Implementing Distributed Data Management System In Dynamic Objects By Using Improved Sort Based Algorithm

In the High Level Architecture (HLA) paradigm, the Runtime Infrastructure (RTI) provides a set of services, such as data distribution and management (DDM) among federates. Each federate may inform the RTI about its intention to publish some data or it may subscri be to receive a subset of the published data. DDM services are used to reduce the transmission and receiving of irrelevant data and aimed at reducing the communication over the network. These services rely on the computation of the intersection between “up date” and “subscription” regions. Currently, there are several main DDM filtering algorithms. Our proposed system describes data management and filtering mechanism on tank simulation in battlefield area. This system intends to detect the movement of the ta nk ob ject s, search overlap between the tank object and every regional regiment (extent). When overlapping information is getting from one of the simulation object (OverlapDetector), another simulation object (Coordinator) connects the relevant extent that conta ining the tank object. That extent continued to send the tank information to other regional regiments according to the predefined list. In this paper, we present the design and implementation of a simulation platform used to implement one of the fil tering algorithms, the improved sort based algorithm, and report the overhead of reducing network traffic and ensuring that the forwarding data receive federates only who need the data

Layer Partition-based Matching Algorithm of DDM

High Level Architecture (HLA) is architecture for reuse and interoperation of simulations. In HLA paradigm, the Runtime Infrastructure (RTI) provides a set of services. Data Distribution Management (DDM) service reduces message traffic over the network. DDM aims to control and limit the data exchanged between federates during federation. Each federate may inform the RTI about its intention to publish some data or it may subscribe to receive a subset of the published data. DDM services are used to reduce the transmission and receiving of irrelevant data and aimed at reducing the communication over the network. These services rely on the computation of the intersection between “update” and “subscription” regions. When calculating the intersection between update regions and subscription regions, the higher computation overhead can occur. Currently, there are several main DDM filtering algorithms. This paper proposes the layer partition-based matching algorithm for DDM in the HLA-based large-scale distributed simulations. The new algorithm chooses the dynamic pivot based on regions distribution in the routing space. The binary partition-based algorithm is fundamentally based on a divide and conquers approach. This algorithm always chooses the midpoint as the pivot point of routing space. This approach promises low computational overhead, since it does not require unnecessary comparisons within regions in different partitions. The proposed algorithm firstly calculates the regions distribution. Then, the partitioning among regions performs based on the result of choosing pivot based on region detection and defines the matching area that entirely covers all regions which need to match with regions at pivot point. The proposed algorithm provides the more definite matching area between update region and subscription region during matching process. This algorithm guarantees low computational overheads for matching process based on the overlapping degree between the regions and reduce the irrelevant message among federates

Distributed simulation of building systems for legacy software reuse

The use of integrated building performance simulation can substantially help in improving a building design with regards to comfort levels and fuel consumption, while reducing emission of greenhouse gasses. However, the traditional tools that are closed for inter-communication, limit the modeler to use of components only available within that particular package. This paper gives an overview of distributed simulation approach that can alleviate above limitation. Each program can represent only a part of a building system that is able to model, exchanging the necessary information during the execution and bridging the gaps between the tools. Several important issues closely connected with its implementation, such as synchronization, are pointed out, and the sensitivity of a model on different coupling strategies is studied. The paper concludes with highlighting the gained flexibility in modeling and simulation of building performance that arises from the distributed approach

Resource-constraint And Scalable Data Distribution Management For High Level Architecture

