On exploiting priority relation graph for reliable multi-path communication in mobile social networks

Lin, Limei; Huang, Yanze; Xiang, Yang; He, Xiangjian

doi:10.1016/j.ins.2018.10.035

Cited by 11 publications

(3 citation statements)

References 35 publications

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“…nformation and Communication Technology (ICT) has radically changed cultural and social issues by changing communication channels [1][2][3] and providing more communication paths for people. Apart from its interesting nature, ICT has provided services for the elderly which were not previously possible for them.…”

Section: Objectivesmentioning

confidence: 99%

Acceptance of Information and Communication Technology by the Elderly People Living in Tehran

Basakha

Kamal

Pashazadeh

2019

Salmand

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Section: Objectivesmentioning

confidence: 99%

Acceptance of Information and Communication Technology by the Elderly People Living in Tehran

Basakha

Kamal

Pashazadeh

2019

Salmand

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“…It has good communication performances because it can build serveral vertex disjoint paths of shorter lengths [16]. The embedding of the path or the cycle is one of the main research topics in networks because many effective algorithms for solving various graph problems have been developed on the basis of paths and cycles [17][18][19][20] and some parallel applications [21,22]. , Hamiltonian path and Hamiltonian cycle embeddings are important properties because the occurrence of congestion and deadlock can be effectively reduced or even avoided by multi-cast algorithms based on Hamiltonian paths and Hamiltonian cycles [23].…”

Section: Introductionmentioning

confidence: 99%

A Novel Conditional Connectivity and Hamiltonian Connectivity of BCube with Various Faulty Elements

Lin

You

2023

Mathematics

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BCube is one of the main data center networks because it has many attractive features. In practical applications, the failure of components or physical connections is inevitable. In data center networks in particular, switch failures are unavoidable. Fault-tolerance capability is one main aspect to measure the performance of data center networks. Connectivity, fault tolerance Hamiltonian connectivity, and fault tolerance Hamiltonicity are important parameters that assess the fault tolerance of networks. In general, the distribution of fault elements is scattered, and it is necessary to consider the distribution of fault elements in different dimensions. We research the fault tolerance of BCube when considering faulty switches and faulty links/edges that distribute in different dimensions. We also investigate the connectivity, fault tolerance Hamiltonian connectivity, and Hamiltonicity. This study better evaluates the fault-tolerant performance of data center networks.

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“…In the wake of the popularity of the cellular phone, dramatic changes have taken place in the way of communication of people's daily routine. SMS or MMS‐based (simple message service or media message service) communication is the primary way of social interaction in mobile social networks …”

Section: Introductionmentioning

confidence: 99%

Influence maximization based on activity degree in mobile social networks

Gao

Lin

et al. 2020

Concurrency and Computation

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The problem of influence maximization (IM) has become an important research topic due to the rapid growth of mobile social networks. It attempts to identify a set of nodes, referred to as influencers, contributing to the spread of maximum information.In this article, we present the construction of social relation graph based on mobile communication data. And we propose a new centrality measure-activity degree to characterize the activity of nodes. By combining the local attributes of nodes and the behavioral characteristics of nodes to measure node activity degree, which can be used to evaluate the influence of users in mobile social networks, we introduce Susceptible-Infected-Susceptible model to simulate the dynamic spreading of information. We take advantage of the two indicators the degree centrality and the betweenness centrality to get a better ranking results. In comparison with spanning graph and initial graph, the results of comparison demonstrate that our algorithm has advantages in the scope of influence propagation. K E Y W O R D Sactivity degree, influence maximization, mobile social networks, SIS model INTRODUCTIONIn the wake of the popularity of the cellular phone, dramatic changes have taken place in the way of communication of people's daily routine. SMS or MMS-based (simple message service or media message service) communication is the primary way of social interaction in mobile social networks. 1,2 Mobile social network is composed of social network 3 and mobile communication network 4,5 (see Figure 1), where individuals with similar interests chat with each other through their devices. If you think of users as nodes and connections between users through short messages as edges, then users and user connections can form one mobile social network. According to graph theory, we can scientifically understand the interaction between users and accurately identify the important people in the social network. For mobile operators, they can identify important people in the real society, conduct marketing through the influence of important people, and maximize the promotion of commercial products.The problem of user activity in a mobile social network can be abstracted into a problem on a social graph consisting purely of nodes and edges.The number and state of nodes and edges in social relationships are always in a dynamic change. The development of mobile social networks is a cascade reaction in which the growth of networks is accompanied by the addition of individual activity, which can be understood as a chain reaction.Real mobile social networks have a number of characteristics, each of which may affect individual activity.How do we quantify activity degree and what is the relationship between activity and influence? These issues are undoubtedly interesting and meaningful for the theoretical study of complex networks and the practical operation of social groups.The interaction of people in social life is called social influence. 6 Users are not only receivers of information, but also producers and di...

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On exploiting priority relation graph for reliable multi-path communication in mobile social networks

Cited by 11 publications

References 35 publications

Acceptance of Information and Communication Technology by the Elderly People Living in Tehran

Acceptance of Information and Communication Technology by the Elderly People Living in Tehran

A Novel Conditional Connectivity and Hamiltonian Connectivity of BCube with Various Faulty Elements

Influence maximization based on activity degree in mobile social networks

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