Uncertain multicast under dynamic behaviors

Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas...
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Autor*in:	Qin, Yudong [verfasserIn] Guo, Deke [verfasserIn] Hu, Zhiyao [verfasserIn] Ren, Bangbang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	uncertain multicast dynamic behaviors routing forest approximation algorithm Steiner tree

Übergeordnetes Werk:	Enthalten in: Frontiers of computer science in China - Beijing : Higher Education Press, 2007, 14(2018), 1 vom: 06. Sept., Seite 130-145
Übergeordnetes Werk:	volume:14 ; year:2018 ; number:1 ; day:06 ; month:09 ; pages:130-145

Links:	Volltext

DOI / URN:	10.1007/s11704-018-7429-x

Katalog-ID:	SPR021943044

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520			\|a Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. The comprehensive evaluation results demonstrate that our methods can well tackle the proposed DMCF problem.
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700	1		\|a Ren, Bangbang \|e verfasserin \|4 aut
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allfields	10.1007/s11704-018-7429-x doi (DE-627)SPR021943044 (SPR)s11704-018-7429-x-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Qin, Yudong verfasserin aut Uncertain multicast under dynamic behaviors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. The comprehensive evaluation results demonstrate that our methods can well tackle the proposed DMCF problem. uncertain multicast (dpeaa)DE-He213 dynamic behaviors (dpeaa)DE-He213 routing forest (dpeaa)DE-He213 approximation algorithm (dpeaa)DE-He213 Steiner tree (dpeaa)DE-He213 Guo, Deke verfasserin aut Hu, Zhiyao verfasserin aut Ren, Bangbang verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 14(2018), 1 vom: 06. Sept., Seite 130-145 (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:14 year:2018 number:1 day:06 month:09 pages:130-145 https://dx.doi.org/10.1007/s11704-018-7429-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2005 54.00 ASE AR 14 2018 1 06 09 130-145
spelling	10.1007/s11704-018-7429-x doi (DE-627)SPR021943044 (SPR)s11704-018-7429-x-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Qin, Yudong verfasserin aut Uncertain multicast under dynamic behaviors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. The comprehensive evaluation results demonstrate that our methods can well tackle the proposed DMCF problem. uncertain multicast (dpeaa)DE-He213 dynamic behaviors (dpeaa)DE-He213 routing forest (dpeaa)DE-He213 approximation algorithm (dpeaa)DE-He213 Steiner tree (dpeaa)DE-He213 Guo, Deke verfasserin aut Hu, Zhiyao verfasserin aut Ren, Bangbang verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 14(2018), 1 vom: 06. Sept., Seite 130-145 (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:14 year:2018 number:1 day:06 month:09 pages:130-145 https://dx.doi.org/10.1007/s11704-018-7429-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2005 54.00 ASE AR 14 2018 1 06 09 130-145
allfields_unstemmed	10.1007/s11704-018-7429-x doi (DE-627)SPR021943044 (SPR)s11704-018-7429-x-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Qin, Yudong verfasserin aut Uncertain multicast under dynamic behaviors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. The comprehensive evaluation results demonstrate that our methods can well tackle the proposed DMCF problem. uncertain multicast (dpeaa)DE-He213 dynamic behaviors (dpeaa)DE-He213 routing forest (dpeaa)DE-He213 approximation algorithm (dpeaa)DE-He213 Steiner tree (dpeaa)DE-He213 Guo, Deke verfasserin aut Hu, Zhiyao verfasserin aut Ren, Bangbang verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 14(2018), 1 vom: 06. Sept., Seite 130-145 (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:14 year:2018 number:1 day:06 month:09 pages:130-145 https://dx.doi.org/10.1007/s11704-018-7429-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2005 54.00 ASE AR 14 2018 1 06 09 130-145
allfieldsGer	10.1007/s11704-018-7429-x doi (DE-627)SPR021943044 (SPR)s11704-018-7429-x-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Qin, Yudong verfasserin aut Uncertain multicast under dynamic behaviors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. The comprehensive evaluation results demonstrate that our methods can well tackle the proposed DMCF problem. uncertain multicast (dpeaa)DE-He213 dynamic behaviors (dpeaa)DE-He213 routing forest (dpeaa)DE-He213 approximation algorithm (dpeaa)DE-He213 Steiner tree (dpeaa)DE-He213 Guo, Deke verfasserin aut Hu, Zhiyao verfasserin aut Ren, Bangbang verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 14(2018), 1 vom: 06. Sept., Seite 130-145 (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:14 year:2018 number:1 day:06 month:09 pages:130-145 https://dx.doi.org/10.1007/s11704-018-7429-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2005 54.00 ASE AR 14 2018 1 06 09 130-145
