This paper presents a database containing 'ground truth' segmentations produced by humans for images of a wide variety of natural scenes. We define an error measure which quantifies the consistency between segmentations of differing granularities and find that different human segmentations of the same image are highly consistent. Use of this dataset is demonstrated in two applications: (1) evaluating the performance of segmentation algorithms and (2) measuring probability distributions associated with Gestalt grouping factors as well as statistics of image region properties.

/pdf/a-database-of-human-segmented-natural-images-and-its-2ve1vk356s.pdf

A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

https://deim.urv.cat/~alexandre.arenas/publicacions/pdf/review.pdf

Synchronization in complex networks

This survey covers rollback-recovery techniques that do not require special language constructs. In the first part of the survey we classify rollback-recovery protocols into checkpoint-based and log-based.Checkpoint-based protocols rely solely on checkpointing for system state restoration. Checkpointing can be coordinated, uncoordinated, or communication-induced. Log-based protocols combine checkpointing with logging of nondeterministic events, encoded in tuples called determinants. Depending on how determinants are logged, log-based protocols can be pessimistic, optimistic, or causal. Throughout the survey, we highlight the research issues that are at the core of rollback-recovery and present the solutions that currently address them. We also compare the performance of different rollback-recovery protocols with respect to a series of desirable properties and discuss the issues that arise in the practical implementations of these protocols.

/pdf/a-survey-of-rollback-recovery-protocols-in-message-passing-bnrpate93a.pdf

A survey of rollback-recovery protocols in message-passing systems

Parallel discrete event simulation (PDES), sometimes called distributed simulation, refers to the execution of a single discrete event simulation program on a parallel computer. PDES has attracted a considerable amount of interest in recent years. From a pragmatic standpoint, this interest arises from the fact that large simulations in engineering, computer science, economics, and military applications, to mention a few, consume enormous amounts of time on sequential machines. From an academic point of view, parallel simulation is interesting because it represents a problem domain that often contains substantial amounts of parallelism (e.g., see [59]), yet paradoxically, is surprisingly difficult to parallelize in practice. A sufficiently general solution to the PDES problem may lead to new insights in parallel computation as a whole. Historically, the irregular, data-dependent nature of PDES programs has identified it as an application where vectorization techniques using supercomputer hardware provide little benefit [14].A discrete event simulation model assumes the system being simulated only changes state at discrete points in simulated time. The simulation model jumps from one state to another upon the occurrence of an event. For example, a simulator of a store-and-forward communication network might include state variables to indicate the length of message queues, the status of communication links (busy or idle), etc. Typical events might include arrival of a message at some node in the network, forwarding a message to another network node, component failures, etc.We are especially concerned with the simulation of asynchronous systems where events are not synchronized by a global clock, but rather, occur at irregular time intervals. For these systems, few simulator events occur at any single point in simulated time; therefore parallelization techniques based on lock-step execution using a global simulation clock perform poorly or require assumptions in the timing model that may compromise the fidelity of the simulation. Concurrent execution of events at different points in simulated time is required, but as we shall soon see, this introduces interesting synchronization problems that are at the heart of the PDES problem.This article deals with the execution of a simulation program on a parallel computer by decomposing the simulation application into a set of concurrently executing processes. For completeness, we conclude this section by mentioning other approaches to exploiting parallelism in simulation problems.Comfort and Shepard et al. have proposed using dedicated functional units to implement specific sequential simulation functions, (e.g., event list manipulation and random number generation [20, 23, 47]). This method can provide only a limited amount of speedup, however. Zhang, Zeigler, and Concepcion use the hierarchical decomposition of the simulation model to allow an event consisting of several subevents to be processed concurrently [21, 98]. A third alternative is to execute independent, sequential simulation programs on different processors [11, 39]. This replicated trials approach is useful if the simulation is largely stochastic and one is performing long simulation runs to reduce variance, or if one is attempting to simulate a specific simulation problem across a large number of different parameter settings. However, one drawback with this approach is that each processor must contain sufficient memory to hold the entire simulation. Furthermore, this approach is less suitable in a design environment where results of one experiment are used to determine the experiment that should be performed next because one must wait for a sequential execution to be completed before results are obtained.

