Hotspot-entropy based data forwarding in opportunistic social networks
Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yuan, Peiyan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015transfer abstract |
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| Schlagwörter: |
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| Umfang: |
19 |
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| Übergeordnetes Werk: |
Enthalten in: BIG-OH: BInarization of gradient orientation histograms - Baber, Junaid ELSEVIER, 2014transfer abstract, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:16 ; year:2015 ; pages:136-154 ; extent:19 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.pmcj.2014.06.003 |
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ELV039682900 |
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| 520 | |a Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. | ||
| 520 | |a Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. | ||
| 650 | 7 | |a Opportunistic social networks |2 Elsevier | |
| 650 | 7 | |a Hotspot |2 Elsevier | |
| 650 | 7 | |a Information entropy |2 Elsevier | |
| 650 | 7 | |a Data forwarding |2 Elsevier | |
| 700 | 1 | |a Ma, Huadong |4 oth | |
| 700 | 1 | |a Fu, Huiyuan |4 oth | |
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10.1016/j.pmcj.2014.06.003 doi GBVA2015007000013.pica (DE-627)ELV039682900 (ELSEVIER)S1574-1192(14)00091-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Yuan, Peiyan verfasserin aut Hotspot-entropy based data forwarding in opportunistic social networks 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Opportunistic social networks Elsevier Hotspot Elsevier Information entropy Elsevier Data forwarding Elsevier Ma, Huadong oth Fu, Huiyuan oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:16 year:2015 pages:136-154 extent:19 https://doi.org/10.1016/j.pmcj.2014.06.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 16 2015 136-154 19 045F 004 |
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10.1016/j.pmcj.2014.06.003 doi GBVA2015007000013.pica (DE-627)ELV039682900 (ELSEVIER)S1574-1192(14)00091-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Yuan, Peiyan verfasserin aut Hotspot-entropy based data forwarding in opportunistic social networks 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Opportunistic social networks Elsevier Hotspot Elsevier Information entropy Elsevier Data forwarding Elsevier Ma, Huadong oth Fu, Huiyuan oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:16 year:2015 pages:136-154 extent:19 https://doi.org/10.1016/j.pmcj.2014.06.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 16 2015 136-154 19 045F 004 |
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10.1016/j.pmcj.2014.06.003 doi GBVA2015007000013.pica (DE-627)ELV039682900 (ELSEVIER)S1574-1192(14)00091-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Yuan, Peiyan verfasserin aut Hotspot-entropy based data forwarding in opportunistic social networks 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Opportunistic social networks Elsevier Hotspot Elsevier Information entropy Elsevier Data forwarding Elsevier Ma, Huadong oth Fu, Huiyuan oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:16 year:2015 pages:136-154 extent:19 https://doi.org/10.1016/j.pmcj.2014.06.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 16 2015 136-154 19 045F 004 |
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10.1016/j.pmcj.2014.06.003 doi GBVA2015007000013.pica (DE-627)ELV039682900 (ELSEVIER)S1574-1192(14)00091-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Yuan, Peiyan verfasserin aut Hotspot-entropy based data forwarding in opportunistic social networks 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Opportunistic social networks Elsevier Hotspot Elsevier Information entropy Elsevier Data forwarding Elsevier Ma, Huadong oth Fu, Huiyuan oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:16 year:2015 pages:136-154 extent:19 https://doi.org/10.1016/j.pmcj.2014.06.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 16 2015 136-154 19 045F 004 |
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10.1016/j.pmcj.2014.06.003 doi GBVA2015007000013.pica (DE-627)ELV039682900 (ELSEVIER)S1574-1192(14)00091-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Yuan, Peiyan verfasserin aut Hotspot-entropy based data forwarding in opportunistic social networks 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. Opportunistic social networks Elsevier Hotspot Elsevier Information entropy Elsevier Data forwarding Elsevier Ma, Huadong oth Fu, Huiyuan oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:16 year:2015 pages:136-154 extent:19 https://doi.org/10.1016/j.pmcj.2014.06.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 16 2015 136-154 19 045F 004 |
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Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. |
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Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. |
| abstract_unstemmed |
Performance of data forwarding in opportunistic social networks benefits considerably if one can make use of human mobility in terms of social contexts. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions of traditional social networks analysis, this is mainly because of the transient node contact and the intermittently connected link. In this paper, we are interested in the following question: Can we exploit some other stable social attributes to quantify the centrality and similarity of nodes? Aggregating GPS traces of human walks from the real world, we find that there exist two types of phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we propose Hotent (HOTspot-ENTropy), a novel data forwarding metric to improve the performance of opportunistic routing. First, we use the relative entropy between the public hotspots and the personal hotspots to compute node centrality. Second, we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to evaluate their similarity. Third, we integrate the two social metrics by using the law of universal gravitation. Besides, we use the entropy of personal hotspots of a node to characterize its personality. Finally, we compare our routing strategy with the state-of-the-art works through extensive trace-driven simulations, the results show that Hotent largely outperforms other solutions, especially in terms of packet delivery ratio and the average number of hops per message. |
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