Homesick L\'evy walk: A mobility model having Ichi-go Ichi-e and scale-free properties of human encounters

In recent years, mobility models have been reconsidered based on findings by analyzing some big datasets collected by GPS sensors, cellphone call records, and Geotagging. To understand the fundamental statistical properties of the frequency of serendipitous human encounters, we conducted experiments to collect long-term data on human contact using short-range wireless communication devices which many people frequently carry in daily life. By analyzing the data we showed that the majority of human encounters occur once-in-an-experimental-period: they are Ichi-go Ichi-e. We also found that the remaining more frequent encounters obey a power-law distribution: they are scale-free. To theoretically find the origin of these properties, we introduced as a minimal human mobility model, Homesick L\'evy walk, where the walker stochastically selects moving long distances as well as L\'evy walk or returning back home. Using numerical simulations and a simple mean-field theory, we offer a theoretical explanation for the properties to validate the mobility model. The proposed model is helpful for evaluating long-term performance of routing protocols in delay tolerant networks and mobile opportunistic networks better since some utility-based protocols select nodes with frequent encounters for message transfer.Comment: 8 pages, 10 figure

SPoT: Representing the Social, Spatial, and Temporal Dimensions of Human Mobility with a Unifying Framework

Modeling human mobility is crucial in the analysis and simulation of opportunistic networks, where contacts are exploited as opportunities for peer-topeer message forwarding. The current approach with human mobility modeling has been based on continuously modifying models, trying to embed in them the mobility properties (e.g., visiting patterns to locations or specific distributions of inter-contact times) as they came up from trace analysis. As a consequence, with these models it is difficult, if not impossible, to modify the features of mobility or to control the exact shape of mobility metrics (e.g., modifying the distribution of inter-contact times). For these reasons, in this paper we propose a mobility framework rather than a mobility model, with the explicit goal of providing a exible and controllable tool for modeling mathematically and generating simulatively different possible features of human mobility. Our framework, named SPoT, is able to incorporate the three dimensions - spatial, social, and temporal - of human mobility. The way SPoT does it is by mapping the different social communities of the network into different locations, whose members visit with a configurable temporal pattern. In order to characterize the temporal patterns of user visits to locations and the relative positioning of locations based on their shared users, we analyze the traces of real user movements extracted from three location-based online social networks (Gowalla, Foursquare, and Altergeo). We observe that a Bernoulli process effectively approximates user visits to locations in the majority of cases and that locations that share many common users visiting them frequently tend to be located close to each other. In addition, we use these traces to test the exibility of the framework, and we show that SPoT is able to accurately reproduce the mobility behavior observed in traces. Finally, relying on the Bernoulli assumption for arrival processes, we provide a throughout mathematical analysis of the controllability of the framework, deriving the conditions under which heavy-tailed and exponentially-tailed aggregate inter-contact times (often observed in real traces) emerge

How Human Mobility Models Can Help to Deal with COVID-19

[EN] One of the key factors for the spreading of human infections, such as the COVID-19, is human mobility. There is a huge background of human mobility models developed with the aim of evaluating the performance of mobile computer networks, such as cellular networks, opportunistic networks, etc. In this paper, we propose the use of these models for evaluating the temporal and spatial risk of transmission of the COVID-19 disease. First, we study both pure synthetic model and simulated models based on pedestrian simulators, generated for real urban scenarios such as a square and a subway station. In order to evaluate the risk, two different risks of exposure are defined. The results show that we can obtain not only the temporal risk but also a heat map with the exposure risk in the evaluated scenario. This is particularly interesting for public spaces, where health authorities could make effective risk management plans to reduce the risk of transmission.Hernández-Orallo, E.; Armero-Martínez, A. (2021). How Human Mobility Models Can Help to Deal with COVID-19. Electronics. 10(1):1-24. https://doi.org/10.3390/electronics1001003312410

