LEADER 04189nam 22006855 450 001 9910437598603321 005 20200630053521.0 010 $a1-283-62466-4 010 $a9786613937117 010 $a1-4614-4918-9 024 7 $a10.1007/978-1-4614-4918-8 035 $a(CKB)2670000000246060 035 $a(EBL)1030910 035 $a(OCoLC)810143415 035 $a(SSID)ssj0000739333 035 $a(PQKBManifestationID)11416820 035 $a(PQKBTitleCode)TC0000739333 035 $a(PQKBWorkID)10687066 035 $a(PQKB)11184471 035 $a(DE-He213)978-1-4614-4918-8 035 $a(MiAaPQ)EBC1030910 035 $a(PPN)168301547 035 $a(EXLCZ)992670000000246060 100 $a20120904d2013 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSpatio-temporal Networks $eModeling and Algorithms /$fby Betsy George, Sangho Kim 205 $a1st ed. 2013. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2013. 215 $a1 online resource (82 p.) 225 1 $aSpringerBriefs in Computer Science,$x2191-5768 300 $aDescription based upon print version of record. 311 $a1-4614-4917-0 320 $aIncludes bibliographical references. 327 $aSpatio-temporal Networks: An Introduction -- Time Aggregated Graph - A model for Spatio-temporal Networks -- Shortest Path Algorithms for a Fixed Start Time -- Best Start Time Journeys -- Spatio-temporal Network Applications. 330 $aSpatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time. These are encountered in many critical areas of everyday life such as transportation networks, electric power distribution grids, and social networks of mobile users. STN modeling and computations raise significant challenges. The model must meet the conflicting requirements of simplicity and adequate support for efficient algorithms. Another challenge is to address the change in the semantics of common graph operations, such as, shortest path computation assuming different semantics, or when temporal dimension is added. Also paradigms (e.g. dynamic programming) used in algorithm design may be ineffective since their assumptions (e.g. stationary ranking of candidates) may be violated by the dynamic nature of STNs. In recent years, STNs have attracted attention in research. New representations have been proposed along with algorithms to perform key STN operations, while accounting for their time dependence. Designing a STN database would require the development of data models, query languages, and indexing methods to efficiently represent, query, store, and manage time-variant properties of the network. The purpose of Spatio-temporal Networks: Modeling and Algorithms is to explore this design at the conceptual, logical, and physical level. Models used to represent STNs are explored and analyzed. STN operations, with an emphasis on their altered semantics with the addition of temporal dimension, are also addressed. 410 0$aSpringerBriefs in Computer Science,$x2191-5768 606 $aDatabase management 606 $aGeographical information systems 606 $aGraph theory 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aGeographical Information Systems/Cartography$3https://scigraph.springernature.com/ontologies/product-market-codes/J13000 606 $aGraph Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/M29020 615 0$aDatabase management. 615 0$aGeographical information systems. 615 0$aGraph theory. 615 14$aDatabase Management. 615 24$aGeographical Information Systems/Cartography. 615 24$aGraph Theory. 676 $a005.74 676 $a511.3 700 $aGeorge$b Betsy$4aut$4http://id.loc.gov/vocabulary/relators/aut$01064187 702 $aKim$b Sangho$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910437598603321 996 $aSpatio-temporal Networks$92536729 997 $aUNINA