{"title":"CoAP-mediated hybrid simulation and visualisation environment for specknets","authors":"D. A. Crisan, I. Radoi, D. Arvind","doi":"10.1145/2486092.2486128","DOIUrl":"https://doi.org/10.1145/2486092.2486128","url":null,"abstract":"This paper describes an integrated hybrid simulation environment in which physical electronic devices interact in real-time with a discrete-event simulator and a 3D visualisation engine, where the communication between the real devices and the virtual world is mediated by CoAP. The resulting simulation framework is a powerful tool for designers of Internet of Things (IoT) applications to assess design decisions ahead of deployment, based on realistic data from sensors and typical movement of people within built spaces. A motivating example is used to illustrate the capabilities of hybrid simulations based on a multi-residence housing facility intended for elderly people, each wearing an on-body speck with one or more sensors, to monitor their condition such as breathing, heart-rate, and activity, and which transmits this information via a mesh network of base-stations to a central hub. The results demonstrate that design decisions can be made on the choice of routing protocols based on real-time transmission of data from people, which captures their typical movement in a built environment and based on actual data transmitted by on-body devices.","PeriodicalId":115341,"journal":{"name":"Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133462235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling communication software execution for accurate simulation of distributed systems","authors":"Stein Kristiansen, T. Plagemann, V. Goebel","doi":"10.1145/2486092.2486102","DOIUrl":"https://doi.org/10.1145/2486092.2486102","url":null,"abstract":"Network simulation is commonly used to evaluate the performance of distributed systems, but these approaches do not account for the performance impact that protocol execution on nodes has on performance, which may be significant. We propose a methodology to capture execution models from communication software running on real devices where the execution models can be integrated with discrete event network simulators to improve their accuracy. We provide a set of rules to instrument the software to obtain the events of importance, and present techniques to create executable models based on the obtained traces. To make the models scalable, processing stages are reduced to statistical distributions. When the resulting models are executed in a device model with a scheduler simulator, we are able to model the dynamics of multithreading and parallel execution. Our initial results from a proof-of-concept extension to Ns-3 show that our models are able to accurately model protocol execution on the Google Nexus One with low simulation overhead.","PeriodicalId":115341,"journal":{"name":"Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134521184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jingjing Wang, Ketan Bahulkar, D. Ponomarev, N. Abu-Ghazaleh
{"title":"Can PDES scale in environments with heterogeneous delays?","authors":"Jingjing Wang, Ketan Bahulkar, D. Ponomarev, N. Abu-Ghazaleh","doi":"10.1145/2486092.2486098","DOIUrl":"https://doi.org/10.1145/2486092.2486098","url":null,"abstract":"The performance and scalability of Parallel Discrete Event Simulation (PDES) is often limited by communication latencies and overheads. The emergence of multi-core processors and their expected evolution into many-cores offers the promise of low latency communication and tight memory integration between cores; these properties should significantly improve the performance of PDES in such environments. However, on clusters of multi-cores (CMs), the latency and processing overheads incurred when communicating between different machines (nodes) far outweigh those between cores on the same chip, especially when commodity networking fabrics and communication software are used. It is unclear if there is any benefit to the low latency among cores on the same node given that communication links across nodes are significantly worse. In this study, we examine the performance of a multi-threaded implementation of PDES on CMs. We demonstrate that the inter-node communication costs impose a substantial bottleneck on PDES and demonstrate that without optimizations addressing these long latencies, multi-threaded PDES does not significantly outperform the multiprocess version despite direct communication through shared memory on the individual nodes. We then propose three optimizations: message consolidation and routing, infrequent polling and latency-sensitive model partitioning. We show that with these optimizations in place, threaded implementation of PDES significantly outperforms process-based implementation even on CMs.","PeriodicalId":115341,"journal":{"name":"Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114379279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jun Wang, Zhenjiang Dong, S. Yalamanchili, G. Riley
{"title":"Optimizing parallel simulation of multicore systems using domain-specific knowledge","authors":"Jun Wang, Zhenjiang Dong, S. Yalamanchili, G. Riley","doi":"10.1145/2486092.2486108","DOIUrl":"https://doi.org/10.1145/2486092.2486108","url":null,"abstract":"This paper presents two optimization techniques for the basic Null-message algorithm in the context of parallel simulation of multicore computer architectures. Unlike the general, application-independent optimization methods, these are application-specific optimizations that make use of system properties of the simulation application. We demonstrate in two aspects that the domain-specific knowledge offers great potential for optimization. First, it allows us to send Null-messages much less eagerly, thus greatly reducing the amount of Null-messages. Second, the internal state of the simulation application allows us to make conservative forecast of future outgoing events. This leads to the creation of an enhanced synchronization algorithm called Forecast Null-message algorithm, which, by combining the forecast from both sides of a link, can greatly improve the simulation look-ahead. Compared with the basic Null-message algorithm, our optimizations greatly reduce the number of Null-messages and increase simulation performance significantly as a result. On a subset of the PARSEC benchmarks, a maximum speedup of about 6 is achieved with 17 LPs.","PeriodicalId":115341,"journal":{"name":"Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126190698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Edward Clarkson, J. Hurt, Jason Zutty, Christopher L Skeels, Brian Parise, Gregory Rohling