A Mobility Model for the Realistic Simulation of Social Context

Simulation is a fundamental means for evaluating mobile applications based on ad-hoc networks. In recent years, the new breed of social mobility models (SMMs) has risen. Contrary to most classical mobility models, SMMs model the social aspects of human mobility, i.e. which users meet, when and how often. Such information is indispensable for the simulation of a wide range of socially-aware communication protocols mostly based on delay-tolerant networks, including opportunistic ad-hoc routing and data dissemination systems. Each SMM needs a model of the relations between a set of relevant people (called social network model -- SNM) in order to simulate their mobility. Existing SMMs lack flexibility since each of them is implicitly restricted to a specific, simplifying SNM. We present GeSoMo (General Social Mobility Model), a new SMM that separates the core mobility model from the structural description of the social network underlying the simulation. This simple and elegant design principle gives GeSoMo generalizing power: Arbitrary existing and future SNMs can be used without changing GeSoMo itself. Our evaluation results show that GeSoMo produces simulations that are coherent with a broad range of empirical data describing real-world human social behavior and mobility

The effect of communication pattern on opportunistic mobile networks

Session - Smart Spaces and Personal Area NetworksSocial-based forwarding algorithms provide a new perspective on the study of routing in opportunistic mobile networks, and all of these schemes assume a uniform pattern for message generating rule. However, this is unconvincing due to the heterogeneity of contact rates in human communication patterns. In this paper we propose three social-based communication pattern models and utilize them to evaluate the network performance of different social-based routing protocols based on several human mobility traces. We find that communication patterns could significantly affect the network performance and the influence degree largely depends on the social metrics which these communication patterns are based on. We contend that considering communication pattern is quite important for designing a practical routing algorithm in opportunistic mobile networks. © 2011 IEEE.published_or_final_versionThe 8th IEEE Consumer Communications and Networking Conference (CCNC 2011), Las Vegas, NV., 9-12 January 2011. In Proceedings of the 8th CCNC, 2011, p. 1016-102

Improving Message Delivery Performance in Opportunistic Networks using a Forced-stop diffusion scheme