In this dissertation, we present an efficient algorithm, called P-Pruning algorithm, for data distribution management problem in High Level Architecture. High Level Architecture (HLA) presents a framework for modeling and simulation within the Department of Defense (DoD) and forms the basis of IEEE 1516 standard. The goal of this architecture is to interoperate multiple simulations and facilitate the reuse of simulation components. Data Distribution Management (DDM) is one of the six components in HLA that is responsible for limiting and controlling the data exchanged in a simulation and reducing the processing requirements of federates. DDM is also an important problem in the parallel and distributed computing domain, especially in large-scale distributed modeling and simulation applications, where control on data exchange among the simulated entities is required. We present a performance-evaluation simulation study of the P-Pruning algorithm against three techniques: region-matching, fixed-grid, and dynamic-grid DDM algorithms. The P-Pruning algorithm is faster than region-matching, fixed-grid, and dynamic-grid DDM algorithms as it avoid the quadratic computation step involved in other algorithms. The simulation results show that the P-Pruning DDM algorithm uses memory at run-time more efficiently and requires less number of multicast groups as compared to the three algorithms. To increase the scalability of P-Pruning algorithm, we develop a resource-efficient enhancement for the P-Pruning algorithm. We also present a performance evaluation study of this resource-efficient algorithm in a memory-constraint environment. The Memory-Constraint P-Pruning algorithm deploys I/O efficient data-structures for optimized memory access at run-time. The simulation results show that the Memory-Constraint P-Pruning DDM algorithm is faster than the P-Pruning algorithm and utilizes memory at run-time more efficiently. It is suitable for high performance distributed simulation applications as it improves the scalability of the P-Pruning algorithm by several order in terms of number of federates. We analyze the computation complexity of the P-Pruning algorithm using average-case analysis. We have also extended the P-Pruning algorithm to three-dimensional routing space. In addition, we present the P-Pruning algorithm for dynamic conditions where the distribution of federated is changing at run-time. The dynamic P-Pruning algorithm investigates the changes among federates regions and rebuilds all the affected multicast groups. We have also integrated the P-Pruning algorithm with FDK, an implementation of the HLA architecture. The integration involves the design and implementation of the communicator module for mapping federate interest regions. We provide a modular overview of P-Pruning algorithm components and describe the functional flow for creating multicast groups during simulation. We investigate the deficiencies in DDM implementation under FDK and suggest an approach to overcome them using P-Pruning algorithm. We have enhanced FDK from its existing HLA 1.3 specification by using IEEE 1516 standard for DDM implementation. We provide the system setup instructions and communication routines for running the integrated on a network of machines. We also describe implementation details involved in integration of P-Pruning algorithm with FDK and provide results of our experiences

Synchronized Data Distribution Management in Distributed Simulations

A considerable amount of effort in the DIS community has been devoted to developing efficient, scaleable, mechanisms for distributing state updates and interaction information in distributed simulations. By contrast, this question has not received as much attention for distributed simulations using logical time (e.g., analytic simulations). It is observed that data distribution management (DDM) mechanisms used for real-time training simulations such as DIS are insufficient to meet the requirements of logical time-based simulations, and may result in errors such as messages not being delivered to federates that have subscribed for them, even if the network provides reliable delivery. An approach to achieving properly synchronized data distribution is described, and is applied to the data distribution management mechanisms based on routing spaces that has been proposed for the HLA. 1

Efficient Synchronized Data Distribution Management in Distributed Simulations

Data distribution management (DDM) is a mechanism to interconnect data producers and data consumers in a distributed application. Data producers provide useful data to consumers in the form of messages. For each message produced, DDM determines the set of data consumers interested in receiving the message and delivers it to those consumers. We are particularly interested in DDM techniques for parallel and distributed discrete event simulations. Thus far, researchers have treated synchronization of events (i.e. time management) and DDM independent of each other. This research focuses on how to realize time managed DDM mechanisms. The main reason for time-managed DDM is to ensure that changes in the routing of messages from producers to consumers occur in a correct sequence. Also time managed DDM avoids non-determinism in the federation execution, which may result in non-repeatable executions. An optimistic approach to time managed DDM is proposed where one allows DDM events to be processed out of time stamp order, but a detection and recovery procedure is used to recover from such errors. These mechanisms are tailored to the semantics of the DDM operations to ensure an efficient realization. A correctness proof is presented to verify the algorithm correctly synchronizes DDM events. We have developed a fully distributed implementation of the algorithm within the framework of the Georgia Tech Federated Simulation Development Kit (FDK) software. A performance evaluation of the synchronized DDM mechanism has been completed in a loosely coupled distributed system consisting of a network of workstations connected over a local area network (LAN). We compare time-managed versus unsynchronized DDM for two applications that exercise different mobility patterns: one based on a military simulation and a second utilizing a synthetic workload. The experiments and analysis illustrate that synchronized DDM performance depends on several factors: the simulations model (e.g. lookahead), applications mobility patterns and the network hardware (e.g. size of network buffers). Under certain mobility patterns, time-managed DDM is as efficient as unsynchronized DDM. There are also mobility patterns where time-managed DDM overheads become significant, and we show how they can be reduced.Ph.D.Committee Chair: Fujimoto Richard; Committee Member: Pande Santosh; Committee Member: Pritchett Amy; Committee Member: Ramachandran Kishore; Committee Member: Riley Georg

Approved by: Efficient Synchronized Data Distribution Management in Distributed Simulations

To my parents, Ilona and Branislav, and brother Igo