New multi-leader consensus protocols leverage the Generalized Consensus specification to enable low latency, even load balancing, and high parallelism. However, these protocols introduce inherent costs with significant performance impact: they need quorums bigger than the minimum required to solve consensus and need to track dependency relations among proposals. In this paper we present M2PAXOS, an implementation of Generalized Consensus that provides fast decisions (i.e., delivery of a command in two communication delays) by leveraging quorums composed of a majority of nodes and by exploiting workload locality. M2PAXOS does not establish command dependencies based on conflicts, instead mapping nodes to accessed objects and enforcing that commands accessing the same objects be ordered by the same node. Our experimental evaluation confirms the effectiveness of M2PAXOS, gaining up to 7X over state-of-the-art Consensus and Generalized Consensus algorithms under partitioned data accesses and up to 5.5× using the TPC-C workload.

Distributed Transactional Memory (DTM) is a recent but promising model for programming distributed systems. It aims to present programmers with a simple to use distributed concurrency control abstraction (transactions), while maintaining performance and scalability similar to distributed fine-grained locks. Any complications usually associated with such locks (e.g., distributed deadlocks) are avoided. In this article, we analyze the use of open nesting in the DTM setting. We extend two DTM algorithms, Transactional Forwarding Algorithm (TFA) and SCORe with support for open nested transactions and we implement them into two frameworks for running distributed transactions, such as Hyflow and Infinispan. We discuss the mechanisms and performance implications of such nesting, and identify the cases where using open nesting is warranted and the relevant parameters for such a decision. To the best of our knowledge, our work also contributes the first ever implementations of DTM systems with support for open-nested transactions.

Modern transactional processing systems need to be fast and scalable, but this means many such systems settled for weak consistency models. It is however possible to achieve all of strong consistency, high scalability and high performance, by using fine-grained partitions and light-weight concurrency control that avoids superfluous synchronization and other overheads such as lock management. Independent transactions are one such mechanism, that rely on good partitions and appropriately defined transactions. On the downside, it is not usually straightforward to determine optimal partitioning schemes, especially when dealing with non-trivial amounts of data. Our work attempts to solve this problem by automating the partitioning process, choosing the correct transactional primitive, and routing transactions appropriately.

Single leader-based Consensus protocols are known to stop scaling once the leader reaches its saturation point. On the other hand, establishing Consensus of commands by taking into account only their dependencies (as specified by Generalized Consensus) is appealing because of the potentially higher parallelism and lower latency. However, current solutions have well-known pitfalls due to the higher quorum size, which is required to exploit low-latency fast decisions, and the need for tracking dependency relations. In this paper we briefly introduce M2PAXOS, a new implementation of Generalized Consensus that provides a fast decision of commands by leveraging a classic quorum size, which matches just the majority of nodes deployed. M2PAXOS does not establish command dependencies based on conflicts, rather it associates accessed objects with nodes, so that the delivery decision of commands operating on the same objects is made by a common node. The evaluation study of M2PAXOS confirms its effectiveness by showing an improvement up to 7× over state-of-the-art (Generalized) Consensus protocols.

Modern transactional processing systems need to be fast and scalable, but this means many such systems settled for weak consistency models. It is however possible to achieve all of strong consistency, high scalability and high performance, by using fine-grained partitions and light-weight concurrency control that avoids superfluous synchronization and other overheads such as lock management. Independent transactions are one such mechanism, that rely on good partitions and appropriately defined transactions. On the downside, it is not usually straightforward to determine optimal partitioning schemes, especially when dealing with non-trivial amounts of data. Our work attempts to solve this problem by automating the partitioning process, choosing the correct transactional primitive, and routing transactions appropriately.

We present the first ever distributed transactional memory (DTM) framework for distributed concurrency control in C++, called HyflowCPP. HyflowCPP provides distributed atomic sections, and plug gable support for policies for concurrency control, directory lookup, contention management, and networking. While there exists other DTM frameworks, they mostly target VM-based languages (e.g., Java, Scala). Additionally, HyflowCPP provides uniquely distinguishing TM features including strong atomicity, closed and open nesting, and check pointing. Our experimental studies revealed that HyflowCPP achieves up to 6x performance improvement over state-of-the-art DTM frameworks.

Distributed Transactional Memory (DTM) is a recent but promising model for programming distributed systems. It aims to present programmers with a simple to use distributed concurrency control abstraction (transactions), while maintaining performance and scalability similar to distributed fine-grained locks. Any complications usually associated with such locks (e.g., distributed deadlocks) are avoided. Building upon the previously proposed Transactional Forwarding Algorithm (TFA), we add support for open-nested transactions. We discuss the mechanisms and performance implications of such nesting, and identify the cases where using open nesting is warranted and the relevant parameters for such a decision. To the best of our knowledge, our work contributes the first ever implementation of a DTM system with support for open-nested transactions.