Epidemics and rumours in complex networks:
Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course,...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2010
|
| Schriftenreihe: | London Mathematical Society lecture note series
369 |
| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 Volltext |
| Zusammenfassung: | Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling methods, Poisson approximation (the Stein–Chen method), concentration inequalities (Chernoff bounds and Azuma–Hoeffding inequality) and branching processes. The authors examine the small-world phenomenon, preferential attachment, as well as classical epidemics. Each chapter ends with pointers to the wider literature. An ideal accompaniment for graduate courses, this book is also for researchers (statistical physicists, biologists, social scientists) who need an efficient guide to modern approaches to epidemic modelling on networks |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (vi, 123 pages) |
| ISBN: | 9780511806018 |
| DOI: | 10.1017/CBO9780511806018 |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV043941024 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 161206s2010 |||| o||u| ||||||eng d | ||
| 020 | |a 9780511806018 |c Online |9 978-0-511-80601-8 | ||
| 024 | 7 | |a 10.1017/CBO9780511806018 |2 doi | |
| 035 | |a (ZDB-20-CBO)CR9780511806018 | ||
| 035 | |a (OCoLC)967600252 | ||
| 035 | |a (DE-599)BVBBV043941024 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-12 |a DE-92 | ||
| 082 | 0 | |a 004.6 |2 22 | |
| 100 | 1 | |a Draief, Moez |d 1978- |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Epidemics and rumours in complex networks |c Moez Draief, Laurent Massoulié |
| 246 | 1 | 3 | |a Epidemics & Rumours in Complex Networks |
| 264 | 1 | |a Cambridge |b Cambridge University Press |c 2010 | |
| 300 | |a 1 online resource (vi, 123 pages) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a London Mathematical Society lecture note series |v 369 | |
| 500 | |a Title from publisher's bibliographic system (viewed on 05 Oct 2015) | ||
| 505 | 8 | 0 | |t Galton-Watson branching processes |t Reed-Frost epidemics and Erdős-Rényi random graphs |t Connectivity and Poisson approximation |t Diameter of Erdős-Rényi graphs |t From microscopic to macroscopic dynamics |t The small-world phenomenon |t Power laws via preferential attachment |t Epidemics on general graphs |t Viral marketing and optimised epidemics |
| 520 | |a Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling methods, Poisson approximation (the Stein–Chen method), concentration inequalities (Chernoff bounds and Azuma–Hoeffding inequality) and branching processes. The authors examine the small-world phenomenon, preferential attachment, as well as classical epidemics. Each chapter ends with pointers to the wider literature. An ideal accompaniment for graduate courses, this book is also for researchers (statistical physicists, biologists, social scientists) who need an efficient guide to modern approaches to epidemic modelling on networks | ||
| 650 | 4 | |a Mathematik | |
| 650 | 4 | |a Computer security / Mathematics | |
| 650 | 4 | |a Epidemics / Computer simulation | |
| 650 | 4 | |a Biologically-inspired computing | |
| 650 | 4 | |a Graph theory | |
| 650 | 4 | |a Probabilities | |
| 650 | 0 | 7 | |a Epidemiologie |0 (DE-588)4015016-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Nächste-Nachbarn-Problem |0 (DE-588)4376579-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Stochastisches Modell |0 (DE-588)4057633-4 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Epidemiologie |0 (DE-588)4015016-1 |D s |
| 689 | 0 | 1 | |a Nächste-Nachbarn-Problem |0 (DE-588)4376579-8 |D s |
| 689 | 0 | 2 | |a Stochastisches Modell |0 (DE-588)4057633-4 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 700 | 1 | |a Massoulié, Laurent |e Sonstige |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druckausgabe |z 978-0-521-51703-4 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druckausgabe |z 978-0-521-73443-1 |
| 856 | 4 | 0 | |u https://doi.org/10.1017/CBO9780511806018 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-20-CBO | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-029349993 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 966 | e | |u https://doi.org/10.1017/CBO9780511806018 |l BSB01 |p ZDB-20-CBO |q BSB_PDA_CBO |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1017/CBO9780511806018 |l FHN01 |p ZDB-20-CBO |q FHN_PDA_CBO |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804176882237702144 |
|---|---|
| any_adam_object | |
| author | Draief, Moez 1978- |
| author_facet | Draief, Moez 1978- |
| author_role | aut |
| author_sort | Draief, Moez 1978- |
| author_variant | m d md |
| building | Verbundindex |
| bvnumber | BV043941024 |
| collection | ZDB-20-CBO |
| contents | Galton-Watson branching processes Reed-Frost epidemics and Erdős-Rényi random graphs Connectivity and Poisson approximation Diameter of Erdős-Rényi graphs From microscopic to macroscopic dynamics The small-world phenomenon Power laws via preferential attachment Epidemics on general graphs Viral marketing and optimised epidemics |
