Offloading cellular traffic through opportunistic communications: analysis and optimization

Offloading traffic through opportunistic communications has been recently proposed as a way to relieve the current overload of cellular networks. Opportunistic communication can occur when mobile device users are (temporarily) in each other's proximity, such that the devices can establish a local peer-to-peer connection (e.g., via WLAN or Bluetooth). Since opportunistic communication is based on the spontaneous mobility of the participants, it is inherently unreliable. This poses a serious challenge to the design of any cellular offloading solutions, that must meet the applications' requirements. In this paper, we address this challenge from an optimization analysis perspective, in contrast to the existing heuristic solutions. We first model the dissemination of content (injected through the cellular interface) in an opportunistic network with heterogeneous node mobility. Then, based on this model, we derive the optimal content injection strategy, which minimizes the load of the cellular network while meeting the applications' constraints. Finally, we propose an adaptive algorithm based on control theory that implements this optimal strategy without requiring any data on the mobility patterns or the mobile nodes' contact rates. The proposed approach is extensively evaluated with both a heterogeneous mobility model as well as real-world contact traces, showing that it substantially outperforms previous approaches proposed in the literature.This work has been sponsored by the HyCloud project, supported by Microsoft Innovation Cluster for Embedded Software (ICES), and by the EU H2020-ICT-2014-2 Flex5Gware project, no. 671563

Relieving the Wireless Infrastructure: When Opportunistic Networks Meet Guaranteed Delays

Major wireless operators are nowadays facing network capacity issues in striving to meet the growing demands of mobile users. At the same time, 3G-enabled devices increasingly benefit from ad hoc radio connectivity (e.g., Wi-Fi). In this context of hybrid connectivity, we propose Push-and-track, a content dissemination framework that harnesses ad hoc communication opportunities to minimize the load on the wireless infrastructure while guaranteeing tight delivery delays. It achieves this through a control loop that collects user-sent acknowledgements to determine if new copies need to be reinjected into the network through the 3G interface. Push-and-Track includes multiple strategies to determine how many copies of the content should be injected, when, and to whom. The short delay-tolerance of common content, such as news or road traffic updates, make them suitable for such a system. Based on a realistic large-scale vehicular dataset from the city of Bologna composed of more than 10,000 vehicles, we demonstrate that Push-and-Track consistently meets its delivery objectives while reducing the use of the 3G network by over 90%.Comment: Accepted at IEEE WoWMoM 2011 conferenc

Extending cloud-based applications in challenged environments with mobile opportunistic networks

With the tremendous growth of mobile devices, e.g, smartphones, tablets and PDAs in recent years, users are looking for more advanced platforms in order to use their computational applications (e.g., processing and storage) in a faster and more convenient way. In addition, mobile devices are capable of using cloud-based applications and the use of such technology is growing in popularity. However, one major concern is how to efficiently access these cloud-based applications when using a resource-constraint mobile device. Essentially applications require a continuous Internet connection which is difficult to obtain in challenged environments that lack an infrastructure for communication (e.g., in sparse or rural areas) or areas with infrastructure (e.g., urban or high density areas) with restricted/full of interference access networks and even areas with high costs of Internet roaming. In these situations the use of mobile opportunistic networks may be extended to avail cloud-based applications to the user. In this thesis we explore the emergence of extending cloud-based applications with mobile opportunistic networks in challenged environments and observe how local user’s social interactions and collaborations help to improve the overall message delivery performance in the network. With real-world trace-driven simulations, we compare and contrast the different user’s behaviours in message forwarding, the impact of the various network loads (e.g., number of messages) along with the long-sized messages and the impact of different wireless networking technologies, in various opportunistic routing protocols in a challenged environment

From MANET to people-centric networking: Milestones and open research challenges

In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

Tactful opportunistic forwarding: What human routines and cooperation can improve?

International audienceOpportunistic D2D forwarding algorithms have leveraged human mobility characteristics to improve cost-effective content delivery. Most previous proposals focused on traditional or simplistic human-centered metrics to improve performance in scenarios such as cellular data offloading. Still, there is a need to approximate algorithm's metrics to inherent in-depth aspects of human mobility hidden into real datasets while leveraging more realistic scenarios interesting to mobile operators. This work proposes TOOTS, a novel human-aware opportunistic D2D forwarding strategy for cost-effective content delivery on cellular networks. TOOTS features a dissemination policy and a forwarding algorithm that leverages wireless encounters patterns, temporal, spatial, geographic, and direction awareness to improve cost-effectiveness delivery. These characteristics are extracted from NCCU and GRM datasets. We compare TOOTS with the most popular state-of-art social-aware algorithm, Bubble Rap, combined with three dissemination policies. Results from TOOTS show increased performance in terms of delivery rate, delivery latency, and overhead.Les algorithmes de transfert opportunistes D2D ont exploité les caractéristiques de la mobilité humaine pour améliorer la livraison de contenu rentable. La plupart des propositions précédentes se sont concentrées sur des mesures traditionnelles ou simplistes centrées sur l'homme pour améliorer les performances dans des scénarios tels que le déchargement de données cellulaires. Néanmoins, il est nécessaire de rapprocher les métriques de l'algorithme des aspects inhérents en profondeur de la mobilité humaine cachés dans des ensembles de données réels tout en tirant parti de scénarios plus réalistes intéressants pour les opérateurs mobiles. Ce travail propose TOOTS, une nouvelle stratégie de transmission D2D opportuniste consciente de l'homme pour la livraison de contenu rentable sur les réseaux cellulaires. TOOTS propose une politique de diffusion et un algorithme de transmission qui tire parti des modèles de rencontres sans fil, de la sensibilité temporelle, spatiale, géographique et de la direction pour améliorer le rapport coût-efficacité. Ces caractéristiques sont extraites des ensembles de données NCCU et GRM. Nous comparons TOOTS avec l'algorithme social de pointe le plus populaire, Bubble Rap, combiné à trois politiques de diffusion. Les résultats de TOOTS montrent des performances accrues en termes de taux de livraison, de latence de livraison et de frais généraux

