The Experts below are selected from a list of 132 Experts worldwide ranked by ideXlab platform
Marc Shapiro - One of the best experts on this subject based on the ideXlab platform.
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SRDS Workshops - SwiftCloud: Fault-Tolerant Geo-Replication Integrated all the Way to the Client Machine
2014 IEEE 33rd International Symposium on Reliable Distributed Systems Workshops, 2014Co-Authors: Nuno Preguiça, Marek Zawirski, Annette Bieniusa, Valter Balegas, Sérgio Duarte, Carlos Baquero, Marc ShapiroAbstract:Client-side logic and storage are increasingly used in web and mobile applications to improve response time and availability. Current approaches tend to be ad-hoc and poorly integrated with the server-side logic. We present a principled approach to integrate client-and server-side storage. We support both mergeable and strongly consistent transactions that target either client or server replicas and provide access to causally-consistent snapshots efficiently. In the presence of infrastructure faults, a client-assisted failover solution allows client execution to resume immediately and seamlessly access consistent snapshots without waiting. We implement this approach in SwiftCloud, the first Transactional System to bring geo-replication all the way to the client machine. Example applications show that our programming model is useful across a range of application areas. Our experimental evaluation shows that SwiftCloud provides better fault tolerance and at the same time can improve both latency and throughput by up to an order of magnitude, compared to classical geo-replication techniques.
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SwiftCloud: Fault-Tolerant Geo-Replication Integrated all the Way to the Client Machine
arXiv: Distributed Parallel and Cluster Computing, 2013Co-Authors: Marek Zawirski, Marc Shapiro, Annette Bieniusa, Valter Balegas, Sérgio Duarte, Carlos Baquero, Nuno PreguiçaAbstract:Client-side logic and storage are increasingly used in web and mobile applications to improve response time and availability. Current approaches tend to be ad-hoc and poorly integrated with the server-side logic. We present a principled approach to integrate client- and server-side storage. We support mergeable and strongly consistent transactions that target either client or server replicas and provide access to causally-consistent snapshots efficiently. In the presence of infrastructure faults, a client-assisted failover solution allows client execution to resume immediately and seamlessly access consistent snapshots without waiting. We implement this approach in SwiftCloud, the first Transactional System to bring geo-replication all the way to the client machine. Example applications show that our programming model is useful across a range of application areas. Our experimental evaluation shows that SwiftCloud provides better fault tolerance and at the same time can improve both latency and throughput by up to an order of magnitude, compared to classical geo-replication techniques.
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Non-Monotonic Snapshot Isolation
2013Co-Authors: Masoud Saeida Ardekani, Pierre Sutra, Nuno Preguiça, Marc ShapiroAbstract:Many distributed applications require transactions. However, Transactional protocols that require strong synchronization are costly in large scale environments. Two properties help with scalability of a Transactional System: genuine partial replication (GPR), which leverages the intrinsic parallelism of a workload, and snapshot isolation (SI), which decreases the need for synchronization. We show that, under standard assumptions (data store accesses are not known in advance, and transactions may access arbitrary objects in the data store), it is impossible to have both SI and GPR. To circumvent this impossibility, we propose a weaker consistency criterion, called Non-monotonic Snapshot Isolation (NMSI). NMSI retains the most important properties of SI, i.e., read-only transactions always commit, and two write-conflicting updates do not both commit. We present a GPR protocol that ensures NMSI, and has lower message cost (i.e., it contacts fewer replicas and/or commits faster) than previous approaches.
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On the scalability of snapshot isolation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013Co-Authors: Masoud Saeida Ardekani, Pierre Sutra, Marc Shapiro, Nuno PreguiçaAbstract:Many distributed applications require transactions. However, Transactional protocols that require strong synchronization are costly in large scale environments. Two properties help with scalability of a Transactional System: genuine partial replication (GPR), which leverages the intrinsic parallelism of a workload, and snapshot isolation (SI), which decreases the need for synchronization. We show that under standard assumptions (data store accesses are not known in advance, and transactions may access arbitrary objects in the data store), it is impossible to have both SI and GPR. Our impossibility result is based on a novel decomposition of SI which proves that, like serializability, SI is expressible on plain histories.