| ctrlnum | (ZDB-20-CBO)CR9780511806018 (OCoLC)967600252 (DE-599)BVBBV043941024 |
| dewey-full | 004.6 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 004 - Computer science |
| dewey-raw | 004.6 |
| dewey-search | 004.6 |
| dewey-sort | 14.6 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.1017/CBO9780511806018 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03893nmm a2200601zcb4500</leader><controlfield tag="001">BV043941024</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">161206s2010 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780511806018</subfield><subfield code="c">Online</subfield><subfield code="9">978-0-511-80601-8</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1017/CBO9780511806018</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-20-CBO)CR9780511806018</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)967600252</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV043941024</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-12</subfield><subfield code="a">DE-92</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">004.6</subfield><subfield code="2">22</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Draief, Moez</subfield><subfield code="d">1978-</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Epidemics and rumours in complex networks</subfield><subfield code="c">Moez Draief, Laurent Massoulié</subfield></datafield><datafield tag="246" ind1="1" ind2="3"><subfield code="a">Epidemics & Rumours in Complex Networks</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge</subfield><subfield code="b">Cambridge University Press</subfield><subfield code="c">2010</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (vi, 123 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">London Mathematical Society lecture note series</subfield><subfield code="v">369</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Title from publisher's bibliographic system (viewed on 05 Oct 2015)</subfield></datafield><datafield tag="505" ind1="8" ind2="0"><subfield code="t">Galton-Watson branching processes</subfield><subfield code="t">Reed-Frost epidemics and Erdős-Rényi random graphs</subfield><subfield code="t">Connectivity and Poisson approximation</subfield><subfield code="t">Diameter of Erdős-Rényi graphs</subfield><subfield code="t">From microscopic to macroscopic dynamics</subfield><subfield code="t">The small-world phenomenon</subfield><subfield code="t">Power laws via preferential attachment</subfield><subfield code="t">Epidemics on general graphs</subfield><subfield code="t">Viral marketing and optimised epidemics</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling methods, Poisson approximation (the Stein–Chen method), concentration inequalities (Chernoff bounds and Azuma–Hoeffding inequality) and branching processes. The authors examine the small-world phenomenon, preferential attachment, as well as classical epidemics. Each chapter ends with pointers to the wider literature. An ideal accompaniment for graduate courses, this book is also for researchers (statistical physicists, biologists, social scientists) who need an efficient guide to modern approaches to epidemic modelling on networks</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematik</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer security / Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Epidemics / Computer simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Biologically-inspired computing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Graph theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Probabilities</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Epidemiologie</subfield><subfield code="0">(DE-588)4015016-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Nächste-Nachbarn-Problem</subfield><subfield code="0">(DE-588)4376579-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Stochastisches Modell</subfield><subfield code="0">(DE-588)4057633-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Epidemiologie</subfield><subfield code="0">(DE-588)4015016-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Nächste-Nachbarn-Problem</subfield><subfield code="0">(DE-588)4376579-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Stochastisches Modell</subfield><subfield code="0">(DE-588)4057633-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Massoulié, Laurent</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druckausgabe</subfield><subfield code="z">978-0-521-51703-4</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druckausgabe</subfield><subfield code="z">978-0-521-73443-1</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1017/CBO9780511806018</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-20-CBO</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-029349993</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/CBO9780511806018</subfield><subfield code="l">BSB01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">BSB_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/CBO9780511806018</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">FHN_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV043941024 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:14Z |
