23,692 research outputs found
Extending Eventually Consistent Cloud Databases for Enforcing Numeric Invariants
Geo-replicated databases often operate under the principle of eventual
consistency to offer high-availability with low latency on a simple key/value
store abstraction. Recently, some have adopted commutative data types to
provide seamless reconciliation for special purpose data types, such as
counters. Despite this, the inability to enforce numeric invariants across all
replicas still remains a key shortcoming of relying on the limited guarantees
of eventual consistency storage. We present a new replicated data type, called
bounded counter, which adds support for numeric invariants to eventually
consistent geo-replicated databases. We describe how this can be implemented on
top of existing cloud stores without modifying them, using Riak as an example.
Our approach adapts ideas from escrow transactions to devise a solution that is
decentralized, fault-tolerant and fast. Our evaluation shows much lower latency
and better scalability than the traditional approach of using strong
consistency to enforce numeric invariants, thus alleviating the tension between
consistency and availability
Update Consistency for Wait-free Concurrent Objects
In large scale systems such as the Internet, replicating data is an essential
feature in order to provide availability and fault-tolerance. Attiya and Welch
proved that using strong consistency criteria such as atomicity is costly as
each operation may need an execution time linear with the latency of the
communication network. Weaker consistency criteria like causal consistency and
PRAM consistency do not ensure convergence. The different replicas are not
guaranteed to converge towards a unique state. Eventual consistency guarantees
that all replicas eventually converge when the participants stop updating.
However, it fails to fully specify the semantics of the operations on shared
objects and requires additional non-intuitive and error-prone distributed
specification techniques. This paper introduces and formalizes a new
consistency criterion, called update consistency, that requires the state of a
replicated object to be consistent with a linearization of all the updates. In
other words, whereas atomicity imposes a linearization of all of the
operations, this criterion imposes this only on updates. Consequently some read
operations may return out-dated values. Update consistency is stronger than
eventual consistency, so we can replace eventually consistent objects with
update consistent ones in any program. Finally, we prove that update
consistency is universal, in the sense that any object can be implemented under
this criterion in a distributed system where any number of nodes may crash.Comment: appears in International Parallel and Distributed Processing
Symposium, May 2015, Hyderabad, Indi
MDCC: Multi-Data Center Consistency
Replicating data across multiple data centers not only allows moving the data
closer to the user and, thus, reduces latency for applications, but also
increases the availability in the event of a data center failure. Therefore, it
is not surprising that companies like Google, Yahoo, and Netflix already
replicate user data across geographically different regions.
However, replication across data centers is expensive. Inter-data center
network delays are in the hundreds of milliseconds and vary significantly.
Synchronous wide-area replication is therefore considered to be unfeasible with
strong consistency and current solutions either settle for asynchronous
replication which implies the risk of losing data in the event of failures,
restrict consistency to small partitions, or give up consistency entirely. With
MDCC (Multi-Data Center Consistency), we describe the first optimistic commit
protocol, that does not require a master or partitioning, and is strongly
consistent at a cost similar to eventually consistent protocols. MDCC can
commit transactions in a single round-trip across data centers in the normal
operational case. We further propose a new programming model which empowers the
application developer to handle longer and unpredictable latencies caused by
inter-data center communication. Our evaluation using the TPC-W benchmark with
MDCC deployed across 5 geographically diverse data centers shows that MDCC is
able to achieve throughput and latency similar to eventually consistent quorum
protocols and that MDCC is able to sustain a data center outage without a
significant impact on response times while guaranteeing strong consistency
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