2019
DOI: 10.1007/s00607-019-00715-6
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Hinode: implementing a vertex-centric modelling approach to maintaining historical graph data

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Cited by 6 publications
(6 citation statements)
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“…To the best of our knowledge, there is no modelling solutions of temporal graphs including all evolution types in order to be used in any desired application. Last but not least, some works propose a modelling approach of evolving graphs completely in break with snapshots [15,17]. They attach a valid time interval to each graph component (i.e.…”
Section: Related Workmentioning
confidence: 99%
“…To the best of our knowledge, there is no modelling solutions of temporal graphs including all evolution types in order to be used in any desired application. Last but not least, some works propose a modelling approach of evolving graphs completely in break with snapshots [15,17]. They attach a valid time interval to each graph component (i.e.…”
Section: Related Workmentioning
confidence: 99%
“…The models described above are organized by time: the dynamic behavior is indexed by the time it takes place. The models that belong to the category of distributed graph over servers are called entity-centric as their formulation focuses on nodes and their history during the timespan of the dynamic graph [33]. Nodes are organized in subsets which are handled by a set of servers.…”
Section: Distributed Graph Over Serversmentioning
confidence: 99%
“…Each server maintains the history of a subset of nodes [56]. For instance, HiNode [33] saves the history of each node using Interval Trees and B-Trees. The authors of [34] introduce materialization techniques and parallel complex graph data processing to reduce the memory usage while the model in [55] involves delta log files in its storage in order to reduce the update time.…”
Section: Distributed Graph Over Serversmentioning
confidence: 99%
“…In the third storage model, a dynamic graph is regarded as a set of varying instances. Each instance contains the update history of a single vertex [17], [28]. Han et al [29] proposed a method that divides the graph into multiple spatio-temporal chunks with each chunk covering a subset of vertices and spanning a certain time interval.…”
Section: Related Workmentioning
confidence: 99%
“…The third one saves storage consumption as well as provides high performance in recreating the historical state of a single vertex or a small sub-graph. However, it is inefficient to recreate the historical state of the whole graph [17].…”
Section: Introductionmentioning
confidence: 99%