327 research outputs found
Social Data Offloading in D2D-Enhanced Cellular Networks by Network Formation Games
Recently, cellular networks are severely overloaded by social-based services,
such as YouTube, Facebook and Twitter, in which thousands of clients subscribe
a common content provider (e.g., a popular singer) and download his/her content
updates all the time. Offloading such traffic through complementary networks,
such as a delay tolerant network formed by device-to-device (D2D)
communications between mobile subscribers, is a promising solution to reduce
the cellular burdens. In the existing solutions, mobile users are assumed to be
volunteers who selfishlessly deliver the content to every other user in
proximity while moving. However, practical users are selfish and they will
evaluate their individual payoffs in the D2D sharing process, which may highly
influence the network performance compared to the case of selfishless users. In
this paper, we take user selfishness into consideration and propose a network
formation game to capture the dynamic characteristics of selfish behaviors. In
the proposed game, we provide the utility function of each user and specify the
conditions under which the subscribers are guaranteed to converge to a stable
network. Then, we propose a practical network formation algorithm in which the
users can decide their D2D sharing strategies based on their historical
records. Simulation results show that user selfishness can highly degrade the
efficiency of data offloading, compared with ideal volunteer users. Also, the
decrease caused by user selfishness can be highly affected by the cost ratio
between the cellular transmission and D2D transmission, the access delays, and
mobility patterns
Towards new methods for mobility data gathering: content, sources, incentives
Over the past decade, huge amounts of work has been done in mobile and opportunistic networking research. Unfortunately, much of this has had little impact as the results have not been applicable to reality, due to incorrect assumptions and models used in the design and evaluation of the systems.
In this paper, we outline some of the problems of the assumptions of early research in the field, and provide a survey of some initial work that has started to take place to alleviate this through more realistic modelling and measurements of real systems. We do note that there is still much work to be done in this area, and then go on to identify some important properties of the network that must be studied further. We identify the types of data that are important to measure, and also give some guidelines on finding existing and potentially new sources for such data and incentivizing the holders of the data to share it
Opportunistic mobile social networks: architecture, privacy, security issues and future directions
Mobile Social Networks and its related applications have made a very great impact in the society. Many new technologies related to mobile social networking are booming rapidly now-a-days and yet to boom. One such upcoming technology is Opportunistic Mobile Social Networking. This technology allows mobile users to communicate and exchange data with each other without the use of Internet. This paper is about Opportunistic Mobile Social Networks, its architecture, issues and some future research directions. The architecture and issues of Opportunistic Mobile Social Networks are compared with that of traditional Mobile Social Networks. The main contribution of this paper is regarding privacy and security issues in Opportunistic Mobile Social Networks. Finally, some future research directions in Opportunistic Mobile Social Networks have been elaborated regarding the data's privacy and security
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
Social-Aware Forwarding Improves Routing Performance in Pocket Switched Networks
Several social-aware forwarding strategies have been recently intro- duced in opportunistic networks, and proved eective in considerably in- creasing routing performance through extensive simulation studies based on real-world data. However, this performance improvement comes at the expense of storing a considerable amount of state information (e.g, history of past encounters) at the nodes. Hence, whether the benets on routing performance comes directly from the social-aware forwarding mechanism, or indirectly by the fact state information is exploited is not clear. Thus, the question of whether social-aware forwarding by itself is eective in im- proving opportunistic network routing performance remained unaddressed so far. In this paper, we give a rst, positive answer to the above question, by investigating the expected message delivery time as the size of the net- work grows larger. In order to make a fair comparison with stateless, social oblivious forwarding mechanisms such as BinarySW, we introduce a simple stateless, social-aware forwarding mechanism exploiting a notion of similarity between individual interests. We then compare the asymp- totic performance of interest-based forwarding with that of BinarySW under two mobility scenarios, modeling situations in which node pairwise meeting rates are independent of or correlated to the similarity of their in- terests. We formally prove that, while asymptotic expected delivery time of BinarySW is highly dependent on the underlying mobility model, with unbounded expected delivery time in presence of correlated mobility, this is not the case with interest-based forwarding, which provides bounded expected delivery time with both mobility models. Thus, our ndings for- mally prove that social-aware forwarding, even when not exploiting state information, has the potential to considerably improve routing perfor- mance in opportunistic networks over traditional forwarding mechanisms
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