{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T03:15:16Z","timestamp":1761621316841,"version":"3.41.0"},"reference-count":30,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2017,5,10]],"date-time":"2017-05-10T00:00:00Z","timestamp":1494374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGMETRICS Perform. Eval. Rev."],"published-print":{"date-parts":[[2017,5,10]]},"abstract":"<jats:p>Mobile Crowdsensing (MCS) is a contribution-based paradigm involving mobiles in pervasive application deployment and operation, pushed by the evergrowing and widespread dissemination of personal devices. Nevertheless, MCS is still lacking of some key features to become a disruptive paradigm. Among others, control on performance and reliability, mainly due to the contribution churning. For mitigating the impact of churning, several policies such as redundancy, over-provisioning and checkpointing can be adopted but, to properly design and evaluate such policies, specific techniques and tools are required.<\/jats:p>\n          <jats:p>This paper attempts to fill this gap by proposing a new technique for the evaluation of relevant performance and energy figures of merit for MCS systems. It allows to get insightson them from three different perspectives: end users, contributors and service providers. Based on queuing networks (QN), the proposed technique relaxes the assumptions of existing solutions allowing a stochastic characterization of underlying phenomena through general, non exponential distributions. To cope with the contribution churning it extends the QN semantics of a service station with variablenumber of servers, implementing proper mechanisms to manage the memory issues thus arising in the underlying process. This way, a preliminary validation of the proposed QN model against an analytic one and an in depth investigation also considering checkpointing have been performed through a case study.<\/jats:p>","DOI":"10.1145\/3092819.3092829","type":"journal-article","created":{"date-parts":[[2017,5,10]],"date-time":"2017-05-10T18:08:53Z","timestamp":1494439733000},"page":"80-90","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Characterization and Evaluation of Mobile CrowdSensing Performance and Energy Indicators"],"prefix":"10.1145","volume":"44","author":[{"given":"Riccardo","family":"Pinciroli","sequence":"first","affiliation":[{"name":"Politecnico di Milano, Milano, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Salvatore","family":"Distefano","sequence":"additional","affiliation":[{"name":"Universit\u00e1 di Messina, Messina, Italy and Kazan Federal University, Kazan, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,5,10]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.1070.0437"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/PerComW.2014.6815170"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1530873.1530877"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2013.6525603"},{"key":"e_1_2_1_5_1","volume-title":"USENIX annual technical conference","author":"Carroll A.","year":"2010","unstructured":"A. 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Distefano. Extending Queuing Networks to Assess Mobile CrowdSensing Application Performance. In The sixth Workshop of the Italian group on Quantitative Methods in Informatics (InfQ2016) - Valuetools 2016. ACM."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2307636.2307668"},{"key":"e_1_2_1_26_1","volume-title":"Modeling server-unreliability in closed queuing-networks","author":"Ramanjaneyulu C.","year":"1989","unstructured":"C. Ramanjaneyulu and V. Sarma . Modeling server-unreliability in closed queuing-networks . IEEE transactions on reliability, 38(1):90--95, 1989 . C. Ramanjaneyulu and V. Sarma. Modeling server-unreliability in closed queuing-networks. IEEE transactions on reliability, 38(1):90--95, 1989."},{"key":"e_1_2_1_27_1","first-page":"60","volume-title":"Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops","author":"Varga A.","unstructured":"A. Varga and R. Hornig . 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