Predicting relative topological stability of mobile users in a P2P mobile cloud

In a P2P mobile cloud (PMC), an ad-hoc cloud is formed using the closely adjacent smart mobile devices (SMD). Here, a resource-deficient SMD user seeks its neighbouring resource-rich SMDs’ help to carry out a resource-wanting job. To maintain reliability and QoS of the PMC, it is necessary to be ass...

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Vydané v:	SN applied sciences Ročník 2; číslo 11; s. 1827
Hlavní autori:	Pramanik, Pijush Kanti Dutta, Bandyopadhyay, Gautam, Choudhury, Prasenjit
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 01.11.2020 Springer Nature B.V
Predmet:	Algorithms Applied and Technical Physics Availability Chemistry/Food Science Cloud computing Cloud Computing and IoT driven solutions for Real-Time Applications Earth Sciences Electronic devices Engineering Engineering: Big Data Environment Geographical distribution Geographical locations Internet of Things Materials Science Mobile computing Mobility Research Article Smartphones Stability analysis Logistic regression P2P cloud Mobility prediction Relative mobility Ad hoc mobile cloud Evaluation metrics Goodness of fit
ISSN:	2523-3963, 2523-3971
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Abstract	In a P2P mobile cloud (PMC), an ad-hoc cloud is formed using the closely adjacent smart mobile devices (SMD). Here, a resource-deficient SMD user seeks its neighbouring resource-rich SMDs’ help to carry out a resource-wanting job. To maintain reliability and QoS of the PMC, it is necessary to be assured of the availability of the SMDs before submitting a job request. If the job is distributed to multiple SMDs, instead of assessing the availability of a single SMD, the availability of a group of SMDs is required for a certain period of time. The objective of the paper is to find a stable group of SMD users to increase the QoS of PMC. We aim to propose a novel mobility prediction method to assess the probability of a group of SMD users to be relatively static with respect to each other. We propose an algorithm to estimate the relative stability of an SMD with respect to its neighbourhood over a period of time, irrespective of its geographical location. We assess the short-term relative stability between a group of SMD users as well as the long-term mobility pattern between them. For mobility calculation, we have used real user traces from the UCSD dataset. The estimated results are analyzed and validated using different metrics.
AbstractList	In a P2P mobile cloud (PMC), an ad-hoc cloud is formed using the closely adjacent smart mobile devices (SMD). Here, a resource-deficient SMD user seeks its neighbouring resource-rich SMDs’ help to carry out a resource-wanting job. To maintain reliability and QoS of the PMC, it is necessary to be assured of the availability of the SMDs before submitting a job request. If the job is distributed to multiple SMDs, instead of assessing the availability of a single SMD, the availability of a group of SMDs is required for a certain period of time. The objective of the paper is to find a stable group of SMD users to increase the QoS of PMC. We aim to propose a novel mobility prediction method to assess the probability of a group of SMD users to be relatively static with respect to each other. We propose an algorithm to estimate the relative stability of an SMD with respect to its neighbourhood over a period of time, irrespective of its geographical location. We assess the short-term relative stability between a group of SMD users as well as the long-term mobility pattern between them. For mobility calculation, we have used real user traces from the UCSD dataset. The estimated results are analyzed and validated using different metrics.
ArticleNumber	1827
Author	Choudhury, Prasenjit Pramanik, Pijush Kanti Dutta Bandyopadhyay, Gautam
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Cites_doi	10.12694/scpe.v20i2.1517 10.1002/nem.386 10.1002/9781118548387 10.1007/11534310_40 10.1016/j.future.2012.05.023 10.1007/BF01193332 10.1002/wcm.72 10.1002/0471712582 10.1002/wcm.441 10.2307/2490395 10.1007/s42452-020-2212-7 10.1109/IGBSG.2014.6835254 10.4135/9781412983433 10.1007/978-3-540-89707-1_3 10.1007/978-3-642-34321-6_25 10.1109/TMC.2004.1261820 10.1016/j.jpdc.2012.07.012 10.1145/2248371.2248394 10.1109/COMST.2005.1423333 10.1145/1072989.1072995 10.1007/978-3-642-20757-0_19 10.1109/90.554717 10.1109/26.103043 10.1002/0471722146 10.1109/CloudCom.2013.50 10.4018/978-1-5225-4200-1.ch009 10.1111/j.1468-5957.1985.tb00077.x 10.1109/INFOCOM.2006.173 10.1016/j.ins.2009.10.001 10.1109/ICACCS.2017.8014613 10.1109/49.709453 10.1145/1410012.1410014 10.1145/1317425.1317433 10.1007/s11227-016-1704-0