| institution | BVB |
| isbn | 9780511806018 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029349993 |
| oclc_num | 967600252 |
| open_access_boolean | |
| owner | DE-12 DE-92 |
| owner_facet | DE-12 DE-92 |
| physical | 1 online resource (vi, 123 pages) |
| psigel | ZDB-20-CBO ZDB-20-CBO BSB_PDA_CBO ZDB-20-CBO FHN_PDA_CBO |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | Cambridge University Press |
| record_format | marc |
| series2 | London Mathematical Society lecture note series |
| spelling | Draief, Moez 1978- Verfasser aut Epidemics and rumours in complex networks Moez Draief, Laurent Massoulié Epidemics & Rumours in Complex Networks Cambridge Cambridge University Press 2010 1 online resource (vi, 123 pages) txt rdacontent c rdamedia cr rdacarrier London Mathematical Society lecture note series 369 Title from publisher's bibliographic system (viewed on 05 Oct 2015) Galton-Watson branching processes Reed-Frost epidemics and Erdős-Rényi random graphs Connectivity and Poisson approximation Diameter of Erdős-Rényi graphs From microscopic to macroscopic dynamics The small-world phenomenon Power laws via preferential attachment Epidemics on general graphs Viral marketing and optimised epidemics Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling methods, Poisson approximation (the Stein–Chen method), concentration inequalities (Chernoff bounds and Azuma–Hoeffding inequality) and branching processes. The authors examine the small-world phenomenon, preferential attachment, as well as classical epidemics. Each chapter ends with pointers to the wider literature. An ideal accompaniment for graduate courses, this book is also for researchers (statistical physicists, biologists, social scientists) who need an efficient guide to modern approaches to epidemic modelling on networks Mathematik Computer security / Mathematics Epidemics / Computer simulation Biologically-inspired computing Graph theory Probabilities Epidemiologie (DE-588)4015016-1 gnd rswk-swf Nächste-Nachbarn-Problem (DE-588)4376579-8 gnd rswk-swf Stochastisches Modell (DE-588)4057633-4 gnd rswk-swf Epidemiologie (DE-588)4015016-1 s Nächste-Nachbarn-Problem (DE-588)4376579-8 s Stochastisches Modell (DE-588)4057633-4 s 1\p DE-604 Massoulié, Laurent Sonstige oth Erscheint auch als Druckausgabe 978-0-521-51703-4 Erscheint auch als Druckausgabe 978-0-521-73443-1 https://doi.org/10.1017/CBO9780511806018 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Draief, Moez 1978- Epidemics and rumours in complex networks Galton-Watson branching processes Reed-Frost epidemics and Erdős-Rényi random graphs Connectivity and Poisson approximation Diameter of Erdős-Rényi graphs From microscopic to macroscopic dynamics The small-world phenomenon Power laws via preferential attachment Epidemics on general graphs Viral marketing and optimised epidemics Mathematik Computer security / Mathematics Epidemics / Computer simulation Biologically-inspired computing Graph theory Probabilities Epidemiologie (DE-588)4015016-1 gnd Nächste-Nachbarn-Problem (DE-588)4376579-8 gnd Stochastisches Modell (DE-588)4057633-4 gnd |
| subject_GND | (DE-588)4015016-1 (DE-588)4376579-8 (DE-588)4057633-4 |
| title | Epidemics and rumours in complex networks |
| title_alt | Epidemics & Rumours in Complex Networks Galton-Watson branching processes Reed-Frost epidemics and Erdős-Rényi random graphs Connectivity and Poisson approximation Diameter of Erdős-Rényi graphs From microscopic to macroscopic dynamics The small-world phenomenon Power laws via preferential attachment Epidemics on general graphs Viral marketing and optimised epidemics |
| title_auth | Epidemics and rumours in complex networks |
| title_exact_search | Epidemics and rumours in complex networks |
| title_full | Epidemics and rumours in complex networks Moez Draief, Laurent Massoulié |
| title_fullStr | Epidemics and rumours in complex networks Moez Draief, Laurent Massoulié |
| title_full_unstemmed | Epidemics and rumours in complex networks Moez Draief, Laurent Massoulié |
| title_short | Epidemics and rumours in complex networks |
| title_sort | epidemics and rumours in complex networks |
| topic | Mathematik Computer security / Mathematics Epidemics / Computer simulation Biologically-inspired computing Graph theory Probabilities Epidemiologie (DE-588)4015016-1 gnd Nächste-Nachbarn-Problem (DE-588)4376579-8 gnd Stochastisches Modell (DE-588)4057633-4 gnd |
| topic_facet | Mathematik Computer security / Mathematics Epidemics / Computer simulation Biologically-inspired computing Graph theory Probabilities Epidemiologie Nächste-Nachbarn-Problem Stochastisches Modell |
| url | https://doi.org/10.1017/CBO9780511806018 |
| work_keys_str_mv | AT draiefmoez epidemicsandrumoursincomplexnetworks AT massoulielaurent epidemicsandrumoursincomplexnetworks AT draiefmoez epidemicsrumoursincomplexnetworks AT massoulielaurent epidemicsrumoursincomplexnetworks |