Location based placement of whole distributed systems

Spence, David R.; Crowcroft, Jon; Hand, Steven; Harris, Tim

doi:10.1145/1095921.1095939

“…When the crashed primary node restarts, it receives the new data accumulated during its down time from the new primary node. When the failed node cannot reboot fast enough, a human operator or a system monitoring service selects a new backup node based on its available NVMM size, its networking topology, and other criteria [6,53]. The new node receives a complete copy of the memory region and begins processing updates from the new mirror node.…”

Section: Recoverymentioning

confidence: 99%

Mojim

Zhang

¹

,

Yang

²

,

Memaripour

³

et al. 2015

Proceedings of the Twentieth International Conference on Architectural Support for Programming Languages and Operating Systems

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Next-generation non-volatile memories (NVMs) promise DRAM-like performance, persistence, and high density. They can attach directly to processors to form non-volatile main memory (NVMM) and offer the opportunity to build very low-latency storage systems. These high-performance storage systems would be especially useful in large-scale data center environments where reliability and availability are critical. However, providing reliability and availability to NVMM is challenging, since the latency of data replication can overwhelm the low latency that NVMM should provide.We propose Mojim, a system that provides the reliability and availability that large-scale storage systems require, while preserving the performance of NVMM. Mojim achieves these goals by using a two-tier architecture in which the primary tier contains a mirrored pair of nodes and the secondary tier contains one or more secondary backup nodes with weakly consistent copies of data. Mojim uses highlyoptimized replication protocols, software, and networking stacks to minimize replication costs and expose as much of NVMM's performance as possible. We evaluate Mojim using raw DRAM as a proxy for NVMM and using an industrial NVMM emulation system. We find that Mojim provides replicated NVMM with similar or even better performance than un-replicated NVMM (reducing latency by 27% to 63% and delivering between 0.4 to 2.7× the throughput). We demonstrate that replacing MongoDB's built-in replication system with Mojim improves MongoDB's performance by 3.4 to 4×.

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“…When the crashed primary node restarts, it receives the new data accumulated during its down time from the new primary node. When the failed node cannot reboot fast enough, a human operator or a system monitoring service selects a new backup node based on its available NVMM size, its networking topology, and other criteria [6,53]. The new node receives a complete copy of the memory region and begins processing updates from the new mirror node.…”

Section: Recoverymentioning

confidence: 99%

Mojim

Zhang

¹

,

Yang

²

,

Memaripour

³

et al. 2015

SIGPLAN Not.

6

0

View full text Add to dashboard Cite

Next-generation non-volatile memories (NVMs) promise DRAM-like performance, persistence, and high density. They can attach directly to processors to form non-volatile main memory (NVMM) and offer the opportunity to build very low-latency storage systems. These high-performance storage systems would be especially useful in large-scale data center environments where reliability and availability are critical. However, providing reliability and availability to NVMM is challenging, since the latency of data replication can overwhelm the low latency that NVMM should provide.We propose Mojim, a system that provides the reliability and availability that large-scale storage systems require, while preserving the performance of NVMM. Mojim achieves these goals by using a two-tier architecture in which the primary tier contains a mirrored pair of nodes and the secondary tier contains one or more secondary backup nodes with weakly consistent copies of data. Mojim uses highlyoptimized replication protocols, software, and networking stacks to minimize replication costs and expose as much of NVMM's performance as possible. We evaluate Mojim using raw DRAM as a proxy for NVMM and using an industrial NVMM emulation system. We find that Mojim provides replicated NVMM with similar or even better performance than un-replicated NVMM (reducing latency by 27% to 63% and delivering between 0.4 to 2.7× the throughput). We demonstrate that replacing MongoDB's built-in replication system with Mojim improves MongoDB's performance by 3.4 to 4×.

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“…However, this approach is based on assumption that system experiences low churn rate [32]. Gossiping and onehop routing approach has been used for maintaining the routing overlay in the work [33].…”

Section: Dhtmentioning

confidence: 99%

Peer-to-Peer Cloud Provisioning: Service Discovery and Load-Balancing

Ranjan

¹

,

Zhao²,

Wu³

et al. 2010

Computer Communications and Networks

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Clouds have evolved as the next generation platform that facilitates creation of widearea on-demand renting of computing or storage services for hosting application services that experience highly variable workloads and requires high availability and performance. Inter-connecting Cloud computing system components (servers, VMs, application services) through peer-to-peer routing and information dissemination structure is essential to avoid the problems of provisioning efficiency bottleneck and single point of failure that are predominantly associated with traditional centralized or hierarchical approaches. These limitations can be overcome by connecting Cloud system components using a structured peer-to-peer network model (such as Distributed Hash Tables (DHTs)). DHTs offer deterministic information/query routing and discovery with close to logarithmic bounds with regards to network message complexity. By maintaining a small routing state of O (log n) per VM, a DHT structure guarantees deterministic look ups in a completely decentralized and distributed manner. This chapter presents: (i) a layered peer-to-peer Cloud provisioning architecture; (ii) a summary of the current state-of-the-art in Cloud provisioning with particular emphasis on service discovery and load-balancing; (iii) a classification of the existing peer-to-peer network management model with focus on extending the DHTs for indexing and managing complex provisioning information; and (iv) the design and implementation of novel, extensible software fabric (Cloud peer) that combines public/private clouds, overlay networking and structured peer-to-peer indexing techniques for supporting scalable and self-managing service discovery and load-balancing in Cloud computing environments. Finally, an experimental evaluation is presented that demonstrates the feasibility of building next generation Cloud provisioning systems based on peer-to-peer network management and information dissemination models. The experimental test-bed has been deployed on a public cloud computing platform, Amazon EC2, which demonstrates the effectiveness of the proposed peer-to-peer Cloud provisioning software fabric.

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Location based placement of whole distributed systems

Cited by 16 publications

References 34 publications

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Peer-to-Peer Cloud Provisioning: Service Discovery and Load-Balancing

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