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-40509-4_11The performance of mobile opportunistic networks strongly depends on contact duration. If the contact lasts less than the required transmission times, some messages will not get delivered, and the whole diffusion scheme will be seriously affected. In this paper we propose a new diffusion method, called Forced-Stop, that is based on controlling node mobility to guarantee a complete message transfer. Using the ONE simulator and realistic mobility traces, we compared our proposal with the classical Epidemic diffusion. We show that Forced-Stop improves the message delivery performance, increasing the delivery ratio up to 30\%, and reducing the latency of message delivery up to 40\%, with a limited impact on buffer utilisation and message relaying. These results can be a relevant indication to the designers of opportunistic network applications that could integrate in their products strategies to inform the user about the need to temporarily stop in order to favor the overall data delivery.This work was partially supported by the Ministerio de Economía y Competitividad, Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014, Spain, under Grant TEC2014-52690-R, the Generalitat Valenciana, Spain, under Grant AICO/2015/108, the Secretaría Nacional de Educación Superior, Ciencia, Tecnología e Innovación del Ecuador(SENESCYT), and the Universidad Laica Eloy Alfaro de Manabi, Ecuador.Herrera Tapia, J.; Hernández Orallo, E.; Tomás Domínguez, AE.; Manzoni, P.; Tavares De Araujo Cesariny Calafate, CM.; Cano Escribá, JC. (2016). Improving Message Delivery Performance in Opportunistic Networks using a Forced-stop diffusion scheme. En Ad-hoc, Mobile, and Wireless Networks. Springer. 156-168. https://doi.org/10.1007/978-3-319-40509-4_11S156168Pelusi, L., Passarella, A., Conti, M.: Opportunistic networking: data forwarding in disconnected mobile ad hoc networks. IEEE Commun. Mag. 44(11), 134–141 (2006)Ferretti, S.: Shaping opportunistic networks. Comput. Commun. 36, 481–503 (2013)Keränen, A., Ott, J., Kärkkäinen, T.: The ONE simulator for DTN protocol evaluation. In: Proceedings of the Second International ICST Conference on Simulation Tools and Techniques, Rome (2009)Tsai, T.-C., Chan, H.-H.: NCCU Trace: social-network-aware mobility trace. IEEE Commun. Mag. 53, 144–149 (2015)AnAverage WhatsApp User Sends Messages per Month, 15 September 2015. http://www.statista.com/chart/1938/monthly-whatsapp-usage-per-userNiu, J., Guo, J., Cai, Q., Sadeh, N., Guo, S.: predict and spread: an efficient routing algorithm for opportunistic networking. In: Wireless Communications and Networking Conference (WCNC), 2011 IEEE, pp. 498–503, Cancún (2011)Thakur, G.S., Kumar, U., Helmy, A., Hsu, W.-J.: On the efficacy of mobility modeling for DTN evaluation: analysis of encounter statistics andspatio-temporal preferences. In: 7th International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 510–515, Istanbul (2011)Warthman, F.: Delay-and Disruption-Tolerant Networks (DTNs) a tutorial, version 2.0. In: The InterPlaNetary (IPN) Internet Project. InterPlanetary Networking Special Interest Group (IPNSIG) (2012)Battestini, A., Setlur, V., Sohn, T.: A large scale study of text messaging use. In: 12th International Conference on Human Computer Interaction with Mobile Devices and Services MobileHCI, pp. 1–10, Lisbon (2010)Förster, A., Garg, K., Nguyen, H.A., Giordano, S. On context awareness and social distance in human mobility traces. In: Third ACM International Workshop on Mobile Opportunistic Networks, pp. 5–12, Zürich (2012)Boldrini, C., Conti, M., Passarella, A.: Modelling data dissemination in opportunistic networks. In: Proceedings of the Third ACM Workshop on Challenged Networks - CHANTS 2008, pp. 89–96, San Francisco (2008)Natalizio, E., Loscrí, V.: Controlled mobility in mobile sensor networks: advantages, issues and challenges. Telecommun. Syst. 52(4), 2411–2418 (2013)Neena, V.V., Rajam, V.M.A.: Performance analysis of epidemic routing protocol for opportunistic networks in different mobility patterns. In: 2013 International Conference on Computer Communication and Informatics, pp. 1–5, Coimbatore (2013)Mehta, N., Shah, M.: Performance evaluation of efficient routing protocols in delay tolerant network under different human mobility models. Int. J. Grid Distrib. Comput. 8(1), 169–178 (2015)Su, J., Chin, A., Popivanova, A., Goel, A., Lara, E.D.: User mobility for opportunistic ad-hoc networking. In: Sixth IEEE Workshop on Mobile Computing Systems and Applications (WMCSA 2004), Low Wood (2004)Feng, Z., Chin, K.-W.: A unified study of epidemic routing protocols and their enhancements. In: IEEE 26th International Parallel and Distributed Processing Symposium Workshops PhD Forum (IPDPSW), pp. 1484–1493, Shanghai (2012)Vardalis, D., Tsaoussidis, V.: Exploiting the potential of DTN for energy-efficient internetworking. J. Syst. Softw. 90, 91–103 (2014)Rango, F.D., Amelio, S., Fazio, P.: Epidemic strategies in delay tolerant networks from an energetic point of view: main issues and performance evaluation. J. Networks 10(01), 4–14 (2015)Herrera-Tapia, J., Manzoni, P., Hernández-Orallo, E., Calafate, C.T., Cano, J.-C.: Power consumption evaluation in vehicular opportunistic networks. In: IEEE 12th CCNC 2015 Workshops - VENITS, pp. 925–930, Las Vegas (2015)Erramilli, V., Crovella, M.: Forwarding in opportunistic networks with resource constraints. In: Proceedings of the third ACM workshop on Challenged networks - CHANTS 2008, pp. 41–47, San Francisco (2008)Fathima, G., Wahidabanu, R.: Buffer management for preferential delivery in opportunistic delay tolerant networks. Int. J. Wirel. Mob. Netw. (IJWMN) 3, 15–28 (2011)Pan, D., Ruan, Z., Zhou, N., Liu, X., Song, Z.: A comprehensive-integrated buffer management strategy for opportunistic networks. EURASIP J. Wirel. Commun. Netw. 2013(1), 1–10 (2013)Hernández-Orallo, E., Herrera-Tapia, J., Cano, J.-C., Calafate, C.T., Manzoni, P.: Evaluating the impact of data transfer time in contact-based messaging applications. IEEE Commun. Lett. 19, 1814–1817 (2015)de Abreu, C.S., Salles, R.M.: Modeling message diffusion in epidemical DTN. Ad Hoc Netw. 16, 197–209 (2014