In this paper, we propose Dynamic Paxos (DPaxos), a Paxos-based consensus protocol to manage access to partitioned data across globally-distributed datacenters and edge nodes. DPaxos is intended to implement a State Machine Replication component in data management systems for the edge. DPaxos targets the unique opportunities of utilizing edge computing resources to support emerging applications with stringent mobility and real-time requirements such as Augmented and Virtual Reality and vehicular applications. The main objective of DPaxos is to reduce the latency of serving user requests, recovering from failures, and reacting to mobility. DPaxos achieves these objectives by a few proposed changes to the traditional Paxos protocol. Most notably, DPaxos proposes a dynamic allocation of quorums ( i.e. , groups of nodes) that are needed for Paxos Leader Election. Leader Election quorums in DPaxos are smaller than traditional Paxos and expand only in the presence of conflicts.
more »
« less
RT-ZooKeeper: Taming the Recovery Latency of a Coordination Service
Fault-tolerant coordination services have been widely used in distributed applications in cloud environments. Recent years have witnessed the emergence of time-sensitive applications deployed in edge computing environments, which introduces both challenges and opportunities for coordination services. On one hand, coordination services must recover from failures in a timely manner. On the other hand, edge computing employs local networked platforms that can be exploited to achieve timely recovery. In this work, we first identify the limitations of the leader election and recovery protocols underlying Apache ZooKeeper, the prevailing open-source coordination service. To reduce recovery latency from leader failures, we then design RT-Zookeeper with a set of novel features including a fast-convergence election protocol, a quorum channel notification mechanism, and a distributed epoch persistence protocol. We have implemented RT-Zookeeper based on ZooKeeper version 3.5.8. Empirical evaluation shows that RT-ZooKeeper achieves 91% reduction in maximum recovery latency in comparison to ZooKeeper. Furthermore, a case study demonstrates that fast failure recovery in RT-ZooKeeper can benefit a common messaging service like Kafka in terms of message latency.
more »
« less
- Award ID(s):
- 1646579
- NSF-PAR ID:
- 10391327
- Date Published:
- Journal Name:
- ACM Transactions on Embedded Computing Systems
- Volume:
- 20
- Issue:
- 5s
- ISSN:
- 1539-9087
- Page Range / eLocation ID:
- 1 to 22
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)We introduce consistency-aware durability or Cad, a new approach to durability in distributed storage that enables strong consistency while delivering high performance. We demonstrate the efficacy of this approach by designing cross-client monotonic reads, a novel and strong consistency property that provides monotonic reads across failures and sessions in leader-based systems; such a property can be particularly beneficial in geo-distributed and edge-computing scenarios. We build Orca, a modified version of ZooKeeper that implements Cad and cross-client monotonic reads. We experimentally show that Orca provides strong consistency while closely matching the performance of weakly consistent ZooKeeper. Compared to strongly consistent ZooKeeper, Orca provides significantly higher throughput (1.8--3.3×) and notably reduces latency, sometimes by an order of magnitude in geo-distributed settings. We also implement Cad in Redis and show that the performance benefits are similar to that of Cad’s implementation in ZooKeeper.more » « less
-
By processing sensory data in the vicinity of its generation, edge computing reduces latency, improves responsiveness, and saves network bandwidth in data-intensive applications. However, existing edge computing solutions operate under the assumption that the edge infrastructure will comprise a set of pre-deployed, custom-configured computing devices, connected by a reliable local network. Although edge computing has great potential to provision the necessary computational resources in highly dynamic and volatile environments, including disaster recovery scenes and wilderness expeditions, extant distributed system architectures in this domain are not resilient against partial failure, caused by network disconnections. In this paper, we present a novel edge computing system architecture that delivers failure-resistant and efficient applications by dynamically adapting to handle failures; if the edge server becomes unreachable, device clusters start executing the assigned tasks by communicating P2P, until the edge server becomes reachable again. Our experimental results with the reference implementation show high responsiveness and resilience in the face of partial failure. These results indicate that the presented solution can integrate the individual capacities of mobile devices into powerful edge clouds, providing efficient and reliable services for end-users in highly dynamic and volatile environments.more » « less
-
null (Ed.)Many Internet of Things (IoT) applications are time-critical and dynamically changing. However, traditional data processing systems (e.g., stream processing systems, cloud-based IoT data processing systems, wide-area data analytics systems) are not well-suited for these IoT applications. These systems often do not scale well with a large number of concurrently running IoT applications, do not support low-latency processing under limited computing resources, and do not adapt to the level of heterogeneity and dynamicity commonly present at edge environments. This suggests a need for a new edge stream processing system that advances the stream processing paradigm to achieve efficiency and flexibility under the constraints presented by edge computing architectures. We present \textsc{Dart}, a scalable and adaptive edge stream processing engine that enables fast processing of a large number of concurrent running IoT applications’ queries in dynamic edge environments. The novelty of our work is the introduction of a dynamic dataflow abstraction by leveraging distributed hash table (DHT) based peer-to-peer (P2P) overlay networks, which can automatically place, chain, and scale stream operators to reduce query latency, adapt to edge dynamics, and recover from failures. We show analytically and empirically that DART outperforms Storm and EdgeWise on query latency and significantly improves scalability and adaptability when processing a large number of real-world IoT stream applications' queries. DART significantly reduces application deployment setup times, becoming the first streaming engine to support DevOps for IoT applications on edge platforms.more » « less
-
Population protocols are a popular model of distributed computing, in which randomly-interacting agents with little computational power cooperate to jointly perform computational tasks. Inspired by developments in molecular computation, and in particular DNA computing, recent algorithmic work has focused on the complexity of solving simple yet fundamental tasks in the population model, such as leader election (which requires convergence to a single agent in a special “leader” state), and majority (in which agents must converge to a decision as to which of two possible initial states had higher initial count). Known results point towards an inherent trade-off between the time complexity of such algorithms, and the space complexity, i.e. size of the memory available to each agent. In this paper, we explore this trade-off and provide new upper and lower bounds for majority and leader election. First, we prove a unified lower bound, which relates the space available per node with the time complexity achievable by a protocol: for instance, our result implies that any protocol solving either of these tasks for n agents using O(log log n) states must take Ω(n/polylogn) expected time. This is the first result to characterize time complexity for protocols which employ super-constant number of states per node, and proves that fast, poly-logarithmic running times require protocols to have relatively large space costs. On the positive side, we give algorithms showing that fast, poly-logarithmic convergence time can be achieved using O (log2 n) space per node, in the case of both tasks. Overall, our results highlight a time complexity separation between O (log log n) and Θ(log2 n) state space size for both majority and leader election in population protocols, and introduce new techniques, which should be applicable more broadly.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3477034
