Delay Tolerant Networking over the Metropolitan Public Transportation

We discuss MDTN: a delay tolerant application platform built on top of the Public Transportation System (PTS) and able to provide service access while exploiting opportunistic connectivity. Our solution adopts a carrier-based approach where buses act as data collectors for user requests requiring Internet access. Simulations based on real maps and PTS routes with state-of-the-art routing protocols demonstrate that MDTN represents a viable solution for elastic nonreal-time service delivery. Nevertheless, performance indexes of the considered routing policies show that there is no golden rule for optimal performance and a tailored routing strategy is required for each specific case

Plausible Mobility: Inferring Movement from Contacts

We address the difficult question of inferring plausible node mobility based only on information from wireless contact traces. Working with mobility information allows richer protocol simulations, particularly in dense networks, but requires complex set-ups to measure, whereas contact information is easier to measure but only allows for simplistic simulation models. In a contact trace a lot of node movement information is irretrievably lost so the original positions and velocities are in general out of reach. We propose a fast heuristic algorithm, inspired by dynamic force-based graph drawing, capable of inferring a plausible movement from any contact trace, and evaluate it on both synthetic and real-life contact traces. Our results reveal that (i) the quality of the inferred mobility is directly linked to the precision of the measured contact trace, and (ii) the simple addition of appropriate anticipation forces between nodes leads to an accurate inferred mobility.Comment: 8 pages, 8 figures, 1 tabl

SOCIAL AND LOCATION BASED ROUTING IN DELAY TOLERANT NETWORKS

Delay tolerant networks (DTNs) are a special type of wireless mobile networks which may lack continuous network connectivity. Routing in DTNs is very challenging as it must handle network partitions, long delays, and dynamic topology in such networks. Recently, the consideration of social characteristics of mobile nodes provides a new angle of view in the design of DTNs routing protocols. In many DTNs, a multitude of mobile devices are used and carried by people (e.g. pocket switched networks and vehicular networks), whose behaviors are better described by social models. This opens the new possibilities of social-based routing, in which the knowledge of social characteristics is used for making better forwarding decision. However, the social relations do not necessarily reflect the true device communication opportunities in a dynamic DTN. On the other hand, the increasing availability of location technologies (GPS, GSM networks, etc.) enables mobile devices to obtain their locations easily. Consider that an individual’s location history in the real world implies his/her social interests and behaviors to some extent, in this dissertation, we study new social based DTN routing protocols, which utilize location and/or social features to achieve efficient and stable routing for delay tolerant networks. We first incorporate the location features into the social-based DTN routing methods to improve their performance by treating location similarity among nodes as possible social relationship. Then, we dis- cuss the possibility and methods to further improve routing performance by adding limited amount of throw-boxes into the networks to aid the DTN relay. Several throw-boxes based routing protocols and location selection methods for throw-boxes are proposed. All pro- posed routing methods are evaluated via extensive simulations with real life trace data (such as MIT reality, Nokia MDC, and Orange D4D)

