36,373 research outputs found
Social-aware Forwarding in Opportunistic Wireless Networks: Content Awareness or Obliviousness?
With the current host-based Internet architecture, networking faces
limitations in dynamic scenarios, due mostly to host mobility. The ICN paradigm
mitigates such problems by releasing the need to have an end-to-end transport
session established during the life time of the data transfer. Moreover, the
ICN concept solves the mismatch between the Internet architecture and the way
users would like to use it: currently a user needs to know the topological
location of the hosts involved in the communication when he/she just wants to
get the data, independently of its location. Most of the research efforts aim
to come up with a stable ICN architecture in fixed networks, with few examples
in ad-hoc and vehicular networks. However, the Internet is becoming more
pervasive with powerful personal mobile devices that allow users to form
dynamic networks in which content may be exchanged at all times and with low
cost. Such pervasive wireless networks suffer with different levels of
disruption given user mobility, physical obstacles, lack of cooperation,
intermittent connectivity, among others. This paper discusses the combination
of content knowledge (e.g., type and interested parties) and social awareness
within opportunistic networking as to drive the deployment of ICN solutions in
disruptive networking scenarios. With this goal in mind, we go over few
examples of social-aware content-based opportunistic networking proposals that
consider social awareness to allow content dissemination independently of the
level of network disruption. To show how much content knowledge can improve
social-based solutions, we illustrate by means of simulation some
content-oblivious/oriented proposals in scenarios based on synthetic mobility
patterns and real human traces.Comment: 7 pages, 6 figure
MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications
Mobile smartphones along with embedded sensors have become an efficient
enabler for various mobile applications including opportunistic sensing. The
hi-tech advances in smartphones are opening up a world of possibilities. This
paper proposes a mobile collaborative platform called MOSDEN that enables and
supports opportunistic sensing at run time. MOSDEN captures and shares sensor
data across multiple apps, smartphones and users. MOSDEN supports the emerging
trend of separating sensors from application-specific processing, storing and
sharing. MOSDEN promotes reuse and re-purposing of sensor data hence reducing
the efforts in developing novel opportunistic sensing applications. MOSDEN has
been implemented on Android-based smartphones and tablets. Experimental
evaluations validate the scalability and energy efficiency of MOSDEN and its
suitability towards real world applications. The results of evaluation and
lessons learned are presented and discussed in this paper.Comment: Accepted to be published in Transactions on Collaborative Computing,
2014. arXiv admin note: substantial text overlap with arXiv:1310.405
SocialDTN: A DTN implementation for Digital and Social Inclusion
Despite of the importance of access to computers and to the Internet for the
development of people and their inclusion in society, there are people that
still suffer with digital divide and social exclusion.
Delay/Disruption-Tolerant Networking (DTN) can help the digital/social
inclusion of these people as it allows opportunistic and asynchronous
communication, which does not depend upon networking infrastructure. We
introduce SocialDTN, an implementation of the DTN architecture for Android
devices that operates over Bluetooth, taking advantages of the social daily
routines of users. As we want to exploit the social proximity and interactions
existing among users, SocialDTN includes a social-aware opportunistic routing
proposal, dLife, instead of the well-known (but social-oblivious) PROPHET.
Simulations show the potential of dLife for our needs. Additionally, some
preliminary results from field experimentations are presented.Comment: 3 pages, 4 figure
Total order in opportunistic networks
Opportunistic network applications are usually assumed to work only with unordered immutable messages, like photos, videos, or music files, while applications that depend on ordered or mutable messages, like chat or shared contents editing applications, are ignored. In this paper, we examine how total ordering can be achieved in an opportunistic network. By leveraging on existing dissemination and causal order algorithms, we propose a commutative replicated data type algorithm on the basis of Logoot for achieving total order without using tombstones in opportunistic networks where message delivery is not guaranteed by the routing layer. Our algorithm is designed to use the nature of the opportunistic network to reduce the metadata size compared to the original Logoot, and even to achieve in some cases higher hit rates compared to the dissemination algorithms when no order is enforced. Finally, we present the results of the experiments for the new algorithm by using an opportunistic network emulator, mobility traces, and Wikipedia pages.Peer ReviewedPostprint (author's final draft
Social-aware Opportunistic Routing Protocol based on User's Interactions and Interests
Nowadays, routing proposals must deal with a panoply of heterogeneous
devices, intermittent connectivity, and the users' constant need for
communication, even in rather challenging networking scenarios. Thus, we
propose a Social-aware Content-based Opportunistic Routing Protocol, SCORP,
that considers the users' social interaction and their interests to improve
data delivery in urban, dense scenarios. Through simulations, using synthetic
mobility and human traces scenarios, we compare the performance of our solution
against other two social-aware solutions, dLife and Bubble Rap, and the
social-oblivious Spray and Wait, in order to show that the combination of
social awareness and content knowledge can be beneficial when disseminating
data in challenging networks
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