SearcharxivSearch

arXiv · 1805.02105

Service Discovery for Hyperledger Fabric

Abstract

Hyperledger Fabric (HLF) is a modular and extensible permissioned blockchain platform released to open-source and hosted by the Linux Foundation. The platform's design exhibits principles required by enterprise grade business applications like supply-chains, financial transactions, asset management, food safety, and many more. For that end HLF introduces several innovations, two of which are smart contracts in general purpose languages (\emph{chaincode} in HLF), and flexible endorsement policies, which govern whether a transaction is considered valid. Typical blockchain applications are comprised of two tiers: the first tier focuses on the modelling of the data schema and embedding of business rules into the blockchain by means of smart contracts (\emph{chaincode}) and endorsment policies; and the second tier uses the SDK (Software Development Kit) provided by HLF to implement client side application logic. However there is a gap between the two tiers that hinders the rapid adoption of changes in the chaincode and endorsement policies within the client SDK. Currently, the chaincode location and endorsement policies are statically configured into the client SDK. This limits the reliability and availability of the client in the event of changes in the platform, and makes the platform more difficult to use. In this work we address and bridge the gap by describing the design and implementation of \emph{Service Discovery}. \emph{Service Discovery} provides APIs which allow dynamic discovery of the configuration required for the client SDK to interact with the platform, alleviating the client from the burden of maintaining it. This enables the client to rapidly adapt to changes in the platform, thus significantly improving the reliability of the application layer. It also makes the HLF platform more consumable, simplifying the job of creating blockchain applications.

Explore related subjects

Keep this discovery

BibTeXRIS

Yacov Manevich, Artem Barger, Yoav Tock. 2018-05-05. Service Discovery for Hyperledger Fabric. https://arxiv.org/abs/1805.02105

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Online Treasure Hunt in Vertex-Permuted Dynamic Rings

We study the problem of treasure hunt by a group of $k \geq 1$ agents in vertex-permuted dynamic rings (VP). In this model, the $n$ vertices remain on a ring but are permuted at each time step. We first show that treasure hunt is impossible for any $k \leq n-3$ agents, if there are no restrictions on the sequence of permutations used in the dynamic ring. We then study the $VP(\delta)$ setting, in which for every pair $i, j$ of vertices, the edge $(i, j)$ is guaranteed to appear within $\delta$ steps. We show that the class $VP(\delta)$ is feasible only for $\delta \geq \left\lceil \frac{n-1}{2}\right\rceil$. For the one-agent case, we show a tight bound of $\Theta(\delta n)$ on the worst-case search time as well as competitive ratio of any online algorithm for treasure hunt, provided $\delta \geq 2n$. We then give an optimal algorithm for $k$ agents, thereby showing that $k$ agents can obtain a speedup of $k$ on the worst-case search time. Finally, in the R-VP setting, in which in every step, the vertices are arranged as a ring according to a random permutation, we show that treasure hunt takes expected $\Theta(n)$ steps against an oblivious adversary and $\Theta(n \log n)$ steps against an adaptive adversary.

cs.DC

The Computing Channel: How Modulation Programs the Airwaves

Distributed computing and distributed artificial intelligence require frequent exchanges of intermediate results, although many applications need only an aggregate rather than messages from individual devices. Conventional systems recover each message before computing the aggregate, whereas over-the-air computation (OAC) exploits simultaneous transmission to obtain it directly. However, dominant OAC implementations rely on analog signaling, creating a mismatch with finite-precision data and digital communication procedures. This article presents digital function-oriented communication, in which finite-alphabet symbol representations and receiver decisions are jointly designed so that multiple-access superposition encodes the desired function without recovering individual inputs. We introduce its computational-constellation principle, main design approaches, extensions, and implementation challenges. Federated edge learning illustrates how the framework can reduce user-dependent data-bearing resources while operating directly on quantized model updates.

cs.DC

Can AI Remediate Backend Failures Safely? GuardedAct with Blast-Radius-Aware Sandboxing

Large Language Models (LLMs) have shown promising capabilities in generating remediation actions for microservice failures. However, directly executing AI-generated repair actions in production risks cascading collateral damage. We propose GuardedAct, a sandbox-first remediation framework that interposes a blast-radius-aware verification layer between the LLM action generator and the production environment. GuardedAct operates in four phases: (1) ingesting a diagnosis report together with the live system topology and recent telemetry, (2) prompting an LLM to produce a ranked list of candidate remediation actions, (3) simulating each action in a lightweight digital-twin sandbox that estimates the blast radius and assigns a risk label, and (4) enforcing a rollback-confidence gate that auto-executes only low-risk actions while escalating high-risk ones for human review. We evaluate GuardedAct on five fault scenarios injected into the DeathStarBench social-network application. Experimental results show that GuardedAct achieves an overall recovery rate of 87.4% while reducing collateral damage by 79.7% relative to direct LLM execution (from 25.6% to 5.2%), at the cost of a modest sandbox-induced increase in mean time to recovery (approximately 8 s). Ablation studies confirm that each component contributes meaningfully to the safety-speed trade-off.

cs.DC