Fault-tolerant distributed transactions for partitioned OLTP databases

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 103-112).This thesis presents Dtxn, a fault-tolerant distributed transaction system designed specifically for building online transaction processing (OLTP) databases. Databases have traditionally been designed as general purpose data processing tools. By being designed only for OLTP workloads, Dtxn can be more efficient. It is designed to support very large databases by partitioning data across a cluster of commodity servers in a data center. Combining multiple servers together allows systems built with Dtxn to be cost effective, highly available, scalable, and fault-tolerant. Dtxn provides three novel features. First, it provides reusable infrastructure for building a distributed OLTP database out of single machine databases. This allows developers to take a specialized backend storage engine and use it across multiple machines, without needing to re-implement the distributed transaction infrastructure. We used Dtxn to build four different applications: a simple key/value store, a specialized TPC-C implementation, a main-memory OLTP database, and a traditional disk-based OLTP database. Second, Dtxn provides a novel concurrency control mechanism called speculative concurrency control, designed for main memory OLTP workloads that are primarily composed of transactions with a single round of communication between the application and database. Speculative concurrency control executes one transaction at a time, with no concurrency control overhead. In cases where there may be stalls due to network communication, it speculates future transactions. Our results show that this provides significantly better throughput than traditional two-phase locking, outperforming it by a factor of two on the TPC-C benchmark. Finally, Dtxn supports live migration, allowing part of the data on one server to be moved to another server while processing transactions. Our experiments show that our approach has nearly no visible impact on throughput or latency when moving data under moderate to high loads. It has significantly less impact than the best commercially available systems when the database is overloaded. The period of time where the throughput is reduced is less than half as long as failing over to another replica or using virtual machine migration.by Evan Philip Charles Jones.Ph.D

Systems Support for Trusted Execution Environments

Cloud computing has become a default choice for data processing by both large corporations and individuals due to its economy of scale and ease of system management. However, the question of trust and trustoworthy computing inside the Cloud environments has been long neglected in practice and further exacerbated by the proliferation of AI and its use for processing of sensitive user data. Attempts to implement the mechanisms for trustworthy computing in the cloud have previously remained theoretical due to lack of hardware primitives in the commodity CPUs, while a combination of Secure Boot, TPMs, and virtualization has seen only limited adoption. The situation has changed in 2016, when Intel introduced the Software Guard Extensions (SGX) and its enclaves to the x86 ISA CPUs: for the first time, it became possible to build trustworthy applications relying on a commonly available technology. However, Intel SGX posed challenges to the practitioners who discovered the limitations of this technology, from the limited support of legacy applications and integration of SGX enclaves into the existing system, to the performance bottlenecks on communication, startup, and memory utilization. In this thesis, our goal is enable trustworthy computing in the cloud by relying on the imperfect SGX promitives. To this end, we develop and evaluate solutions to issues stemming from limited systems support of Intel SGX: we investigate the mechanisms for runtime support of POSIX applications with SCONE, an efficient SGX runtime library developed with performance limitations of SGX in mind. We further develop this topic with FFQ, which is a concurrent queue for SCONE's asynchronous system call interface. ShieldBox is our study of interplay of kernel bypass and trusted execution technologies for NFV, which also tackles the problem of low-latency clocks inside enclave. The two last systems, Clemmys and T-Lease are built on a more recent SGXv2 ISA extension. In Clemmys, SGXv2 allows us to significantly reduce the startup time of SGX-enabled functions inside a Function-as-a-Service platform. Finally, in T-Lease we solve the problem of trusted time by introducing a trusted lease primitive for distributed systems. We perform evaluation of all of these systems and prove that they can be practically utilized in existing systems with minimal overhead, and can be combined with both legacy systems and other SGX-based solutions. In the course of the thesis, we enable trusted computing for individual applications, high-performance network functions, and distributed computing framework, making a <vision of trusted cloud computing a reality

High-performance state-machine replication

Replication, a common approach to protecting applications against failures, refers to maintaining several copies of a service on independent machines (replicas). Unlike a stand-alone service, a replicated service remains available to its clients despite the failure of some of its copies. Consistency among replicas is an immediate concern raised by replication. In effect, an important factor for providing the illusion of an uninterrupted service to clients is to preserve consistency among the multiple copies. State-machine replication is a popular replication technique that ensures consistency by ordering client requests and making all the replicas execute them deterministically and sequentially. The overhead of ordering the requests, and the sequentiality of request execution, the two essential requirements in realizing state-machine replication, are also the two major obstacles that prevent the performance of state-machine replication from scaling. In this thesis we concentrate on the performance of state-machine replication and enhance it by overcoming the two aforementioned bottlenecks, the overhead of ordering and the overhead of sequentially executing commands. To realize a truly scalable system, one must iteratively examine and analyze all the layers and components of a system and avoid or eliminate potential performance obstructions and congestion points. In this dissertation, we iterate between optimizing the ordering of requests and the strategies of replicas at request execution, in order to stretch the performance boundaries of state-machine replication. To eliminate the negative implications of the ordering layer on performance, we devise and implement several novel and highly efficient ordering protocols. Our proposals are based on practical observations we make after closely assessing and identifying the shortcomings of existing approaches. Communication is one of the most important components of any distributed system and thus selecting efficient communication patterns is a must in designing scalable systems. We base our protocols on the most suitable communication patterns and extend their design with additional features that altogether realize our protocol's high efficiency. The outcome of this phase is the design and implementation of the Ring Paxos family of protocols. According to our evaluations these protocols are highly scalable and efficient. We then assess the performance ramifications of sequential execution of requests on the replicas of state-machine replication. We use some known techniques such as state-partitioning and speculative execution, and thoroughly examine their advantages when combined with our ordering protocols. We then exploit the features of multicore hardware and propose our final solution as a parallelized form of state-machine replication, built on top of Ring Paxos protocols, that is capable of accomplishing significantly high performance. Given the popularity of state-machine replication in designing fault-tolerant systems, we hope this thesis provides useful and practical guidelines for the enhancement of the existing and the design of future fault-tolerant systems that share similar performance goals