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References_xml	– reference: PramanikPKDPalSChoudhuryPGreen and sustainable high-performance computing with smartphone crowd computing: benefits, enablers, and challengesScalable Comput Pract Exp201920225928310.12694/scpe.v20i2.1517 – reference: HosmerDWLemeshowSApplied logistic regression20002HobokenWiley10.1002/0471722146 – reference: MusolesiMMascoloCDesigning mobility models based on social network theoryACM SIGMOBILE Mob Comput Commun Rev2007113597010.1145/1317425.1317433 – reference: TsuiJBYFundamental of global positioning system receivers: a software approach20042HobokenWiley10.1002/0471712582 – reference: Musolesi M, Mascolo C (2008) Mobility models for systems evaluation—a survey – reference: Gross T, Truduce C (2005) A mobility model based on wlan traces and its validation. In: 24th annual joint conference of the IEEE computer and communications societies, Miami, USA – reference: McNettMVoelkerGMAccess and mobility of wireless PDA usersMob Comput Commun Rev200592405510.1145/1072989.1072995 – reference: MillsDInternet time synchronization: the network time protocolIEEE Trans Commun199139101482149310.1109/26.103043 – reference: YuJChongPA survey of clustering schemes for mobile ad hoc networksIEEE Commun Surv Tutor200571324810.1109/COMST.2005.1423333 – reference: KhalifaIAbbasHMobility prediction in dynamic gridsJ Comput Inf Sci20125390 – reference: Basu P, Khan N, Little T (2001) A mobility based metric for clustering in mobile ad hoc networks. In: 21st international conference on distributed computing systems workshops, Mesa, AZ, USA – reference: Kim M, Kotz D, Kim S (2006) Extracting a mobility model from real user traces. 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In IEEE 5th international conference on cloud computing technology and science, Bristol, UK – reference: ShahSCNizamaniQ-U-AChauhdarySHParkM-SAn effective and robust two-phase resource allocation scheme for interdependent tasks in mobile ad hoc computational GridsJ Parallel Distrib Comput201272121664167910.1016/j.jpdc.2012.07.012 – reference: LevineDAkyildizINaghshinehMA resource estimation and call admission algorithm for wireless multimedia networks using the shadow cluster conceptIEEE/ACM Trans Netw19975111210.1109/90.554717 – reference: Li X, Mitton N, Simplot-Ryl D (2011) Mobility prediction based neighborhood discovery in mobile Ad Hoc networks. In: NETWORKING 2011. Lecture notes in computer science , vol 6640, J. Domingo-Pascual, P. Manzoni, S. Palazzo, A. Pont and C. Scoglio, Eds., Berlin, Heidelberg, Springer, 2011, pp 241–253. – reference: Chan J, Seneviratne A (1999) A practical user mobility prediction algorithm for supporting adaptive QoS in wireless networks. In: Seventh IEEE international conference on networks (ICON’99) – reference: AgrestiACategorical data analysis20123HobokenWiley0716.62001 – reference: FernandoNLokeSWRahayuWMobile cloud computing: a surveyFuture Gener Comput Syst2013298410610.1016/j.future.2012.05.023 – reference: WangWGuanXWangBWangYA novel mobility model based on semi-random circular movement in mobile Ad hoc networkJ Inf Sci2010180339941310.1016/j.ins.2009.10.001 – reference: ZavgrenCVAssessing the vulnerability of American industrial firms: a logistic analysisJ Bus Finan Acc1985121194510.1111/j.1468-5957.1985.tb00077.x – reference: Pramanik PKD, Choudhury P, Saha A (2017) Economical supercomputing thru smartphone crowd computing: an assessment of opportunities, benefits, deterrents, and applications from india’s perspective. In: 4th international conference on advanced computing and communication systems (ICACCS—2017), Coimbatore, India – reference: PramanikPKDChoudhuryPMobility-aware service provisioning for delay tolerant applications in a mobile crowd computing environmentSN Appl Sci20202311710.1007/s42452-020-2212-7 – reference: Chang C, Srirama SN, Ling S (2012) An adaptive mediation framework for mobile P2P social content sharing. In: Liu C, Ludwig H, Toumani F, Yu Q (eds) Service-oriented computing (ICSOC 2012). Lecture notes in computer science, vol 7636. Springer, Berlin, Heidelberg, pp 374–388 – reference: OhlsonJAFinancial ratios and the probabilistic prediction of bankruptcyJ Acc Res198018110913148429310.2307/2490395 – reference: Er I, Seah W (2004) Mobility-based d-hop clustering algorithm for mobile ad hoc networks. 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Snippet	In a P2P mobile cloud (PMC), an ad-hoc cloud is formed using the closely adjacent smart mobile devices (SMD). Here, a resource-deficient SMD user seeks its...
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SubjectTerms	Algorithms Applied and Technical Physics Availability Chemistry/Food Science Cloud computing Cloud Computing and IoT driven solutions for Real-Time Applications Earth Sciences Electronic devices Engineering Engineering: Big Data Environment Geographical distribution Geographical locations Internet of Things Materials Science Mobile computing Mobility Research Article Smartphones Stability analysis
Title	Predicting relative topological stability of mobile users in a P2P mobile cloud
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