In this paper, we propose a genetic algorithm-based method for evaluation of operational plans within effects-based planning. We formulate the effects-based planning problem as a bi-objective optimization problem, in which the distance from the initial state to the current state (g) and the distance from the current state to the desired end state (h) are minimized. To solve the problem, we adopt Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Considering an expeditionary operation scenario, we simulate a subset of possible plans and present the decision maker with a set of promising plans which are capable of approaching the desired end state efficiently. In order to discuss the efficiency and effectiveness of the algorithm, we compare the results of NSGA-II with the results of A*. The computational results show that NSGA-II is much more efficient than A* with regard to g. On the other hand A* is a little more effective with regard to h.

Maintaining interactivity is one of the key challenges in distributed virtual environments (DVEs). In this paper, we consider a new problem, termed the interactivity-constrained server provisioning problem, whose goal is to minimize the number of distributed servers needed to achieve a prespecified level of interactivity. We identify and formulate two variants of this new problem and show that they are both NP-hard via reductions to the set covering problem. We then propose several computationally efficient approximation algorithms for solving the problem. The main algorithms exploit dependencies among distributed servers to make provisioning decisions. We conduct extensive experiments to evaluate the performance of the proposed algorithms. Specifically, we use both static Internet latency data available from prior measurements and topology generators, as well as the most recent, dynamic latency data collected via our own large-scale deployment of a DVE performance monitoring system over PlanetLab. The results show that the newly proposed algorithms that take into account interserver dependencies significantly outperform the well-established set covering algorithm for both problem variants.

In this paper, we present a model for estimating the performance of a team of agents, based on the capabilities of the agents and importance of these capabilities for the task. Performance of a team is assumed to be the sum of contributions of individual agents and contributions of subgroups built in the team. We introduce a set of notations, which is required for discussing the suggested models. We also propose a model to estimate the benefit of an agent from interaction with other agents in a subgroup. Based on this benefit model and different (common) strategies, the agents devise plans in which they formulate to what extent they are willing to cooperate with other agents. A negotiation algorithm that resolves the conflicts between the desires of the agents is presented. The effect of this algorithm and different strategies are tested on a set of generated data. The test results show that the performance of a team when the agents choose a cooperation strategy that follows the principle of least effort (Zipf's law) is higher than teams with other cooperation strategies.

The importance of domain knowledge in the design of effective evolutionary algorithms (EAs) is widely acknowledged in the meta-heuristics community. In the last few decades, a plethora of EAs has been manually designed by domain experts for solving domain-specific problems. Specialization has been achieved mainly by embedding available domain knowledge into the algorithms. Although programming libraries have been made available to construct EAs, a unifying framework for designing specialized EAs across different problem domains and branches of evolutionary computing does not exist yet. In this paper, we address this issue by introducing an evolutionary computing modeling language (ECML) which is based on the unified modeling language (UML). ECML incorporates basic UML elements and introduces new extensions that are specially needed for the evolutionary computation domain. Subsequently, the concept of meta evolutionary algorithms (MEAs) is introduced as a family of EAs that is capable of interpreting ECML. MEAs are solvers that are not restricted to a particular problem domain or branch of evolutionary computing through the use of ECML. By separating problem-specific domain knowledge from the EA implementation, we show that a unified framework for evolutionary computation can be attained. We demonstrate our approach by applying it to a number of examples.

Base Object Model (BOM) is a component-based standard designed to support reusability and Composability. Reusability helps in reducing time and cost of the development of a simulation process. Composing predefined components such as BOMs is a well known approach to achieve reusability. However, there is a need for a matching mechanism to identify whether a set of components are composable or not. Although BOM provides good model representation, it lacks capability to express semantic and behavioral matching.In this paper we propose an approach for matching behavior of BOM components by matching their statemachines. Our proposed process includes a static and a dynamic matching phase. In the static matching phase, we apply a set of rules to validate the structure of statemachines. In the dynamic matching phase, we execute the statemachines together at an abstract level on our proposed execution framework. We have developed this framework using the State Chart Extensible Markup Language (SCXML), which is a W3C compliant standard. If the execution terminates successfully (i.e. reaches specified final states) we conclude that there is a positive match and the behavior of these BOMs is composable. We describe the matching process and the implementation of our runtime environment in detail and present a case study as proof of concept.

In distributed virtual environments, e.g., online gaming, collaborative designs and distributed military simulations, interactivity is one of the most important requirements. The users may notice serious degradations in quality of service when interacting in the virtual world if the response from the system is much slower than what they have experienced in real life. In this paper, we consider the problem of placing distributed servers in the network to reduce client-server communication latencies, which is termed the server placement problem. We proposed two new network-aware placement algorithms which take into account users' locations in the network and connectivity at the autonomous system level to determine good sites for servers. Extensive experiments with realistic network models showed that these new algorithms significantly outperform existing approaches that require full knowledge of network connectivity at the router-level topologies.

This study looks at the extent to which controlling locomotion within a virtual shop detracts from what is remembered of the shop and its contents, within immersive projection technology (TPT). The effect is analyzed by a memory test with a sample of 40 VE visitors. The test users' visited in two VE shops; in one shop an operator navigated and in another one the test users navigated by themselves using wand. Controlling one's own locomotion was found detrimental to recalling the content and impression of the VE.

