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Distributed simulation and the grid: Position statements
The Grid provides a new and unrivaled technology for large scale distributed simulation as it enables collaboration and the use of distributed computing resources. This panel paper presents the views of four researchers in the area of Distributed Simulation and the Grid. Together we try to identify the main research issues involved in applying Grid technology to distributed simulation and the key future challenges that need to be solved to achieve this goal. Such challenges include not only technical challenges, but also political ones such as management methodology for the Grid and the development of standards. The benefits of the Grid to end-user simulation modelers also are discussed
LUNES: Agent-based Simulation of P2P Systems (Extended Version)
We present LUNES, an agent-based Large Unstructured NEtwork Simulator, which
allows to simulate complex networks composed of a high number of nodes. LUNES
is modular, since it splits the three phases of network topology creation,
protocol simulation and performance evaluation. This permits to easily
integrate external software tools into the main software architecture. The
simulation of the interaction protocols among network nodes is performed via a
simulation middleware that supports both the sequential and the
parallel/distributed simulation approaches. In the latter case, a specific
mechanism for the communication overhead-reduction is used; this guarantees
high levels of performance and scalability. To demonstrate the efficiency of
LUNES, we test the simulator with gossip protocols executed on top of networks
(representing peer-to-peer overlays), generated with different topologies.
Results demonstrate the effectiveness of the proposed approach.Comment: Proceedings of the International Workshop on Modeling and Simulation
of Peer-to-Peer Architectures and Systems (MOSPAS 2011). As part of the 2011
International Conference on High Performance Computing and Simulation (HPCS
2011
The Simulation Model Partitioning Problem: an Adaptive Solution Based on Self-Clustering (Extended Version)
This paper is about partitioning in parallel and distributed simulation. That
means decomposing the simulation model into a numberof components and to
properly allocate them on the execution units. An adaptive solution based on
self-clustering, that considers both communication reduction and computational
load-balancing, is proposed. The implementation of the proposed mechanism is
tested using a simulation model that is challenging both in terms of structure
and dynamicity. Various configurations of the simulation model and the
execution environment have been considered. The obtained performance results
are analyzed using a reference cost model. The results demonstrate that the
proposed approach is promising and that it can reduce the simulation execution
time in both parallel and distributed architectures
Fault Tolerant Adaptive Parallel and Distributed Simulation through Functional Replication
This paper presents FT-GAIA, a software-based fault-tolerant parallel and
distributed simulation middleware. FT-GAIA has being designed to reliably
handle Parallel And Distributed Simulation (PADS) models, which are needed to
properly simulate and analyze complex systems arising in any kind of scientific
or engineering field. PADS takes advantage of multiple execution units run in
multicore processors, cluster of workstations or HPC systems. However, large
computing systems, such as HPC systems that include hundreds of thousands of
computing nodes, have to handle frequent failures of some components. To cope
with this issue, FT-GAIA transparently replicates simulation entities and
distributes them on multiple execution nodes. This allows the simulation to
tolerate crash-failures of computing nodes. Moreover, FT-GAIA offers some
protection against Byzantine failures, since interaction messages among the
simulated entities are replicated as well, so that the receiving entity can
identify and discard corrupted messages. Results from an analytical model and
from an experimental evaluation show that FT-GAIA provides a high degree of
fault tolerance, at the cost of a moderate increase in the computational load
of the execution units.Comment: arXiv admin note: substantial text overlap with arXiv:1606.0731
A Survey on Load Balancing Algorithms for VM Placement in Cloud Computing
The emergence of cloud computing based on virtualization technologies brings
huge opportunities to host virtual resource at low cost without the need of
owning any infrastructure. Virtualization technologies enable users to acquire,
configure and be charged on pay-per-use basis. However, Cloud data centers
mostly comprise heterogeneous commodity servers hosting multiple virtual
machines (VMs) with potential various specifications and fluctuating resource
usages, which may cause imbalanced resource utilization within servers that may
lead to performance degradation and service level agreements (SLAs) violations.