{"title":"Supporting robust system analysis with the test matrix tool framework","authors":"Edward Clarkson, J. Hurt, Jason Zutty, Christopher L Skeels, Brian Parise, Gregory Rohling","doi":"10.1145/2486092.2486096","DOIUrl":"https://doi.org/10.1145/2486092.2486096","url":null,"abstract":"We present the Test Matrix Tool (TMT) framework, a simulation-agnostic framework providing end-to-end support for robust analysis of complex systems. The need to execute a large number of simulations is common to many problem environments, even those already reduced by Design of Experiments or similar methodologies. TMT addresses key end-user needs in easing the specification, execution and analysis of simulation workloads in ways that are consistent between specific applications of the framework. The TMT design contributes modular specifications for key data communicated between and within the specification, execution and analysis components. Our TMT implementation is an instantiation of those formats freely available for general use. TMT's data analysis component provides a variety of features data filtering, comparison, transformation and visualization for analytic tasks on any TMT-embedded model. We provide a brief case study as an example of its use in a real-world application.","PeriodicalId":115341,"journal":{"name":"Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130177533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Post-mortem analysis of emergent behavior in complex simulation models","authors":"Claudia Szabo, Y. M. Teo","doi":"10.1145/2486092.2486123","DOIUrl":"https://doi.org/10.1145/2486092.2486123","url":null,"abstract":"Analyzing and validating emergent behavior in component-based models is increasingly challenging as models grow in size and complexity. Despite increasing research interest, there is a lack of automated, formalized approaches to identify emergent behavior and its causes. As part of our integrated framework for understanding emergent behavior, we propose a post-mortem emergence analysis approach that identifies the causes of emergent behavior in terms of properties of the composed model and properties of the individual model components, and their interactions. In this paper, we detail the use of reconstructability analysis for post-mortem analysis of known emergent behavior. The two-step process first identifies model components that are most likely to have caused emergent behavior, and then analyzes their interaction. Our case study using small and large examples demonstrates the applicability of our approach.","PeriodicalId":115341,"journal":{"name":"Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126702633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Formalization of emergence in multi-agent systems","authors":"Y. M. Teo, Ba Linh Luong, Claudia Szabo","doi":"10.1145/2486092.2486122","DOIUrl":"https://doi.org/10.1145/2486092.2486122","url":null,"abstract":"Emergence is a distinguishing feature in systems, especially when complexity grows with the number of components, interactions, and connectivity. There is immense interest in emergence, and a plethora of definitions from philosophy to sciences. Despite this, there is a lack of consensus on the definition of emergence and this hinders the development of a formal approach to understand and predict emergent behavior in multi-agent systems. This paper proposes a grammar-based set-theoretic approach to formalize and verify the existence and extent of emergence without prior knowledge or definition of emergent properties. Our approach is based on weak (basic) emergence that is both generated and autonomous from the underlying agents. In contrast with current work, our approach has two main advantages. By focusing only on system interactions of interest and feasible combinations of individual agent behavior, state-space explosion is reduced. In formalizing emergence, our extended grammar is designed to model agents of diverse types, mobile agents, and open systems. Theoretical and experimental studies using the boids model demonstrate the complexity of our formal approach.","PeriodicalId":115341,"journal":{"name":"Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124315510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Heterogeneous parallel simulation","authors":"Jason Liu","doi":"10.1145/3260229","DOIUrl":"https://doi.org/10.1145/3260229","url":null,"abstract":"","PeriodicalId":115341,"journal":{"name":"Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132583865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yunsick Sung, A. Helal, Jaewoong Lee, Kyungeun Cho
{"title":"Bayesian-based scenario generation method for human activities","authors":"Yunsick Sung, A. Helal, Jaewoong Lee, Kyungeun Cho","doi":"10.1145/2486092.2486111","DOIUrl":"https://doi.org/10.1145/2486092.2486111","url":null,"abstract":"Emerging smart space applications are increasingly relying on capabilities for recognizing human activities. Activity recognition research is however challenged and slowed by the lack of data necessary for testing and validation. Collecting data through live-in trials in real world deployments is often very expensive and complicated. Legitimate limitations on the use of human subjects also renders a much smaller dataset than desired to be collected. To address this challenge, we propose a scenario generation approach in which a small set of scenarios is used to generate new relevant and realistic scenarios, and hence increase the base of testing data needed for activity recognition validation. Unlike existing methods for generating scenarios, which usually focus on scenario structure and complexity, we propose a Bayesian-based approach that learns the stochastic characteristics of a small number of collected datasets to generate additional scenarios of similar characteristics. Our approach is prolific and can generate enormous datasets with high degree of realism at affordable cost. The proposed approach is validated using a Viterbi-based algorithm and a real dataset case study. The validation experiment confirms that the generated dataset has highly similar stochastic characteristics as that of the real dataset.","PeriodicalId":115341,"journal":{"name":"Proceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134530058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}