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020 _a9783031799983
_9978-3-031-79998-3
024 7 _a10.1007/978-3-031-79998-3
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aKesidis, George.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_988199
245 1 3 _aAn Introduction to Models of Online Peer-to-Peer Social Networking
_h[electronic resource] /
_cby George Kesidis.
250 _a1st ed. 2011.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2011.
300 _aXIII, 111 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Learning, Networks, and Algorithms,
_x2690-4314
505 0 _aNetworking overview -- Graphs -- Games -- Search in structured networks -- Search in unstructured networks -- Transactions, reputations, and referrals -- False Referrals -- Peer-to-peer file sharing -- Consensus in dynamical belief systems -- Byzantine consensus -- Epidemics.
520 _aThis book concerns peer-to-peer applications and mechanisms operating on the Internet, particularly those that are not fully automated and involve significant human interaction. So, the realm of interest is the intersection of distributed systems and online social networking. Generally, simple models are described to clarify the ideas. Beginning with short overviews of caching, graph theory and game theory, we cover the basic ideas of structured and unstructured search. We then describe a simple framework for reputations and for iterated referrals and consensus. This framework is applied to a problem of sybil identity management. The fundamental result for iterated Byzantine consensus for a relatively important issue is also given. Finally, a straight-forward epidemic model is used to describe the propagation of malware on-line and for BitTorrent-style file-sharing. This short book can be used as a preliminary orientation to this subject matter. References are given for the interested student to papers with good survey and tutorial content and to those with more advanced treatments of specific topics. For an instructor, this book is suitable for a one-semester seminar course. Alternatively, it could be the framework for a semester's worth of lectures where the instructor would supplement each chapter with additional lectures on related or more advanced subject matter. A basic background is required in the areas of computer networking, probability theory, stochastic processes, and queueing. Table of Contents: Networking overview / Graphs / Games / Search in structured networks / Search in unstructured networks / Transactions, reputations, and referrals / False Referrals / Peer-to-peer file sharing / Consensus in dynamical belief systems / Byzantine consensus / Epidemics.
650 0 _aArtificial intelligence.
_93407
650 0 _aCooperating objects (Computer systems).
_96195
650 0 _aProgramming languages (Electronic computers).
_97503
650 0 _aTelecommunication.
_910437
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aCyber-Physical Systems.
_932475
650 2 4 _aProgramming Language.
_939403
650 2 4 _aCommunications Engineering, Networks.
_931570
710 2 _aSpringerLink (Online service)
_988206
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031799976
776 0 8 _iPrinted edition:
_z9783031799990
830 0 _aSynthesis Lectures on Learning, Networks, and Algorithms,
_x2690-4314
_988207
856 4 0 _uhttps://doi.org/10.1007/978-3-031-79998-3
912 _aZDB-2-SXSC
942 _cEBK
999 _c86215
_d86215