Understanding Urban Human Mobility for Network Applications

Understanding urban human mobility is crucial for various mobile and network applications. This thesis addresses two key challenges presented by mobile applications, namely urban mobility modeling and its applications in Delay Tolerant Networks (DTNs). First, we model urban human mobility with transportation mode information. Our research is based on two real-life GPS datasets containing approximately 20 and 10 million GPS samples. Previous research has suggested that the trajectories in human mobility have statistically similar features as Lévy Walks. We attempt to explain the Lévy Walks behavior by decomposing them into different classes according to the different transportation modes, such as Walk/Run, Bike, Train/ Subway or Car/Taxi/Bus. We show that human mobility can be modelled as a mixture of different transportation modes, and that these single movement patterns can be approximated by a lognormal distribution rather than a power-law distribution. Then, we demonstrate that the mixture of the decomposed lognormal flight distributions associated with each modality is a power-law distribution, providing an explanation for the emergence of Lévy Walks patterns that characterize human mobility patterns. Second, we find that urban human mobility exhibits strong spatial and temporal patterns. We leverage such human mobility patterns to derive an optimal routing algorithm that minimizes the hop count while maximizing the number of needed nodes in DTNs. We propose a solution framework, called Ameba, for timely data delivery in DTNs. Simulation results with experimental traces indicate that Ameba achieves a comparable delivery ratio to a Flooding-based algorithm, but with much lower overhead. Third, we infer the functions of the sub-areas in three cities by analyzing urban mobility patterns. The analysis is based on three large taxi GPS datasets in Rome, San Francisco and Beijing containing 21, 11 and 17 million GPS points, respectively. We categorize the city regions into four categories, workplaces, entertainment places, residential places and other places. We show that the identification of these functional sub-areas can be utilized to increase the efficiency of urban DTN applications. The three topics pertaining to urban mobility examined in the thesis support the design and implementation of network applications for urban environments.Ihmisen liikkumisen ymmärtäminen on erittäin tärkeää monille mobiiliverkkojen sovelluksille. Tämä väitöskirja käsittelee mobiilikäyttäjien liikkuvuuden mallintamista ja sen soveltamista viiveitä sietävään tiedonvälitykseen urbaanissa ympäristössä. Aloitamme mallintamalla mobiilikäyttäjien liikkuvuutta ottaen huomioon kulkumuodon. Tutkimuksemme perustuu kahteen laajaan GPS-data-aineistoon. Käytetyissä data-aineisto koostuu 10 ja 20 miljoonan havaintopisteen kulkuvälineet sisältävistä GPS-tiedoista. Aikaisemmat tutkimukset ovat ehdottaneet, että liikkuvuusmalleilla on samankaltaisia tilastollisia ominaisuuksia kuin Lévy-kävelyillä. Tutkimuksemme selittää Lévy-kävelyiden käyttäytymisen jakamalla ne erilaisiin kulkumuotoihin, kuten kävely/juoksu, polkupyöräily, juna/metro tai auto/taksi/bussi. Näytämme, että ihmisten liikkuvuus voidaan mallintaa eri kulkumuotojen yhdistelminä ja että yksittäiset liikkuvuusmallit voidaan arvioida logaritmisella normaalijakaumalla paremmin kuin potenssilakia noudattavalla jakaumalla. Lisäksi osoitamme, että yhdistelmä kävelyjen lavennetusta logaritmisesta normaalijakaumasta eri kulkumuotojen kanssa on potenssilakia noudattava jakauma, joka selittää ihmisten liikkuvuusmalleja luonnehtivien Lévy-kävelymallien esiintymisen. Toiseksi osoitamme, että urbaanin ihmisen liikkuvuuteen kuuluu vahvoja aikaan ja paikkaan liittyviä malleja. Johdamme näistä ihmisten liikkuvuusmalleista optimaalisen reititysalgoritmin, joka minimoi tarvittavien hyppyjen määrän ja maksimoi tarvittavien solmujen määrän viiveitä sietävissä verkoissa. Esitämme ratkaisuksi arkkitehtuurikehyksen nimeltä Ameba, joka takaa oikea-aikaisen viestien välityksen viiveitä sietävissä verkoissa. Simulointitulosten perusteella Ameba saavuttaa tulvitukseen perustuvien algoritmien kanssa vertailukelpoisen viestien kuljetussuhteen, mutta pienemmällä resurssikustannuksella. Kolmanneksi päättelemme maantieteellisten osa-alueiden funktiot analysoimalla kolmen kaupungin urbaaneja liikkumismalleja. Analyysi perustuu kolmeen laajaan taksien GPS-paikkatiedosta. GPS-data on kerätty Roomassa, San Franciscossa, ja Pekingissä ja koostuu 21, 11, ja 17 miljoonasta havaintopisteestä. Luokittelemme kaupunkien alueet neljään luokkaan: työpaikat, viihde-, asuin-, ja muut paikat. Näytämme, että näiden luokkien tunnistamista voidaan käyttää parantamaan viiveitä sietävien verkkojen sovellusten tehokkuutta. Kaikki tässä väitöskirjassa käsitellyt mobiilikäyttäjien liikkuvuuden mallintamisen aihepiirit edesauttavat urbaanien ympäristöjen verkkojen sovellusten suunnittelua ja toteutusta

