A Protocol for Content-Based Communication in Disconnected Mobile Ad Hoc Networks

Haillot, Julien; Guidec, Frédéric

doi:10.1109/aina.2008.82

Cited by 24 publications

(16 citation statements)

References 12 publications

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“…For effective content‐based dissemination, the flow of information should be interest driven rather than destination driven. Destinations announce their interested information, without regard to any specific source . Most of the current content dissemination schemes are network‐centric and ignore destinations' interests .…”

Section: Related Workmentioning

confidence: 99%

“…Content‐based dissemination in the infrastructure network is performed by constructing an overlay network, whose role is to forward content from source to all interested destinations and nodes' interests are extracted from some kind of social networks . But this approach hits a major barrier to be applied in MSNs, which is the lack of end‐to‐end connectivity between nodes that prevents building any network‐wide overlay . So reported methods unveil innovative approaches for content‐based dissemination which in turn face new challenges.…”

Section: Related Workmentioning

confidence: 99%

“…Destinations announce their interested information, without regard to any specific source. 15 Most of the current content dissemination schemes are network-centric and ignore destinations' interests. 17 But MSN applications need to deliver data to a group of interested destinations instead of single destinations, 18 and sources in the content-based applications disseminate data in the network without specifying any destination, 15 thus contents are delivered to the destinations based on their interests.…”

Section: Content-based Disseminationmentioning

confidence: 99%

“…Such applications are called content‐based or targeted content exchange applications (TCEA). Some examples of TCEA in MSNs are commodity promotion advertisements, traffic congestion notifications, military battlefield information, content‐based multicast, and P2P file sharing …”

Section: Introductionmentioning

confidence: 99%

“…Some examples of TCEA in MSNs are commodity promotion advertisements, 9,10 traffic congestion notifications, 9,11 military battlefield information, 12 content-based multicast, 13 and P2P file sharing. 14,15 Unfortunately, most existing dissemination and forwarding solutions do not consider the interest of destination nodes. Traditional dissemination methods generally use epidemic algorithms that flood the network, 16 and as a result, a lot of network resources are wasted.…”

mentioning

confidence: 99%

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Targeted content dissemination in mobile social networks taking account of resource limitation

Ravaei

Sabaei

Pedram

et al. 2017

Concurrency and Computation

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Summary Mobile social networks are presenting new opportunities for content dissemination. User location, mobility, and social communities can be used to deliver delay‐tolerant content. Most existing dissemination methods either fail to consider the user's interest in their protocol design or just allow exchange of contents between nodes that have a similar interest. If nodes with similar interest never encounter each other, then contents might not be exchanged with them. In this paper, we propose a method in which user location, mobility, and interest as well as certain limiting factors such as relay buffer size and communication overhead are used to select a set of relays for targeted advertisement distribution. Besides, our method does not depend on nodes with similar interest encountering one another. In the proposed method, a distribution agent exploits user location, mobility, and social networks as well as the interest of destinations to select a group of relays to carry content to the targeted destinations. Users move among social communities and carry advertisements to their peers in other communities. We have also developed an optimization problem for advertisement selection and scheduling. Since the problem is NP‐hard, we propose a heuristic solution. Evaluation of the proposed approach shows that the algorithm is not sensitive to network resource variation and readily outperforms popular methods reported in the literature in terms of delay, delivery ratio, and interest compatibility.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%