Nuno Preguiça - One of the best experts on this subject based on the ideXlab platform.
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SRDS Workshops - SwiftCloud: Fault-Tolerant Geo-Replication Integrated all the Way to the Client Machine
2014 IEEE 33rd International Symposium on Reliable Distributed Systems Workshops, 2014Co-Authors: Nuno Preguiça, Marek Zawirski, Annette Bieniusa, Valter Balegas, Sérgio Duarte, Carlos Baquero, Marc ShapiroAbstract:Client-side logic and storage are increasingly used in web and mobile applications to improve response time and availability. Current approaches tend to be ad-hoc and poorly integrated with the server-side logic. We present a principled approach to integrate client-and server-side storage. We support both mergeable and strongly consistent transactions that target either client or server replicas and provide access to causally-consistent snapshots efficiently. In the presence of infrastructure faults, a client-assisted failover solution allows client execution to resume immediately and seamlessly access consistent snapshots without waiting. We implement this approach in SwiftCloud, the first Transactional System to bring geo-replication all the way to the client machine. Example applications show that our programming model is useful across a range of application areas. Our experimental evaluation shows that SwiftCloud provides better fault tolerance and at the same time can improve both latency and throughput by up to an order of magnitude, compared to classical geo-replication techniques.
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SwiftCloud: Fault-Tolerant Geo-Replication Integrated all the Way to the Client Machine
arXiv: Distributed Parallel and Cluster Computing, 2013Co-Authors: Marek Zawirski, Marc Shapiro, Annette Bieniusa, Valter Balegas, Sérgio Duarte, Carlos Baquero, Nuno PreguiçaAbstract:Client-side logic and storage are increasingly used in web and mobile applications to improve response time and availability. Current approaches tend to be ad-hoc and poorly integrated with the server-side logic. We present a principled approach to integrate client- and server-side storage. We support mergeable and strongly consistent transactions that target either client or server replicas and provide access to causally-consistent snapshots efficiently. In the presence of infrastructure faults, a client-assisted failover solution allows client execution to resume immediately and seamlessly access consistent snapshots without waiting. We implement this approach in SwiftCloud, the first Transactional System to bring geo-replication all the way to the client machine. Example applications show that our programming model is useful across a range of application areas. Our experimental evaluation shows that SwiftCloud provides better fault tolerance and at the same time can improve both latency and throughput by up to an order of magnitude, compared to classical geo-replication techniques.
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Non-Monotonic Snapshot Isolation
2013Co-Authors: Masoud Saeida Ardekani, Pierre Sutra, Nuno Preguiça, Marc ShapiroAbstract:Many distributed applications require transactions. However, Transactional protocols that require strong synchronization are costly in large scale environments. Two properties help with scalability of a Transactional System: genuine partial replication (GPR), which leverages the intrinsic parallelism of a workload, and snapshot isolation (SI), which decreases the need for synchronization. We show that, under standard assumptions (data store accesses are not known in advance, and transactions may access arbitrary objects in the data store), it is impossible to have both SI and GPR. To circumvent this impossibility, we propose a weaker consistency criterion, called Non-monotonic Snapshot Isolation (NMSI). NMSI retains the most important properties of SI, i.e., read-only transactions always commit, and two write-conflicting updates do not both commit. We present a GPR protocol that ensures NMSI, and has lower message cost (i.e., it contacts fewer replicas and/or commits faster) than previous approaches.
