Enabling On-Demand Database Computing with MIT SuperCloud Database Management System

The MIT SuperCloud database management system allows for rapid creation and flexible execution of a variety of the latest scientific databases, including Apache Accumulo and SciDB. It is designed to permit these databases to run on a High Performance Computing Cluster (HPCC) platform as seamlessly as any other HPCC job. It ensures the seamless migration of the databases to the resources assigned by the HPCC scheduler and centralized storage of the database files when not running. It also permits snapshotting of databases to allow researchers to experiment and push the limits of the technology without concerns for data or productivity loss if the database becomes unstable.Comment: 6 pages; accepted to IEEE High Performance Extreme Computing (HPEC) conference 2015. arXiv admin note: text overlap with arXiv:1406.492

Using Open Stack for an Open Cloud Exchange(OCX)

We are developing a new public cloud, the Massachusetts Open Cloud (MOC) based on the model of an Open Cloud eXchange (OCX). We discuss in this paper the vision of an OCX and how we intend to realize it using the OpenStack open-source cloud platform in the MOC. A limited form of an OCX can be achieved today by layering new services on top of OpenStack. We have performed an analysis of OpenStack to determine the changes needed in order to fully realize the OCX model. We describe these proposed changes, which although significant and requiring broad community involvement will provide functionality of value to both existing single-provider clouds as well as future multi-provider ones

A Byzantine Fault-Tolerant Ordering Service for the Hyperledger Fabric Blockchain Platform

Hyperledger Fabric (HLF) is a flexible permissioned blockchain platform designed for business applications beyond the basic digital coin addressed by Bitcoin and other existing networks. A key property of HLF is its extensibility, and in particular the support for multiple ordering services for building the blockchain. Nonetheless, the version 1.0 was launched in early 2017 without an implementation of a Byzantine fault-tolerant (BFT) ordering service. To overcome this limitation, we designed, implemented, and evaluated a BFT ordering service for HLF on top of the BFT-SMaRt state machine replication/consensus library, implementing also optimizations for wide-area deployment. Our results show that HLF with our ordering service can achieve up to ten thousand transactions per second and write a transaction irrevocably in the blockchain in half a second, even with peers spread in different continents

Towards effective live cloud migration on public cloud IaaS.

Cloud computing allows users to access shared, online computing resources. However, providers often offer their own proprietary applications, APIs and infrastructures, resulting in a heterogeneous cloud environment. This environment makes it difficult for users to change cloud service providers and to explore capabilities to support the automated migration from one provider to another. Many standards bodies (IEEE, NIST, DMTF and SNIA), industry (middleware) and academia have been pursuing standards and approaches to reduce the impact of vendor lock-in. Cloud providers offer their Infrastructure as a Service (IaaS) based on virtualization to enable multi-tenant and isolated environments for users. Because, each provider has its own proprietary virtual machine (VM) manager, called the hypervisor, VMs are usually tightly coupled to the underlying hardware, thus hindering live migration of VMs to different providers. A number of user-centric approaches have been proposed from both academia and industry to solve this coupling issue. However, these approaches suffer limitations in terms of flexibility (decoupling VMs from underlying hardware), performance (migration downtime) and security (secure live migration). These limitations are identified using our live cloud migration criteria which are rep- resented by flexibility, performance and security. These criteria are not only used to point out the gap in the previous approaches, but are also used to design our live cloud migration approach, LivCloud. This approach aims to live migration of VMs across various cloud IaaS with minimal migration downtime, with no extra cost and without user’s intervention and awareness. This aim has been achieved by addressing different gaps identified in the three criteria: the flexibility gap is improved by considering a better virtualization platform to support a wider hardware range, supporting various operating system and taking into account the migrated VMs’ hardware specifications and layout; the performance gap is enhanced by improving the network connectivity, providing extra resources required by the migrated VMs during the migration and predicting any potential failure to roll back the system to its initial state if required; finally, the security gap is clearly tackled by protecting the migration channel using encryption and authentication. This thesis presents: (i) A clear identification of the key challenges and factors to successfully perform live migration of VMs across different cloud IaaS. This has resulted in a rigorous comparative analysis of the literature on live migration of VMs at the cloud IaaS based on our live cloud migration criteria; (ii) A rigorous analysis to distil the limitations of existing live cloud migration approaches and how to design efficient live cloud migration using up-to-date technologies. This has led to design a novel live cloud migration approach, called LivCloud, that overcomes key limitations in currently available approaches, is designed into two stages, the basic design stage and the enhancement of the basic design stage; (iii) A systematic approach to assess LivCloud on different public cloud IaaS. This has been achieved by using a combination of up-to-date technologies to build LivCloud taking the interoperability challenge into account, implementing and discussing the results of the basic design stage on Amazon IaaS, and implementing both stages of the approach on Packet bare metal cloud. To sum up, the thesis introduces a live cloud migration approach that is systematically designed and evaluated on uncontrolled environments, Amazon and Packet bare metal. In contrast to other approaches, it clearly highlights how to perform and secure the migration between our local network and the mentioned environments

Effective Live Cloud Migration

Cloud providers offer their IaaS services based on virtualization to enable multi-tenant and isolated environments for cloud users. Currently, each provider has its own proprietary virtual machine (VM) manager, called the hypervisor. This has resulted in tight coupling of VMs to their underlying hardware hindering live migration of VMs to different providers. A number of user-centric approaches have been proposed from both academia and industry to solve this issue. However, these approaches suffer limitations in terms of performance (migration downtime), flexibility (decoupling VMs from underlying hardware) and security (secure live migration). This paper proposes LivCloud to overcome such limitations. An open-source cloud orchestrator, a developed transport protocol, overlay network and secured migration channel are crucial parts of LivCloud to achieve effective live cloud migration. Moreover, an initial evaluation of LAN live migration in nested virtualization environment and between different hypervisors has been considered to show the migration impact on network throughput, network latency and CPU utilization. The evaluation has demonstrated the need for optimization within the LAN environment

Synthetically generated text for supervised text analysis

Supervised text models are a valuable tool for political scientists but present several obstacles to their use, including the expense of hand-labeling documents, the difficulty of retrieving rare relevant documents for annotation, and copyright and privacy concerns involved in sharing annotated documents. This article proposes a partial solution to these three issues, in the form of controlled generation of synthetic text with large language models. I provide a conceptual overview of text generation, guidance on when researchers should prefer different techniques for generating synthetic text, a discussion of ethics, and a simple technique for improving the quality of synthetic text. I demonstrate the usefulness of synthetic text with three applications: generating synthetic tweets describing the fighting in Ukraine, synthetic news articles describing specified political events for training an event detection system, and a multilingual corpus of populist manifesto statements for training a sentence-level populism classifier