Creating simulation models via composition of predefined and reusable components is an efficient way of reducing costs and time associated with the simulation model development process. However, in order to successfully compose models one has to solve the issues of syntactic and semantic composability of components. HLA is the most widely used architecture for distributed simulations today. It provides a simulation environment and standards for specifying simulation parts and interactions between simulation parts. But it provides little support for semantic composability. The Base Object Model (BOM) standard is an attempt to ease reusability and composition of simulation models. However, BOMs do not contain sufficient information for defining concepts and terms in order to avoid ambiguity, and provide no methods for matching conceptual models (state machines). In this paper, we present our approach for enhancement of the semantic contents of BOMs and propose a three-layer model for syntactic and semantic matching of BOMs. The semantic enhancement includes ontologies for entities, event and interactions in each component. We also present an OWL-S description for each component including the statemachines. The three-layer model consists of syntactic matching, static semantic matching and dynamic semantic matching utilising a set of rules for reasoning about the compositions. We also describe our discovery and matching rules, which have been implemented in the Jess inference engine. In order to test our approach we have defined some simulation scenarios and implemented BOMs as building blocks for development of those scenarios, one of which has been presented in this paper. Our result shows that the three-layer model is promising and can improve and simplify composition of BOM-based components.

Development of simulation models is a multi-disciplinary and time/resource consuming process. An approach to reduce the associated costs and improving the usability of the models is to compose simulation models through reuse of predefined and already existing, validated simulation components. Using this method the simulation model is built in a component-based fashion. The Base Object Model, BOM, is a new standard for defining reusable and composable simulation components. The introduction of BOMs into the simulation community opens up the possibility of component based simulation development approach that is faster and more efficient than today's simulation creation process. In this paper we describe a process that has been developed at the Swedish Defence Research Agency (FOI) with the aim to speed up and improve the development of simulation models. This process utilizes the BOM concept coupled with ontologies in simulation development, and employs SRML (Simulation Reference Markup Language) as a means to define a component based simulation on a high-level. We present our experimental results and findings based on our implementation of the proposed process. Our experience indicates that including ontological information in BOMs will further increase their usability

CSCW (computer supported cooperative work) has been around for many years. However, despite growing use of CSCW, general infrastructures that support it are few, and seldom provide data consistency management. A question at issue is how to easily provide different consistency policies for CSCW applications. In a modeling and simulation project at the Swedish Defense Research Agency we have evaluated technologies for developing a CSCW infrastructure. Frequently used distributed simulation architecture, the HLA, appeared as a candidate for beneficially providing CSCW services. Hence we have investigated the use of HLA for the purpose, with successful result. This paper presents some of the outcome, and the experiences from adapting an application to CSCW utilizing HLA. It presents performance experiments for evaluation of three consistency policies for CSCW using HLA, conclusions, future work and some recommendations.

Structured peer-to-peer systems can be organized hierarchically as two-level overlay networks. The top-level overlay consists of groups of nodes, where each group is identified by a group identifier. In each group, one or more nodes are designated as supernodes and act as gateways to the nodes at the second level. A collision occurs during join operations, when two or more groups with the same group identifier are created at the top-level overlay. Collisions increase the lookup path length and the stabilization overhead, and reduce the scalability of hierarchical peer-to-peer systems. We propose a new scheme to detect and resolve collisions, and we study the impact of the collision problem on the performance of peer-to-peer systems. Our simulation results show the effectiveness of our scheme in reducing collisions and maintaining the size of the top-level overlay close to the ideal size.

Parallel and distributed simulation techniques have been investigated in a number of studies as a way to decrease long execution times of personal communication system (PCS) simulations. However, most studies have omitted important issues in radio propagation in the simulations. Including these radio propagation issues makes it significantly more difficult to partition a PCS model efficiently. In this paper we consider parallel simulation of PCS models using time warp and focus on the partitioning issue. We compare base station based partitioning with channel based partitioning for an F/TDMA system. Analytical and experimental results on a shared memory multiprocessor indicate that for realistic parameters the partitioning per channel will significantly outperform the partitioning per base station.

Abstract The paper presents a Conservative Time Window (CTW) algorithm for parallel simulation of discrete event systems. The physical system to be simulated is partitioned intondisjoint sub‐systems, each of which is represented by an object The CTW algorithm identifies a time window for each object, such that events occurring in each window are independent of events in other windows and thus they can be processed concurrently. The CTW algorithm was implemented on a shared memory multiprocessor, a Sequent Symmetry S81 with 16 processors. We measured performance of the CTW algorithm on two types of network topologies: feed‐forward networks and networks with feedback loops. We used three metrics to measure performance: speed‐up, average number of independent windows detected by the algorithm, and average number of events occurring in each window. We also investigated the impact of various event scheduling policies on performance. The results obtained show that the CTW algorithm produces good performance in many cases.

Trace-driven simulation is the most widely used method to evaluate caches. This demands large amounts of storage and computer time. Several techniques have been proposed to reduce the simulation time of sequential trace-driven simulation. However, little has been done to exploit parallelism. In this paper, we present some efficient parallel simulation techniques that exploit set-partitioning as the main source of parallelism. We show that a straightforward implementation does not give much speedup as one might expect. We develop more efficient parallel simulation techniques by introducing more knowl edge into the cache simulator. The techniques presented here can be efficiently used on multiprocessor worksta tions.