OClient: On-board client clustering to bridge the interaction gap across multi-fabric adaptive ecosystem

<div><div><div><p>The current blockchain paradigm is being hailed as an unquenchable goal to develop Hyperledger Fabric (HF)-based applications, resulting in a set of substantial enterprises shifting their networking operations, as intriguing consortia to plug the permissioned-nature of blockchain-based computing. While this practice endeavors to fundamentally revolutionize industries, one of the unavoidable problems that emerge is a lack of communication among autonomous HF-based networks, which can hinder the ongoing research landscape and consequently, have detrimental effects on its adoption. Towards this, blockchain interoperability (BI) has been heralded as the underlying concept by which communication can be derived through locating an inter-connection bridge. Considering BI’s significant traction, this paper introduces a new methodological approach to deal with the disparate nature of HF-based networks, termed OClient, for embracing two different interoperabilities (inter-network and inter-chain). This approach strategically tunes the inner working of clients by providing the global information of HF network topology that extends their conventional role as a matching service provider for facilitating opportunistic communication, in contrast to the existing solutions where typically third-parties have been exploited as the intermediaries. The paper streamlines the discussion by putting forth a pragmatic multi-HF (MHF) network scenario to formulate the disconnectivity problem, followed by constructing interaction-path-based graphs and conducting rigorous simulations. More importantly, this paper manifests experimental examples and corresponding results, providing insights across various dimensions of client-level interoperability so as to understand the impact on performance for combinations of inter-network and inter-chain scenarios. Succinctly, the results demonstrate that OClient is close to the performance of autonomous HF networks, which makes it a useful approach. Besides, this paper strives to understand how the adopted failure strategy to maintain ledger consistency contributes to performance and finally, concludes by anticipating significant future research directions towards HF interoperability.</p></div></div></div>

OClient: On-board client clustering to bridge the interaction gap across multi-fabric adaptive ecosystem

<div><div><div><p>The current blockchain paradigm is being hailed as an unquenchable goal to develop Hyperledger Fabric (HF)-based applications, resulting in a set of substantial enterprises shifting their networking operations, as intriguing consortia to plug the permissioned-nature of blockchain-based computing. While this practice endeavors to fundamentally revolutionize industries, one of the unavoidable problems that emerge is a lack of communication among autonomous HF-based networks, which can hinder the ongoing research landscape and consequently, have detrimental effects on its adoption. Towards this, blockchain interoperability (BI) has been heralded as the underlying concept by which communication can be derived through locating an inter-connection bridge. Considering BI’s significant traction, this paper introduces a new methodological approach to deal with the disparate nature of HF-based networks, termed OClient, for embracing two different interoperabilities (inter-network and inter-chain). This approach strategically tunes the inner working of clients by providing the global information of HF network topology that extends their conventional role as a matching service provider for facilitating opportunistic communication, in contrast to the existing solutions where typically third-parties have been exploited as the intermediaries. The paper streamlines the discussion by putting forth a pragmatic multi-HF (MHF) network scenario to formulate the disconnectivity problem, followed by constructing interaction-path-based graphs and conducting rigorous simulations. More importantly, this paper manifests experimental examples and corresponding results, providing insights across various dimensions of client-level interoperability so as to understand the impact on performance for combinations of inter-network and inter-chain scenarios. Succinctly, the results demonstrate that OClient is close to the performance of autonomous HF networks, which makes it a useful approach. Besides, this paper strives to understand how the adopted failure strategy to maintain ledger consistency contributes to performance and finally, concludes by anticipating significant future research directions towards HF interoperability.</p></div></div></div>

An Online Calibration Method Based on n-Tuple and Opportunistic Communication for Mine Mass Portable Gas Sensors

Due to the increasing deployment of the Internet of Things (IoT) in the mining industry, portable gas monitoring devices have been widely used. Sensor calibration of large-scale portable gas monitoring devices is becoming an urgent problem to be solved. An online sensor calibration algorithm based on n-tuple and opportunistic communication is proposed based on the specific characteristics (i.e., ‘single-sensor, multi-position’ and ‘multi-sensor, single-position’) of each portable gas monitoring device employed. In this paper, data collected from portable and fixed sensors were defined as multi-dimensional data points and gas monitoring data pairs, respectively. The cluster-based self-adaptive weighted data fusion algorithm and multi-period single sensor reliability fusion algorithm were proposed and used for overall judging. The overall judgments were broadcast to each wireless access point by network, and the reliability of the calibration information transmission was enhanced by opportunistic communications. The simulation results revealed that efforts required for the calibration of portable sensors were reduced significantly, and their reliability was improved.