allfieldsSound	10.1007/s11704-018-7429-x doi (DE-627)SPR021943044 (SPR)s11704-018-7429-x-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Qin, Yudong verfasserin aut Uncertain multicast under dynamic behaviors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. The comprehensive evaluation results demonstrate that our methods can well tackle the proposed DMCF problem. uncertain multicast (dpeaa)DE-He213 dynamic behaviors (dpeaa)DE-He213 routing forest (dpeaa)DE-He213 approximation algorithm (dpeaa)DE-He213 Steiner tree (dpeaa)DE-He213 Guo, Deke verfasserin aut Hu, Zhiyao verfasserin aut Ren, Bangbang verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 14(2018), 1 vom: 06. Sept., Seite 130-145 (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:14 year:2018 number:1 day:06 month:09 pages:130-145 https://dx.doi.org/10.1007/s11704-018-7429-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2005 54.00 ASE AR 14 2018 1 06 09 130-145
language	English
source	Enthalten in Frontiers of computer science in China 14(2018), 1 vom: 06. Sept., Seite 130-145 volume:14 year:2018 number:1 day:06 month:09 pages:130-145
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topic_facet	uncertain multicast dynamic behaviors routing forest approximation algorithm Steiner tree
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container_title	Frontiers of computer science in China
authorswithroles_txt_mv	Qin, Yudong @@aut@@ Guo, Deke @@aut@@ Hu, Zhiyao @@aut@@ Ren, Bangbang @@aut@@
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Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. 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author	Qin, Yudong
spellingShingle	Qin, Yudong ddc 004 bkl 54.00 misc uncertain multicast misc dynamic behaviors misc routing forest misc approximation algorithm misc Steiner tree Uncertain multicast under dynamic behaviors
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topic_title	004 ASE 54.00 bkl Uncertain multicast under dynamic behaviors uncertain multicast (dpeaa)DE-He213 dynamic behaviors (dpeaa)DE-He213 routing forest (dpeaa)DE-He213 approximation algorithm (dpeaa)DE-He213 Steiner tree (dpeaa)DE-He213
topic	ddc 004 bkl 54.00 misc uncertain multicast misc dynamic behaviors misc routing forest misc approximation algorithm misc Steiner tree
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title	Uncertain multicast under dynamic behaviors
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title_full	Uncertain multicast under dynamic behaviors
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title_sort	uncertain multicast under dynamic behaviors
title_auth	Uncertain multicast under dynamic behaviors
abstract	Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. The comprehensive evaluation results demonstrate that our methods can well tackle the proposed DMCF problem.
abstractGer	Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. The comprehensive evaluation results demonstrate that our methods can well tackle the proposed DMCF problem.
abstract_unstemmed	Abstract Multicast transfer can efficiently save the bandwidth consumption and reduce the load on the source node than a series of independent unicast transfers. Nowadays, many applications employ the content replica strategy to improve the robustness and efficiency; hence each file and its replicas are usually distributed among multiple sources. In such scenarios, the traditional deterministic multicast develops into the Uncertain multicast, which has more flexibility in the source selection. In this paper, we focus on building and maintaining a minimal cost forest (MCF) for any uncertain multicast, whose group members (source nodes and destination nodes) may join or leave after constructing a MCF. We formulate this dynamic minimal cost forest (DMCF) problem as a mixed integer programming model. We then design three dedicated methods to approximate the optimal solution. Among them, our a-MCF aims to efficiently construct an MCF for any given uncertain multicast, without dynamic behaviors of multicast group members. The d-MCF method motivates to slightly update the existing MCF via local modifications once appearing a dynamic behavior. It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. The comprehensive evaluation results demonstrate that our methods can well tackle the proposed DMCF problem.
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title_short	Uncertain multicast under dynamic behaviors
url	https://dx.doi.org/10.1007/s11704-018-7429-x
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up_date	2024-07-04T01:07:18.562Z
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It can achieve the balance between the minimal cost and the minimal modifications to the existing forest. The last r-MCF is a supplement method to the d-MCF method, since many rounds of local modifications may make the resultant forest far away from the optimal forest. Accordingly, our r-MCF method monitors the accumulated degradation and triggers the rearrangement process to reconstruct an new MCF when necessary. 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