Opportunistic Networking: Congestion, Transfer Ordering and Resilience

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Fältnamn	Indikatorer	Metadata
000		03970nam a2200445 4500
001		oai:DiVA.org:uu-223492
003		SwePub
008		140422s2014 \| \|\|\|\|\|\|\|\|\|\|\|000 \|\|eng\|
020		a 9789155489533q print
024	7	a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-2234922 URI
040		a (SwePub)uu
041		a engb eng
042		9 SwePub
072	7	a vet2 swepub-contenttype
072	7	a dok2 swepub-publicationtype
100	1	a Bjurefors, Fredrik,d 1978-u Uppsala universitet,Avdelningen för datorteknik,Datorteknik,Communication Research4 aut0 (Swepub:uu)frebj730
245	1 0	a Opportunistic Networking :b Congestion, Transfer Ordering and Resilience
264	1	a Uppsala :b Acta Universitatis Upsaliensis,c 2014
300		a 45 s.
338		a electronic2 rdacarrier
520		a Opportunistic networks are constructed by devices carried by people and vehicles. The devices use short range radio to communicate. Since the network is mobile and often sparse in terms of node contacts, nodes store messages in their buffers, carrying them, and forwarding them upon node encounters. This form of communication leads to a set of challenging issues that we investigate: congestion, transfer ordering, and resilience.Congestion occurs in opportunistic networks when a node's buffers becomes full. To be able to receive new messages, old messages have to be evicted. We show that buffer eviction strategies based on replication statistics perform better than strategies that evict messages based on the content of the message.We show that transfer ordering has a significant impact on the dissemination of messages during time limited contacts. We find that transfer strategies satisfying global requests yield a higher delivery ratio but a longer delay for the most requested data compared to satisfying the neighboring node's requests.Finally, we assess the resilience of opportunistic networks by simulating different types of attacks. Instead of enumerating all possible attack combinations, which would lead to exhaustive evaluations, we introduce a method that use heuristics to approximate the extreme outcomes an attack can have. The method yields a lower and upper bound for the evaluated metric over the different realizations of the attack. We show that some types of attacks are harder to predict the outcome of and other attacks may vary in the impact of the attack due to the properties of the attack, the forwarding protocol, and the mobility pattern.
650	7	a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe
650	7	a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng
650	7	a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Kommunikationssystem0 (SwePub)202032 hsv//swe
650	7	a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Communication Systems0 (SwePub)202032 hsv//eng
653		a Opportunistic Networking
653		a Congestion
653		a Transfer Ordering
653		a Resilience
653		a Testbed
653		a WISENET
653		a Datavetenskap med inriktning mot datorkommunikation
653		a Computer Science with specialization in Computer Communication
700	1	a Gunningberg, Per,c Professoru Uppsala universitet,Avdelningen för datorteknik4 ths0 (Swepub:uu)pergunn
700	1	a Rohner, Christian,c Docentu Uppsala universitet,Avdelningen för datorteknik4 ths0 (Swepub:uu)chroh499
700	1	a Gerla, Mario,c Professoru UCLA, Computer Science Department4 opn
710	2	a Uppsala universitetb Avdelningen för datorteknik4 org
856	4	u https://uu.diva-portal.org/smash/get/diva2:713179/FULLTEXT01.pdfx primaryx Raw objecty fulltext
856	4	u https://uu.diva-portal.org/smash/get/diva2:713179/PREVIEW01.jpgx Previewy preview image
856	4 8	u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-223492

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Av författaren/redakt...: Bjurefors, Fredr ...; Gunningberg, Per ...; Rohner, Christia ...; Gerla, Mario, Pr ...

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TEKNIK OCH TEKNOLOGIER: TEKNIK OCH TEKNO ...; och Elektroteknik oc ...; och Kommunikationssy ...

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