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A Decentralized Architecture for Sharing and Querying Semantic Data

Accepted at ESWC 2019. Download submitted version
Authors: Christian Aebeloe, Gabriela Montoya and Katja Hose.
Although the Semantic Web in principle provides access to a vast Web of interlinked data, the full potential currently remains mostly unexploited. One of the main reasons is the fact that the architecture of the current Web of Data relies on a set of servers providing access to the data. These servers represent bottlenecks and single points of failure that result in instability and unavailability of data at certain points in time. In this paper, we therefore propose a decentralized architecture (Piqnic) for sharing and querying semantic data. By combining both client and server functionality at each participating node and introducing replication, Piqnic avoids bottlenecks and keeps datasets available and queryable although the original source might (temporarily) not be available. Our experimental results using a standard benchmark of real datasets show that Piqnic can serve as an architecture for sharing and querying semantic data, even in the presence of node failures.

EXPERIMENTS

We ran our experiments on a server with 4xAMD Opteron 6376, 16 core processors at 2.3GHz, 768KB L1 cache, 16MB L2 cache and 16MB L3 cache each (64 cores in total), and 516GB RAM. We use 200 clients on the same server.

We have the following metrics: We use LargeRDFBench for data and queries for tests. We use groups CD, LS, C, L, and CH.

All queries that completed within the timeout had 100% completeness. Some that timed out were in the process of answering, and had returned some of the answers.

Execution Time (ET) in Seconds for groups CD and LS (log scale)

Execution Time (ET) in Seconds for group C (log scale) - Full has been left out, since it timed out for all cases

Execution Time (ET) in Seconds for groups L and CH (log scale) - Full has been left out, since it timed out for all cases

Number of Messages for groups CD and LS (log scale) - Not shown for C, L and CH, since Bulk was the only approach that could answer most queries

Number of Transferred Bytes for groups CD and LS (log scale) - Not shown for C, L and CH, since Bulk was the only approach that could answer most queries

Completeness in Percentage for groups CD and LS, given no recovery time

Completeness in Percentage for groups CD and LS, given recovery time

Execution Time (ET) in Seconds for groups CD and LS (log scale)

Execution Time (ET) in Seconds for group C (log scale)

Execution Time (ET) in Seconds for groups L and CH (log scale)

Completeness in Percentage for groups CD and LS

Completeness in Percentage for group C

We only show NM and NTB for CD and LS, since they were the groups answered successfully by most TTL values.

Number of Messages for groups CD and LS (log scale)

Number of Transferred Bytes for groups CD and LS (log scale)

We tested with 0% replication (each fragment is only located on 1 node), 5% and 10%

Execution Time (ET) in Seconds for groups CD and LS (log scale)

Execution Time (ET) in Seconds for group C (log scale)

Execution Time (ET) in Seconds for groups L and CH (log scale)

Completeness in Percentage for groups CD and LS

Completeness in Percentage for group C

NM and NTB are the same with the exception of small fluctuations due to the specific neighbourhoods of the tested nodes. This is due to the network structure being the same (same amount of nodes contacted).

We tested with 2, 5 and 10 neighbors. We also tested with 0 and 1 neighbors, however none of the queries returned any results.

Execution Time (ET) in Seconds for groups CD and LS (log scale)

Execution Time (ET) in Seconds for group C (log scale)

Execution Time (ET) in Seconds for groups L and CH (log scale)

Completeness in Percentage for groups CD and LS

Completeness in Percentage for group C

INSTALLATION

PIQNIC is currently implemented only as a prototype for testing the performance and availability of a network. Some features, described in the paper are therefore missing. Here is a list of known differences:

In order to select query execution strategy, set the value of the field PROCESSOR in dk.aau.cs.qweb.piqnic.jena.PiqnicJenaConstants to either ProcessingType.FLOOD, ProcessingType.BIND, or ProcessingType.DOWN.

Requirements

Java 8 or newer.

Installation

  1. Download the .jar-file.
  2. Run with the following command: java -jar [filename].jar [config].json:
  3. Connect to the CLI port and follow the steps on screen.
  4. Example config.json:
  1. {
  2.   "replication" : 4,
  3.   "ports" : {
  4.     "listener" : 7625,
  5.     "cli" : 7626,
  6.     "test" : 7627
  7.   "maxFragments" : 200,
  8.   "timeToLive" : 5,
  9.   "shuffleLength" : 4,
  10.   "neighbours" : 5,
  11.   "minutesTilShuffle" : 200,
  12.   "maxDelay" : 500,
  13.   "version" : "0.1-SNAPSHOT"
  14. }

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