Fine-Grained Intercontact Characterization in Disruption-Tolerant Networks

International audienceSo far, efforts attempting to characterize the spa- tiotemporal nature of disruption-tolerant networks (DTN) have relied on the dual notion of contacts and intercontacts. A contact happens when two nodes are within communication range of each other. An intercontact is simply defined as the dual of a contact, i.e., when two nodes are not in communication range of each other. We refer to this model as "binary". Although the binary characterization allows understanding the main interac- tion properties of the network, it is not sufficient to capture a plethora of situations beyond the binary hypothesis. In this paper, we investigate the structural properties of the network when nodes are not in contact but do have a contemporaneous path connecting them. We first introduce the notion of n- ary intercontact and, to defend its adoption, we quantify the proportion of nodes bearing this new intercontact notion in well-known datasets available to the community. Surprisingly, we observe that most pairs of nodes are nearby (within a few hops) for significant amounts of time when not directly in contact. Finally, we compare the impact of our proposal with the classic intercontact definition and give incentives toward using the n-ary characterization to leverage new communication opportunities

Efficient geocasting in opportunistic networks

With the proliferation of smartphones and their advanced connectivity capabilities, opportunistic networks have gained a lot of traction during the past years; they are suitable for increasing network capacity and sharing ephemeral, localised content. They can also offload traffic from cellular networks to device-to-device ones, when cellular networks are heavily stressed. Opportunistic networks can play a crucial role in communication scenarios where the network infrastructure is inaccessible due to natural disasters, large-scale terrorist attacks or government censorship. Geocasting, where messages are destined to specific locations (casts) instead of explicitly identified devices, has a large potential in real world opportunistic networks, however it has attracted little attention in the context of opportunistic networking. In this paper we propose Geocasting Spray And Flood (GSAF), a simple and efficient geocasting protocol for opportunistic networks. GSAF follows an elegant and flexible approach where messages take random walks towards the destination cast. Messages that are routed away from the destination cast are extinct when devices’ buffers get full, freeing space for new messages to be delivered. In GSAF, casts do not have to be pre-defined; instead users can route messages to arbitrarily defined casts. GSAF does that in a privacy-preserving fashion. We also present DA-GSAF, a Direction-Aware extension of GSAF in which messages are forwarded to encountered nodes based on whether a node is moving towards their destination cast. In DA-GSAF only the direction of a mobile node is revealed to other devices. We experimentally evaluate our protocols and compare their performance to prominent geocasting protocols in a very wide set of scenarios, including different maps, mobility models and user populations. Both GSAF and DA-GSAF perform significantly better compared to all other studied protocols, in terms of message delivery ratio, latency and network overhead. DA-GSAF is particularly efficient in sparse scenarios minimising network overhead compared to all other studied protocols. Both GSAF and DA-GSAF perform very well for a wide range of device/user populations indicating that our proposal is viable for crowded and sparse opportunistic networks

Fine-Grained Tracking of Human Mobility in Dense Scenarios

This paper envisions an urban scenario where people carry radio devices that can be dynamically networked, by exploiting human contact opportunities, to create unplanned, improvised and localized wireless connectivity, which has been recently called pocket switched networks (PSN).The paper focuses on the radio device (pocket mobility trace recorder, or PMTR) we have on purposely designed and developed to improve this understanding by enabling the gathering of rich and detailed mobility data sets from experiments in real mobility settings. The main contribution of the paper is twofold: we firstly describe the architecture of the radio devices and, secondly, we provide some evidence of the impact short contacts have on forwarding in dense settings