in terms of the variation of fast-recovery probabilities with packet-loss probability. The results of our analysis compare well with a simulation that uses actual TCP code.
8290753
Time and energy complexity of distributed computation in wireless sensor networks
We consider a scenario where a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing the maximum value of the measurements and communicating it to an operator station. We view the problem as one of message passing distributed computation over a geometric random graph. The network is assumed to be synchronous; at each sampling instant each sensor measures a value, and then the sensors collaboratively compute and deliver the maximum of these values to the operator station. Computation algorithms differ in the messages they need to exchange, and our formulation focuses on the problem of scheduling of the message exchanges. We do not exploit techniques such as source compression, or block coding of the computations. For this problem, we study the computation time and energy expenditure for one time maximum computation, and also the pipeline throughput. We show that, for an optimal algorithm, the computation time, energy expenditure and the achievable rate of computation scale as /spl Theta/(/spl radic/ n/log n), /spl Theta/(n) and /spl Theta/(1/log n) asymptotically (in probability) as the number of sensors n/spl rarr//spl infin/. We also analyze the performance of three specific computational algorithms, namely, the tree algorithm, multihop transmission, and the ripple algorithm, and obtain scaling laws for the computation time and energy expenditure as n/spl rarr//spl infin/. Simulation results are provided to show that our analysis indeed captures the correct scaling; the simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized scheduler and hence our results can be viewed as providing bounds for the performance with a distributed scheduler.
1890977
W-RBAC - A Workflow Security Model Incorporating Controlled Overriding of Constraints
This paper presents a pair of role-based access control models for workflow systems, collectively known as the W-RBAC models. The first of these models, W0-RBAC is based on a framework that couples a powerful RBAC-based permission service and a workflow component with clear separation of concerns for ease of administration of authorizations. The permission service is the focus of the work, providing an expressive logic-based language for the selection of users authorized to perform workflow tasks, with preference ranking. W1-RBAC extends the basic model by incorporating exception handling capabilities through controlled and systematic overriding of constraints.
7291217
Merging workflows: A new perspective on connecting business processes
This paper describes the concept of workflow merge and methods for merging business processes. We grouped merges in four categories according to the type of merge: sequential, parallel, conditional, and iterative, and describe the corresponding algorithms for performing these operations. We give results that allow us to determine whether a merge operation is sound. It is shown that to avoid invalid merges, one should choose merge points between which a sub-workflow, called a merge region, is well structured. These findings can provide useful guidance for future workflow merge research. We also raise issues of more complex merge problems, such as merge conflicts, semantic ambiguities and workflow splits.
39839954
A randomized algorithm for distributed consensus
We describe a randomized, fully distributed algorithm for distributed consensus and evaluate its performance assuming probabilistically bounded message delay. Each node randomly contacts a few other nodes and incorporates their values into its own value. All the nodes are able to reach consensus in this manner after a few rounds. The results show that the randomized algorithm is flexible, efficient and robust, and offers several advantages over a deterministic algorithm.
28378631
The Universal Medical Language System and the Gene Ontology: Some Critical Reflections
The Unified Medical Language System and the Gene Ontology are among the most widely used terminology resources in the biomedical domain. However, when we evaluate them in the light of simple principles for well-constructed ontologies we find a number of characteristic inadequacies. Employing the theory of granular partitions, a new approach to the understanding of ontologies and of the relationships ontologies bear to instances in reality, we provide an application of this theory in relation to an example drawn from the context of the pathophysiology of hypertension. This exercise is designed to demonstrate how, by taking ontological principles into account we can create more realistic biomedical ontologies which will also bring advantages in terms of efficiency and robustness of associated software applications.
7719957
Connectivity and inference problems for temporal networks
Many network problems are based on fundamental relationships involving time. Consider, for example, the problems of modeling the flow of information through a distributed network, studying the spread of a disease through a population, or analyzing the reachability properties of an airline timetable. In such settings, a natural model is that of a graph in which each edge is annotated with a time label specifying the time at which its endpoints "communicated." We will call such a graph a temporal network. To model the notion that information in such a network "flows" only on paths whose labels respect the ordering of time, we call a path time-respecting if the time labels on its edges are non-decreasing. The central motivation for our work is the following question: how do the basic combinatorial and algorithmic properties of graphs change when we impose this additional temporal condition? The notion of a path is intrinsic to many of the most fundamental algorithmic problems on graphs; spanning trees, connectivity, flows, and cuts are some examples. When we focus on time-respecting paths in place of arbitrary paths, many of these problems acquire a character that is different from the traditional setting, but very rich in its own right. We provide results on two types of problems for temporal networks. First, we consider connectivity problems, in which we seek disjoint time-respecting paths between pairs of nodes. The natural analogue of Menger's Theorem for node-disjoint paths fails in general for time-respecting paths; we give a non-trivial characterization of those graphs for which the theorem does hold in terms of an excluded subdivision theorem, and provide a polynomial-time algorithm for connectivity on this class of graphs. (The problem on general graphs is NP-complete.) We then define and study the class of inference problems, in which we seek to reconstruct a partially specified time labeling of a network in a manner consistent with an observed history of information flow.