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On the scalability of snapshot isolation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013Co-Authors: Masoud Saeida Ardekani, Pierre Sutra, Marc Shapiro, Nuno PreguiçaAbstract:Many distributed applications require transactions. However, Transactional protocols that require strong synchronization are costly in large scale environments. Two properties help with scalability of a Transactional System: genuine partial replication (GPR), which leverages the intrinsic parallelism of a workload, and snapshot isolation (SI), which decreases the need for synchronization. We show that under standard assumptions (data store accesses are not known in advance, and transactions may access arbitrary objects in the data store), it is impossible to have both SI and GPR. Our impossibility result is based on a novel decomposition of SI which proves that, like serializability, SI is expressible on plain histories.
Youyou Lu - One of the best experts on this subject based on the ideXlab platform.
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scalable rdma rpc on reliable connection with efficient resource sharing
European Conference on Computer Systems, 2019Co-Authors: Youmin Chen, Youyou LuAbstract:RDMA provides extremely low latency and high bandwidth to distributed Systems. Unfortunately, it fails to scale and suffers from performance degradation when transferring data to an increasing number of targets on Reliable Connection (RC). We observe that the above scalability issue has its root in the resource contention in the NIC cache, the CPU cache and the memory of each server. In this paper, we propose ScaleRPC, an efficient RPC primitive using one-sided RDMA verbs on reliable connection to provide scalable performance. To effectively alleviate the resource contention, ScaleRPC introduces 1) connection grouping to organize the network connections into groups, so as to balance the saturation and thrashing of the NIC cache; 2) virtualized mapping to enable a single message pool to be shared by different groups of connections, which reduces CPU cache misses and improve memory utilization. Such scalable connection management provides substantial performance benefits: By deploying ScaleRPC both in a distributed file System and a distributed Transactional System, we observe that it achieves high scalability and respectively improves performance by up to 90% and 160% for metadata accessing and SmallBank transaction processing.
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EuroSys - Scalable RDMA RPC on Reliable Connection with Efficient Resource Sharing
Proceedings of the Fourteenth EuroSys Conference 2019 CD-ROM on ZZZ - EuroSys '19, 2019Co-Authors: Youmin Chen, Youyou LuAbstract:RDMA provides extremely low latency and high bandwidth to distributed Systems. Unfortunately, it fails to scale and suffers from performance degradation when transferring data to an increasing number of targets on Reliable Connection (RC). We observe that the above scalability issue has its root in the resource contention in the NIC cache, the CPU cache and the memory of each server. In this paper, we propose ScaleRPC, an efficient RPC primitive using one-sided RDMA verbs on reliable connection to provide scalable performance. To effectively alleviate the resource contention, ScaleRPC introduces 1) connection grouping to organize the network connections into groups, so as to balance the saturation and thrashing of the NIC cache; 2) virtualized mapping to enable a single message pool to be shared by different groups of connections, which reduces CPU cache misses and improve memory utilization. Such scalable connection management provides substantial performance benefits: By deploying ScaleRPC both in a distributed file System and a distributed Transactional System, we observe that it achieves high scalability and respectively improves performance by up to 90% and 160% for metadata accessing and SmallBank transaction processing.
Marek Zawirski - One of the best experts on this subject based on the ideXlab platform.
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SRDS Workshops - SwiftCloud: Fault-Tolerant Geo-Replication Integrated all the Way to the Client Machine
2014 IEEE 33rd International Symposium on Reliable Distributed Systems Workshops, 2014Co-Authors: Nuno Preguiça, Marek Zawirski, Annette Bieniusa, Valter Balegas, Sérgio Duarte, Carlos Baquero, Marc ShapiroAbstract:Client-side logic and storage are increasingly used in web and mobile applications to improve response time and availability. Current approaches tend to be ad-hoc and poorly integrated with the server-side logic. We present a principled approach to integrate client-and server-side storage. We support both mergeable and strongly consistent transactions that target either client or server replicas and provide access to causally-consistent snapshots efficiently. In the presence of infrastructure faults, a client-assisted failover solution allows client execution to resume immediately and seamlessly access consistent snapshots without waiting. We implement this approach in SwiftCloud, the first Transactional System to bring geo-replication all the way to the client machine. Example applications show that our programming model is useful across a range of application areas. Our experimental evaluation shows that SwiftCloud provides better fault tolerance and at the same time can improve both latency and throughput by up to an order of magnitude, compared to classical geo-replication techniques.