/pdf/parallel-discrete-event-simulation-m759whzicd.pdf

Parallel discrete event simulation

A number of library based parallel and sequential network simulators have been designed. The paper describes a library, called GloMoSim (Global Mobile system Simulator), for parallel simulation of wireless networks. GloMoSim has been designed to be extensible and composable: the communication protocol stack for wireless networks is divided into a set of layers, each with its own API. Models of protocols at one layer interact with those at a lower (or higher) layer only via these APIs. The modular implementation enables consistent comparison of multiple protocols at a given layer. The parallel implementation of GloMoSim can be executed using a variety of conservative synchronization protocols, which include the null message and conditional event algorithms. The paper describes the GloMoSim library, addresses a number of issues relevant to its parallelization, and presents a set of experimental results on the IBM 9076 SP, a distributed memory multicomputer. These experiments use models constructed from the library modules.

GloMoSim: a library for parallel simulation of large-scale wireless networks

Existing research has defined a new type of simulation time called Approximate Time, where the simulation's knowledge about the values that represent time is uncertain. The approach is based on temporal uncertainty and uses time intervals rather than precise time values to represent time. Simulation language constructs are necessary to provide a convenient means of exploiting the temporal uncertainty to simulation modelers. To address this problem, a new time advance primitive for process-oriented simulations was developed, termed the interval hold construct. Interval hold is an extension of the well-known hold primitive used in conventional simulation languages. This paper defines the interval time advance primitive and describes an algorithm for implementing it.

/pdf/exploiting-temporal-uncertainty-in-process-oriented-7jiag5tmbk.pdf

Exploiting temporal uncertainty in process-oriented distributed simulations

Ad hoc distributed simulation, a methodology for embedded online simulation, has been studied for the steady-state simulation of open queueing networks. However, for most online simulation applications, the capability of a simulation approach to respond to system dynamics is at least as important as the performance in steady-state analysis. Hence, this paper focuses on the prediction accuracy of the ad hoc approach in open queueing networks with short-term system-state transients. We empirically demonstrate that, with slight modification to the prior ad hoc approach for steady-state studies, system dynamics can be modeled appropriately. Furthermore, a potential livelock issue that arises with the modification is addressed.

On the transient response of open queueing networks using ad hoc distributed simulations

Many of today's military services and applications run on geographically distributed sites. Before these services and applications can be deployed in an actual network, they need to be tested and evaluated under realistic scenarios with many unpredictable factors. Existing experimental tools cannot meet the requirements for scale, accuracy and timeliness. A network emulation framework called ROSENET is proposed that can meet these requirements by using a remote parallel simulation server to model a wide area network and a local network emulator to provide timely QoS predictions for testing real world applications. This paper discusses the challenges faced in applying ROSENET to defense applications through two case studies. In the first case study we apply synthetic traffic workloads over DARPA's NMS network topology for a large scale simulation and define a metric called remote emulation delay to evaluate and quantify ROSENET's performance. In the second case study we illustrate the procedures using ROSE...

Remote Network Emulation for Defense Applications

The Chapter describes an approach of the dynamic data-driven applications systems (DDDAS) paradigm to reduce fuel consumption and emissions in surface transportation systems. The approach includes algorithms and distributed simulations to predict space-time trajectories of onroad vehicles. Given historical and real-time measurement data from the road network, computation resources residing in the vehicle generate speed/acceleration profiles used to estimate fuel consumption and emissions. These predictions are used to suggest energy-efficient routes to the driver. Because many components of the envisioned DDDAS system operate on mobile computing devices, a distributed computing architecture and energy-efficient middleware and simulations are proposed to maximize battery life. Energy and emissions modeling and mobile client power measurements are also discussed.

Energy-Aware Dynamic Data-Driven Distributed Traffic Simulation for Energy and Emissions Reduction

This manual gives an introduction to writing parallel discrete event simulation programs for the Georgia Tech Time Warp (GTW) system (version 3.1). Time Warp is a synchronization mechanism for parallel discrete event simulation programs. GTW is a Time Warp simulation kernel implemented on distributed network of uniprocessor and shared memory multiprocessor machines. Use of this program shall be restricted to internal research purposes only, and it may not be redistributed in any form without authorization from the Georgia Tech Research Corporation. Derivative works must carry this Copyright notice. This program is provided as is and Georgia Tech Research Corporation disclaims all warranties with regard to this program. In no event shall Georgia Tech Research Corporation be liable for any damages arising out of or in connection with the use or performance of this program.

/pdf/georgia-tech-time-warp-gtw-version-3-1-programmer-s-manual-4h8t3nrz19.pdf

Richard M. Fujimoto

Papers

Exploiting temporal uncertainty in process-oriented distributed simulations

On the transient response of open queueing networks using ad hoc distributed simulations

Remote Network Emulation for Defense Applications

Energy-Aware Dynamic Data-Driven Distributed Traffic Simulation for Energy and Emissions Reduction

Georgia Tech Time Warp (GTW Version 3.1) Programmer's Manual for Distributed Network of Workstations