An adaptive routing algorithm considering position and social similarities in an opportunistic network

Jang, Kyungsoo; Lee, Junyeop; Kim, Sun-Kyum; Yoon, Ji-Hyeun; Yang, Seung Choul

doi:10.1007/s11276-015-1048-3

Cited by 21 publications

(18 citation statements)

References 42 publications

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“…The movement of a node from a community to the next community consists of selection of the speed uniformly at random over [ v min , v max ] . Various flavors of HCMM (such as CMM, HCMM, and HCMM‐SO) are widely used to evaluate forwarding and dissemination methods in the literatures …”

Section: Discussionmentioning

confidence: 99%

“…43 Various flavors of HCMM (such as CMM, 64 HCMM, 43 and HCMM-SO 61 ) are widely used to evaluate forwarding and dissemination methods in the literatures. 7,34,62,63,[65][66][67][68][69][70][71][72] The number of communities in HCMM-SO simulation scenarios is randomly selected. Distribution of the number of communities for a scenario with 100 nodes is expressed by the following formula and depicted in Figure 4, which follows the normal distribution with mean 39.641 and variance 6.95532:…”

Section: Simulation Scenariosmentioning

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: Discussionmentioning

confidence: 99%

Section: Simulation Scenariosmentioning

confidence: 99%

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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show abstract

“…In recent years, research around the routing algorithm [8,[11][12][13][14] has been a hot issue in opportunistic social networks, where different methods suitable for different application scenarios have been proposed. In opportunistic social networks, routing algorithms can be roughly divided into two categories: context-aware algorithms, and context-ignorant algorithms.…”

Section: Related Workmentioning

confidence: 99%

“…In opportunistic networks, nodes in unpredictable locations attempt to communicate with each other at unpredictable intervals. Nowadays, the application areas of opportunistic networks mainly include wildlife monitoring networks [5], interplanetary networks [6,7], vehicular networks [8], networks in underdeveloped areas [9,10], and social opportunistic networks [11][12][13][14]. At the dawn of 5G networks and big data, technological development is leading to the wide distribution of mobile devices, such as smartphones, Bluetooth, Wi-Fi technologies, or notebooks.…”

Section: Introductionmentioning

confidence: 99%

“…However, when evaluating the similarity degree between a pair of nodes, few algorithms [10,12] synthetically consider multiple similarity factors, and mobile similarity is even disregarded. While transmission mechanisms accurately assess the similarity degree between nodes, the biggest difficulty is how to comprehensively evaluate the different effects of each similarity factor and highlight the importance of moving user trajectories in data transmission.…”

Section: Introductionmentioning

confidence: 99%

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FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks

Liu

Chen

et al. 2018

Symmetry

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At the dawn of big data and 5G networks, end-to-end communication with large amounts of data between mobile devices is difficult to be implemented through the traditional face-to-face transmission mechanism in social networks. Consequently, opportunistic social networks proposed that message applications should choose proper relay nodes to perform effective data transmission processes. At present, several routing algorithms, based on node similarity, attempt to use the contextual information related to nodes and the special relationships between them to select a suitable relay node among neighbors. However, when evaluating the similarity degree between a pair of nodes, most existing algorithms in opportunistic social networks pay attention to only a few similar factors, and even ignore the importance of mobile similarity in the data transmission process. To improve the transmission environment, this study establishes a fuzzy routing-forwarding algorithm (FCNS) exploiting comprehensive node similarity (the mobile and social similarities) in opportunistic social networks. In our proposed scheme, the transmission preference of the node is determined through the fuzzy evaluation of mobile and social similarities. The suitable message delivery decision is made by collecting and comparing the transmission preference of nodes, and the sustainable and stable data transmission process is performed through the feedback mechanism. Through simulations and the comparison of social network algorithms, the delivery ratio in the proposed algorithm is 0.85 on average, and the routing delay and network overhead of this algorithm are always the lowest.

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A Routing Algorithm Based on Node Utility and Energy in Opportunistic Networks

Yuan

Huang

2022

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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An adaptive routing algorithm considering position and social similarities in an opportunistic network

Cited by 21 publications

References 42 publications

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

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

FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks

A Routing Algorithm Based on Node Utility and Energy in Opportunistic Networks

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