Hybrid routing in delay tolerant networks

This work addresses the integration of today\\u27s infrastructure-based networks with infrastructure-less networks. The resulting Hybrid Routing System allows for communication over both network types and can help to overcome cost, communication, and overload problems. Mobility aspect resulting from infrastructure-less networks are analyzed and analytical models developed. For development and deployment of the Hybrid Routing System an overlay-based framework is presented

Towards Proactive Mobility-Aware Fog Computing

Paljude värkvõrk- ja ärirakenduste tavapäraseks osaks on sõltuvus kaugete pilveteenuste poolt pakutavast andmetöötlusvõimekusest. Arvestatav hulk seesugustest rakendustest koguvad andmeid mitmetelt ümbritsevatelt heterogeensetelt seadmetelt, et pakkuda reaalajal põhinevaid teenuseid oma kasutajatele. Taolise lahenduse negatiivseks küljeks on aga kõrge viiteaeg, mis muutub eriti problemaatiliseks, kui vastava rakenduse efektiivne töö on väleda vastuse saamisega otseses sõltuvuses. Taolise olukorra puhul on viiteaja vähendamiseks välja pakutud uduandmetöötlusel põhinev arhitektuur, mis kujutab endast arvutusmahukate andmetöötlusühikute jaotamist andmeallikate ja lõppkasutajatele lähedal asuvatele arvutusseadmetele. Vaatamata sellele, et uduandmetöötlusel põhinev arhitektuur on paljutõotav, toob see kaasa uusi väljakutseid seoses kvaliteetse uduandmetöötlusteenuse pakkumisega mobiilsetele kasutajatele. Käesolev magistritöö käsitleb proaktiivset lähenemist uduandmetöötlusele, kasutades selleks lähedalasuvatel kasutajatel baseeruvat mobiilset ad hoc võrgustikku, mis võimaldab uduteenusetuvastust ja juurdepääsu ilma pilveteenuse abi kasutamata. Proaktiivset lähenemist kasutatakse nii teenusetuvastuse ja arvutuse migratsiooni kui ka otsese uduteenuse pakkumise käigus, kiirendades arvutusühikute jaotusprotsessi ning parendadades arvutuste jaotust vastavalt käitusaegsele kontekstiinfole (nt. arvutusseadmete hetkevõimekus). Lisaks uuriti uduarvutuse rakendusviisi mobiilses sotsiaal–silmusvõrgustikus, tehes andmeedastuseks optimaalseima valiku vastavalt kuluefektiivsuse indeksile. Lähtudes katsetest nii päris seadmete kui simulaatoritega, viidi läbi käesoleva magistritöö komponentide kontseptuaalsete prototüüpide testhindamine.A common approach for many Internet of Things (IoT) and business applications is to rely on distant Cloud services for the processing of data. Several of these applications collect data from a multitude of proximity-based ubiquitous resources to provide various real-time services for their users. However, this has the downside of resulting in explicit latency of the result, being especially problematic when the application requires a rapid response in the edge network. Therefore, researchers have proposed the Fog computing architecture that distributes the computational data processing tasks to the edge network nodes located in the vicinity of the data sources and end-users, to reduce the latency. Although the Fog computing architecture is promising, it still faces challenges in many areas, especially when dealing with support for mobile users. Utilizing Fog for real-time mobile applications faces the new challenge of ensuring the seamless accessibility of Fog services on the move. Further, Fog computing also faces a challenge in mobility when the tasks originate from mobile ubiquitous applications in which the data sources are moving objects. In this thesis, a proactive approach for Fog computing is proposed, which supports proactive Fog service discovery and process migration using Mobile Ad hoc Social Network in proximity, enabling Fog-assisted ubiquitous service provisioning in proximity without distant Cloud services. Moreover, a proactive approach is also applied for the Fog service provisioning itself, in order to hasten the task distribution process in Mobile Fog use cases and provide an optimization scheme based on runtime context information. In addition, a case study regarding the usage of Fog Computing for the enhancement of Mobile Mesh Social Network was presented, along with a resource-aware Cost-Performance Index scheme to assist choosing the approach to be used for transmission of data. The proposed elements have been evaluated by utilizing a combination of real devices and simulators in order to provide proof-of-concept