To achieve efficient scheduling, these challenges should be addressed and
solved by using load balancing strategies, which have been proved to be NP-hard
problem. From multiple perspectives, this work identifies the challenges and
analyzes existing algorithms for allocating VMs to PMs in infrastructure
Clouds, especially focuses on load balancing. A detailed classification
targeting load balancing algorithms for VM placement in cloud data centers is
investigated and the surveyed algorithms are classified according to the
classification. The goal of this paper is to provide a comprehensive and
comparative understanding of existing literature and aid researchers by
providing an insight for potential future enhancements.Comment: 22 Pages, 4 Figures, 4 Tables, in pres
Anonymity and Confidentiality in Secure Distributed Simulation
Research on data confidentiality, integrity and availability is gaining
momentum in the ICT community, due to the intrinsically insecure nature of the
Internet. While many distributed systems and services are now based on secure
communication protocols to avoid eavesdropping and protect confidentiality, the
techniques usually employed in distributed simulations do not consider these
issues at all. This is probably due to the fact that many real-world simulators
rely on monolithic, offline approaches and therefore the issues above do not
apply. However, the complexity of the systems to be simulated, and the rise of
distributed and cloud based simulation, now impose the adoption of secure
simulation architectures. This paper presents a solution to ensure both
anonymity and confidentiality in distributed simulations. A performance
evaluation based on an anonymized distributed simulator is used for quantifying
the performance penalty for being anonymous. The obtained results show that
this is a viable solution.Comment: Proceedings of the IEEE/ACM International Symposium on Distributed
Simulation and Real Time Applications (DS-RT 2018
Inference of Selection Based on Temporal Genetic Differentiation in the Study of Highly Polymorphic Multigene Families
The co-evolutionary arms race between host immune genes and parasite virulence genes is known as Red Queen dynamics. Temporal fluctuations in allele frequencies, or the âturnoverâ of alleles at immune genes, are concordant with predictions of the Red Queen hypothesis. Such observations are often taken as evidence of host-parasite co-evolution. Here, we use computer simulations of the Major Histocompatibility Complex (MHC) of guppies (Poecilia reticulata) to study the turnover rate of alleles (temporal genetic differentiation, GâST). Temporal fluctuations in MHC allele frequencies can be $#order of magnitude larger than changes observed at neutral loci. Although such large fluctuations in the MHC are consistent with Red Queen dynamics, simulations show that other demographic and population genetic processes can account for this observation, these include: (1) overdominant selection, (2) fluctuating population size within a metapopulation, and (3) the number of novel MHC alleles introduced by immigrants when there are multiple duplicated genes. Synergy between these forces combined with migration rate and the effective population size can drive the rapid turnover in MHC alleles. We posit that rapid allelic turnover is an inherent property of highly polymorphic multigene families and that it cannot be taken as evidence of Red Queen dynamics. Furthermore, combining temporal samples in spatial FST outlier analysis may obscure the signal of selection
Distributed Hybrid Simulation of the Internet of Things and Smart Territories
This paper deals with the use of hybrid simulation to build and compose
heterogeneous simulation scenarios that can be proficiently exploited to model
and represent the Internet of Things (IoT). Hybrid simulation is a methodology
that combines multiple modalities of modeling/simulation. Complex scenarios are
decomposed into simpler ones, each one being simulated through a specific
simulation strategy. All these simulation building blocks are then synchronized
and coordinated. This simulation methodology is an ideal one to represent IoT
setups, which are usually very demanding, due to the heterogeneity of possible
scenarios arising from the massive deployment of an enormous amount of sensors
and devices. We present a use case concerned with the distributed simulation of
smart territories, a novel view of decentralized geographical spaces that,
thanks to the use of IoT, builds ICT services to manage resources in a way that
is sustainable and not harmful to the environment. Three different simulation
models are combined together, namely, an adaptive agent-based parallel and
distributed simulator, an OMNeT++ based discrete event simulator and a
script-language simulator based on MATLAB. Results from a performance analysis
confirm the viability of using hybrid simulation to model complex IoT
scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487
Evolutionary genetics of immunological supertypes reveals two faces of the Red Queen
Red Queen host-parasite co-evolution can drive adaptations of immune-genes by positive selection that erodes genetic variation (Red Queen Arms Race), or result in a balanced polymorphism (Red Queen Dynamics) and the long-term preservation of genetic variation (trans-species polymorphism). These two Red Queen processes are opposite extremes of the co-evolutionary spectrum. Here we show that both Red Queen processes can operate simultaneously, analyzing the Major Histocompatibility Complex (MHC) in guppies (Poecilia reticulata and P. obscura), and swamp guppies (Micropoecilia picta). Sub-functionalization of MHC alleles into âsupertypesâ explains how polymorphisms persist during rapid host-parasite co-evolution. Simulations show the maintenance of supertypes as balanced polymorphisms, consistent with Red Queen Dynamics, whereas alleles within supertypes are subject to positive selection in a Red Queen Arms Race. Building on the Divergent Allele Advantage hypothesis, we show that functional aspects of allelic diversity help to elucidate the evolution of polymorphic genes involved in Red Queen co-evolution
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