{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T18:24:57Z","timestamp":1761157497879,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031251573"},{"type":"electronic","value":"9783031251580"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-25158-0_5","type":"book-chapter","created":{"date-parts":[[2023,2,13]],"date-time":"2023-02-13T21:37:20Z","timestamp":1676324240000},"page":"45-59","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["ACF2: Accelerating Checkpoint-Free Failure Recovery for\u00a0Distributed Graph Processing"],"prefix":"10.1007","author":[{"given":"Chen","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingfeng","family":"Pan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongfu","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,2,10]]},"reference":[{"issue":"10","key":"5_CR1","doi-asserted-by":"publisher","first-page":"1151","DOI":"10.14778\/3231751.3231764","volume":"11","author":"K Ammar","year":"2018","unstructured":"Ammar, K., et al.: Experimental analysis of distributed graph systems. Proc. VLDB Endow. 11(10), 1151\u20131164 (2018)","journal-title":"Proc. VLDB Endow."},{"key":"5_CR2","doi-asserted-by":"crossref","unstructured":"Dathathri, R., et al.: Phoenix: a substrate for resilient distributed graph analytics. In: ASPLOS, pp. 615\u2013630 (2019)","DOI":"10.1145\/3297858.3304056"},{"key":"5_CR3","unstructured":"Gonzalez, J.E., et al.: Powergraph: distributed graph-parallel computation on natural graphs. In: OSDI, pp. 17\u201330 (2012)"},{"key":"5_CR4","unstructured":"Gonzalez, J.E., et al.: Graphx: graph processing in a distributed dataflow framework. In: OSDI, pp. 599\u2013613 (2014)"},{"issue":"2","key":"5_CR5","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1109\/TKDE.2017.2762294","volume":"30","author":"V Kalavri","year":"2018","unstructured":"Kalavri, V., et al.: High-level programming abstractions for distributed graph processing. IEEE Trans. Knowl. Data Eng. 30(2), 305\u2013324 (2018)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"5_CR6","unstructured":"Li, B., et al.: : A trusted parallel route planning model on dynamic road networks. TITS (2022)"},{"issue":"8","key":"5_CR7","doi-asserted-by":"publisher","first-page":"716","DOI":"10.14778\/2212351.2212354","volume":"5","author":"Y Low","year":"2012","unstructured":"Low, Y., et al.: Distributed graphLab: a framework for machine learning in the cloud. Proc. VLDB Endow. 5(8), 716\u2013727 (2012)","journal-title":"Proc. VLDB Endow."},{"issue":"3","key":"5_CR8","doi-asserted-by":"publisher","first-page":"281","DOI":"10.14778\/2735508.2735517","volume":"8","author":"Y Lu","year":"2014","unstructured":"Lu, Y., et al.: Large-scale distributed graph computing systems: an experimental evaluation. Proc. VLDB Endow. 8(3), 281\u2013292 (2014)","journal-title":"Proc. VLDB Endow."},{"key":"5_CR9","doi-asserted-by":"crossref","unstructured":"Malewicz, G., et al.: Pregel: a system for large-scale graph processing. In: SIGMOD, pp. 135\u2013146 (2010)","DOI":"10.1145\/1807167.1807184"},{"key":"5_CR10","doi-asserted-by":"crossref","unstructured":"McCune, R.R., Weninger, T., Madey, G.: Thinking like a vertex: a survey of vertex-centric frameworks for large-scale distributed graph processing. ACM Comput. Surv. 48(2), 1\u201339 (2015)","DOI":"10.1145\/2818185"},{"key":"5_CR11","doi-asserted-by":"crossref","unstructured":"Pundir, M., et al.: Zorro: zero-cost reactive failure recovery in distributed graph processing. In: SoCC, pp. 195\u2013208 (2015)","DOI":"10.1145\/2806777.2806934"},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Schelter, S., et al.: \u201cAll roads lead to rome\u201d: optimistic recovery for distributed iterative data processing. In: CIKM, pp. 1919\u20131928 (2013)","DOI":"10.1145\/2505515.2505753"},{"issue":"4","key":"5_CR13","doi-asserted-by":"publisher","first-page":"437","DOI":"10.14778\/2735496.2735506","volume":"8","author":"Y Shen","year":"2014","unstructured":"Shen, Y., et al.: Fast failure recovery in distributed graph processing systems. Proc. VLDB Endow. 8(4), 437\u2013448 (2014)","journal-title":"Proc. VLDB Endow."},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Vora, K., et al.: Coral: confined recovery in distributed asynchronous graph processing. In: ASPLOS, pp. 223\u2013236 (2017)","DOI":"10.1145\/3093336.3037747"},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Wang, P., et al.: Replication-based fault-tolerance for large-scale graph processing. In: DSN, pp. 562\u2013573 (2014)","DOI":"10.1109\/DSN.2014.58"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Xu, C., et al.: Efficient fault-tolerance for iterative graph processing on distributed dataflow systems. In: ICDE, pp. 613\u2013624 (2016)","DOI":"10.1109\/ICDE.2016.7498275"},{"key":"5_CR17","doi-asserted-by":"crossref","unstructured":"Yan, D., et al.: Lightweight fault tolerance in Pregel-like systems. In: ICPP, pp. 1\u201310 (2019)","DOI":"10.1145\/3337821.3337823"},{"key":"5_CR18","unstructured":"Zaharia, M., et al.: Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing. In: NSDI, pp. 15\u201328 (2012)"}],"container-title":["Lecture Notes in Computer Science","Web and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-25158-0_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T19:03:41Z","timestamp":1689879821000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-25158-0_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031251573","9783031251580"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-25158-0_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"10 February 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APWeb-WAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 August 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apwebwaim2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/apweb-waim2022.com\/proceedings","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"297","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"75","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"45","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"25% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5 Demo papers + 23 workshop papers","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}