Fault-tolerant dynamic parallel schedules

Dynamic Parallel Schedules (DPS) is a high-level framework for developing parallel applications on distributed memory computers such as clusters of PCs. DPS applications are defined by using directed acyclic flow graphs composed of user-defined operations. These operations derive from basic concepts provided by the framework: split, merge, leaf and stream operations. Whereas a simple parallel application can be expressed with a split-leaf-merge sequence of operations, flow graphs of arbitrary complexity can be created. DPS provides run-time support for dynamically mapping flow graph operations onto the nodes of a cluster. The flow graph based application description used in DPS allows the framework to offer many additional features, most of these transparently to the application developer. In order to maximize performance, DPS applications benefit from automatic overlapping of computations and communications and from implicit pipelining. The framework provides simple primitives for flow control and load balancing. Applications can integrate flow graph parts provided by other applications as parallel components. Since the mapping of DPS applications to processing nodes can be dynamically changed at runtime, DPS provides a basis for developing malleable applications. The DPS framework provides a complete fault tolerance mechanism based on the dynamic mapping capabilities, ensuring continued execution of parallel applications even in the presence of multiple node failures. DPS is provided as an open-source, cross-platform C++ library allowing DPS applications and services to run on heterogeneous clusters

A Programming System for Distributed Real-Time Applications

A distributed programming system designed to support the construction and execution of a real-time distributed program is presented. The system is to facilitate the construction of a distributed program from sequential programs written in different programming languages and to simplify the loading and execution of the distributed program. The system is based on a distributed configuration language. The language is used to write the configuration of a distributed program, which includes resource requirements, process declarations, port connections, real-time constraints, process assignment constraints, and process control statements

Effects of distribution planning systems on the cost of delivery in unique make-to-order manufacturing

This thesis investigates the effects of simulation through the use of a distribution planning system (DPS) on distribution costs in the setting of unique make-to-order manufacturers (UMTO). In doing so, the German kitchen furniture industry (GKFI) serves as an example and supplier of primary data. On the basis of a detailed market analysis this thesis will demonstrate that this industry, which mostly works with its own vehicles for transport, is in urgent need of innovative logistics strategies. Within the scope of an investigation into the current practical and theoretical use of DPS, it will become apparent that most known DPS are based on the application of given or set delivery tour constraints. Those constraints are often not questioned in practice and in theory nor even attempted to be omitted, but are accepted in day-to-day operation. This paper applies a different approach. In the context of this research, a practically applied DPS is used supportively for the removal of time window constraints (TWC) in UMTO delivery. The same DPS is used in ceteris paribus condition for the re-routing of deliveries and hereby supports the findings regarding the costliness of TWC. From this experiment emerges an overall cost saving of 50.9% and a 43.5% reduction of kilometres travelled. The applied experimental research methodology and the significance of the resulting savings deliver the opportunity to analyse the removal of delivery time window restrictions as one of many constraints in distribution logistics. The economic results of this thesis may become the basis of discussion for further research based on the applied methodology. From a practical point of view, the contributions to new knowledge are the cost savings versus the change of demand for the setting of TWC between the receiver of goods and the UMTO supplier. On the side of theoretical knowledge, this thesis contributes to filling the gap on the production – distribution problem from a UMTO perspective. Further contributions to knowledge are delivered through the experimental methodology with the application of a DPS for research in logistics simulation

SDN-enabled Resource Provisioning Framework for Geo-Distributed Streaming Analytics

Geographically distributed (geo-distributed) datacenters for stream data processing typically comprise multiple edges and core datacenters connected through Wide-Area Network (WAN) with a master node responsible for allocating tasks to worker nodes. Since WAN links significantly impact the performance of distributed task execution, the existing task assignment approach is unsuitable for distributed stream data processing with low latency and high throughput demand. In this paper, we propose SAFA, a resource provisioning framework using the Software-Defined Networking (SDN) concept with an SDN controller responsible for monitoring the WAN, selecting an appropriate subset of worker nodes, and assigning tasks to the designated worker nodes. We implemented the data plane of the framework in P4 and the control plane components in Python. We tested the performance of the proposed system on Apache Spark, Apache Storm, and Apache Flink using the Yahoo! streaming benchmark on a set of custom topologies. The results of the experiments validate that the proposed approach is viable for distributed stream processing and confirm that it can improve at least 1.64× the processing time of incoming events of the current stream processing systems.</p