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SwiftCloud: Fault-Tolerant Geo-Replication Integrated all the Way to the Client Machine
arXiv: Distributed Parallel and Cluster Computing, 2013Co-Authors: Marek Zawirski, Marc Shapiro, Annette Bieniusa, Valter Balegas, Sérgio Duarte, Carlos Baquero, Nuno PreguiçaAbstract:Client-side logic and storage are increasingly used in web and mobile applications to improve response time and availability. Current approaches tend to be ad-hoc and poorly integrated with the server-side logic. We present a principled approach to integrate client- and server-side storage. We support mergeable and strongly consistent transactions that target either client or server replicas and provide access to causally-consistent snapshots efficiently. In the presence of infrastructure faults, a client-assisted failover solution allows client execution to resume immediately and seamlessly access consistent snapshots without waiting. We implement this approach in SwiftCloud, the first Transactional System to bring geo-replication all the way to the client machine. Example applications show that our programming model is useful across a range of application areas. Our experimental evaluation shows that SwiftCloud provides better fault tolerance and at the same time can improve both latency and throughput by up to an order of magnitude, compared to classical geo-replication techniques.
Youmin Chen - One of the best experts on this subject based on the ideXlab platform.
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scalable rdma rpc on reliable connection with efficient resource sharing
European Conference on Computer Systems, 2019Co-Authors: Youmin Chen, Youyou LuAbstract:RDMA provides extremely low latency and high bandwidth to distributed Systems. Unfortunately, it fails to scale and suffers from performance degradation when transferring data to an increasing number of targets on Reliable Connection (RC). We observe that the above scalability issue has its root in the resource contention in the NIC cache, the CPU cache and the memory of each server. In this paper, we propose ScaleRPC, an efficient RPC primitive using one-sided RDMA verbs on reliable connection to provide scalable performance. To effectively alleviate the resource contention, ScaleRPC introduces 1) connection grouping to organize the network connections into groups, so as to balance the saturation and thrashing of the NIC cache; 2) virtualized mapping to enable a single message pool to be shared by different groups of connections, which reduces CPU cache misses and improve memory utilization. Such scalable connection management provides substantial performance benefits: By deploying ScaleRPC both in a distributed file System and a distributed Transactional System, we observe that it achieves high scalability and respectively improves performance by up to 90% and 160% for metadata accessing and SmallBank transaction processing.
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EuroSys - Scalable RDMA RPC on Reliable Connection with Efficient Resource Sharing
Proceedings of the Fourteenth EuroSys Conference 2019 CD-ROM on ZZZ - EuroSys '19, 2019Co-Authors: Youmin Chen, Youyou LuAbstract:RDMA provides extremely low latency and high bandwidth to distributed Systems. Unfortunately, it fails to scale and suffers from performance degradation when transferring data to an increasing number of targets on Reliable Connection (RC). We observe that the above scalability issue has its root in the resource contention in the NIC cache, the CPU cache and the memory of each server. In this paper, we propose ScaleRPC, an efficient RPC primitive using one-sided RDMA verbs on reliable connection to provide scalable performance. To effectively alleviate the resource contention, ScaleRPC introduces 1) connection grouping to organize the network connections into groups, so as to balance the saturation and thrashing of the NIC cache; 2) virtualized mapping to enable a single message pool to be shared by different groups of connections, which reduces CPU cache misses and improve memory utilization. Such scalable connection management provides substantial performance benefits: By deploying ScaleRPC both in a distributed file System and a distributed Transactional System, we observe that it achieves high scalability and respectively improves performance by up to 90% and 160% for metadata accessing and SmallBank transaction processing.