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.
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.
6238404
Fixed point analysis of single cell IEEE 802.11e WLANs: uniqueness, multistability and throughput differentiation
We consider the vector fixed point equations arising out of the analysis of the saturation throughput of a single cell IEEE 802.11e wireless local area network with nodes that have different back-off parameters, including different Arbitration InterFrame Space (AIFS) values. We consider balanced and unbalanced solutions of the fixed point equations arising in homogeneous and nonhomogeneous networks. We are concerned, in particular, with (i) whether the fixed point is balanced within a class, and (ii) whether the fixed point is unique. Our simulations show that when multiple unbalanced fixed points exist in a homogeneous system then the time behaviour of the system demonstrates severe short term unfairness (or multistability). Implications for the use of the fixed point formulation for performance analysis are also discussed. We provide a condition for the fixed point solution to be balanced within a class, and also a condition for uniqueness. We then provide an extension of our general fixed point analysis to capture AIFS based differentiation; again a condition for uniqueness is established. An asymptotic analysis of the fixed point is provided for the case in which packets are never abandoned, and the number of nodes goes to ∞. Finally the fixed point equations are used to obtain insights into the throughput differentiation provided by different initial back-offs, persistence factors, and AIFS, for finite number of nodes, and for differentiation parameter values similar to those in the standard.
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.
5840162
The Case for Non-Cooperative Multihoming of Users to Access Points in IEEE 802.11 WLANs
In many cases, a mobile user has the option of connecting to one of several IEEE 802.11 access points (APs),each using an independent channel. User throughput in each 
AP is determined by the number of other users as well as the 
frame size and physical rate being used. We consider the scenario where users could multihome, i.e., split their traffic amongst all the available APs, based on the throughput they obtain and the price charged. Thus, they are involved in a non-cooperative game with each other. We convert the problem into a fluid model and show that under a pricing scheme, which we call the cost price mechanism, the total system throughput is maximized,i.e., the system suffers no loss of efficiency due to selfish dynamics. We also study the case where the Internet Service 
Provider (ISP) could charge prices greater than that of the cost price mechanism. We show that even in this case multihoming outperforms unihoming, both in terms of throughput as well as profit to the ISP.
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.
8488383
Sorting and selection with structured costs
The study of the effect of priced information on basic algorithmic problems was initiated by M. Charikar et al. (2000). The authors continue the study of sorting and selection in the priced comparison model, i.e., when each comparison has an associated cost, and answer some of the open problems suggested by Charikar et al. If the comparison costs are allowed to be arbitrary, we show that one cannot get good approximation ratios. A different way to assign costs is based on the idea that one can distill out an intrinsic value for each item being compared, such that the cost of comparing two elements is some "well-behaved" or "structured" function of their values. We feel that most practical applications will have some structured cost property. The authors study the problems of sorting and selection (which includes finding the maximum and the median) in the structured cost model. We get a variety of approximation results for these problems, depending on the restrictions we put on the structured costs. We show that it is possible to get much improved results with the structured cost model than the case when we do not have any assumptions on comparison costs.
7923805
A reference model for team-enabled workflow management systems
Abstract Today's workflow systems assume that each work item is executed by a single worker. From the viewpoint of the system, a worker with the proper qualifications selects a work item, executes the associated work, and reports the result. There is usually no support for teams, i.e., groups of people collaborating by jointly executing work items (e.g., the program committee of a conference, the management team of a company, a working group, and the board of directors). In this paper, we propose the addition of a team concept to today's workflow management systems. Clearly, this involves a marriage of workflow and groupware technology. To shed light on the introduction of teams, we extend the traditional organizational meta model with teams and propose a team-enabled workflow reference model. For this reference model and to express constraints with respect to the distribution of work to teams, we use object constraint language (OCL).
2987975
Data streaming algorithms for efficient and accurate estimation of flow size distribution
Knowing the distribution of the sizes of traffic flows passing through a network link helps a network operator to characterize network resource usage, infer traffic demands, detect traffic anomalies, and accommodate new traffic demands through better traffic engineering. Previous work on estimating the flow size distribution has been focused on making inferences from sampled network traffic. Its accuracy is limited by the (typically) low sampling rate required to make the sampling operation affordable. In this paper we present a novel data streaming algorithm to provide much more accurate estimates of flow distribution, using a "lossy data structure" which consists of an array of counters fitted well into SRAM. For each incoming packet, our algorithm only needs to increment one underlying counter, making the algorithm fast enough even for 40 Gbps (OC-768) links. The data structure is lossy in the sense that sizes of multiple flows may collide into the same counter. Our algorithm uses Bayesian statistical methods such as Expectation Maximization to infer the most likely flow size distribution that results in the observed counter values after collision. Evaluations of this algorithm on large Internet traces obtained from several sources (including a tier-1 ISP) demonstrate that it has very high measurement accuracy (within 2%). Our algorithm not only dramatically improves the accuracy of flow distribution measurement, but also contributes to the field of data streaming by formalizing an existing methodology and applying it to the context of estimating the flow-distribution.