Design and Implementation of a Distributed Middleware for Parallel Execution of Legacy Enterprise Applications

A typical enterprise uses a local area network of computers to perform its business. During the off-working hours, the computational capacities of these networked computers are underused or unused. In order to utilize this computational capacity an application has to be recoded to exploit concurrency inherent in a computation which is clearly not possible for legacy applications without any source code. This thesis presents the design an implementation of a distributed middleware which can automatically execute a legacy application on multiple networked computers by parallelizing it. This middleware runs multiple copies of the binary executable code in parallel on different hosts in the network. It wraps up the binary executable code of the legacy application in order to capture the kernel level data access system calls and perform them distributively over multiple computers in a safe and conflict free manner. The middleware also incorporates a dynamic scheduling technique to execute the target application in minimum time by scavenging the available CPU cycles of the hosts in the network. This dynamic scheduling also supports the CPU availability of the hosts to change over time and properly reschedule the replicas performing the computation to minimize the execution time. A prototype implementation of this middleware has been developed as a proof of concept of the design. This implementation has been evaluated with a few typical case studies and the test results confirm that the middleware works as expected

Incremental Consistency Guarantees for Replicated Objects

Programming with replicated objects is difficult. Developers must face the fundamental trade-off between consistency and performance head on, while struggling with the complexity of distributed storage stacks. We introduce Correctables, a novel abstraction that hides most of this complexity, allowing developers to focus on the task of balancing consistency and performance. To aid developers with this task, Correctables provide incremental consistency guarantees, which capture successive refinements on the result of an ongoing operation on a replicated object. In short, applications receive both a preliminary---fast, possibly inconsistent---result, as well as a final---consistent---result that arrives later. We show how to leverage incremental consistency guarantees by speculating on preliminary values, trading throughput and bandwidth for improved latency. We experiment with two popular storage systems (Cassandra and ZooKeeper) and three applications: a Twissandra-based microblogging service, an ad serving system, and a ticket selling system. Our evaluation on the Amazon EC2 platform with YCSB workloads A, B, and C shows that we can reduce the latency of strongly consistent operations by up to 40% (from 100ms to 60ms) at little cost (10% bandwidth increase, 6% throughput drop) in the ad system. Even if the preliminary result is frequently inconsistent (25% of accesses), incremental consistency incurs a bandwidth overhead of only 27%.Comment: 16 total pages, 12 figures. OSDI'16 (to appear

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor