We present the Distributed Batch Controller (DBC), a system built to support batch processing of large scientiic datasets. The DBC implements a federation of autonomous workstation pools, which may be widely-distributed. Individual batch jobs are executed using idle workstations in these pools. Input data are staged to the pool before processing begins. We describe the architecture and implemen...

We present the Distributed Batch Controller DBC a system built to support batch processing of large scienti c datasets The DBC implements a federation of autonomous workstation pools which may be widely distributed Individual batch jobs are executed using idle workstations in these pools Input data are staged to the pool before processing begins We describe the architecture and implementation o...

In this work, a novel sequence-based mixed-integer linear programming formulation for the simultaneous batching and scheduling in multi-product multi-stage batch plants is developed. The selection of batches, the allocation of batches to processing units and the sequencing of batches in each unit constitute the discrete decisions of our model. Batch processing times and sizes are variables. Bat...

We analyze batch-scheduling problems that arise in connection with certain industrial applications. The models concern processing on a single max-batch machine with the additional feature that the tasks of the same batch have to be compatible. Compatibility is a symmetric binary relation—the compatible pairs are described with an undirected “compatibility graph”, which is often an interval grap...

Summingbird is an open-source domain-specific language implemented in Scala and designed to integrate online and batch MapReduce computations in a single framework. Summingbird programs are written using dataflow abstractions such as sources, sinks, and stores, and can run on different execution platforms: Hadoop for batch processing (via Scalding/Cascading) and Storm for online processing. Dif...

We consider a batch scheduling problem in which the processing time of a batch of jobs equals the maximum of the processing times of all jobs in the batch. This is the case, for example, for burn-in operations in semiconductor manufacturing, and other testing operations. Processing times are assumed to be random, and we consider minimizing the makespan and the flowtime. The problem is much more...

We present the Distributed Batch Controller (DBC}, a system built to support batch processing of large scienti$c datasets. The DBC implements a federation of autonomous workstation pools, which may be widely distributed. Individual batch ,jobs are executed using idle workstations in these pools. Input data are staged to the pool before processing begins. We describe the architecture and impleme...

We study a class of scheduling problems with batch setups for the online-list and online-time paradigms. Jobs are to be scheduled in batches for processing. All jobs in a batch start and complete together, and a constant setup is prior to each batch. The objective is to minimize the total completion time of all jobs. We primarily consider the special cases of these problems with identical proce...

Scheduling is a key factor for manufacturing productivity. Effective scheduling can improve on-time delivery, reduce work-in-process inventory, cut lead time, and improve machine utilization. Motivated by the extensive use of batch machines in manufacturing industries, the scheduling of job shops with batch machines is studied in this paper. Unlike machines that can process one part at a time (...

In this paper, we consider the scheduling problem of minimizing total weighted completion time on uniform machines with unbounded batch. Each of the machine Ml (l = 1, ⋅ ⋅ ⋅ ,m) has a speed sl and can process up to B(≥ n) jobs simultaneously as a batch. The processing time of a batch denoted by P(B) is given by the processing time of the longest job in it, and the running time of the batch on m...