Performance analysis of mobility-assisted routing
By Thrasyvoulos Spyropoulos, Konstantinos Psounis, Cauligi S. Raghavendra. ACM Interational Symposium on Mobile Ad Hoc Networking and Computing, 2006
335 citations recorded by the source corpus.
Subfields: Computer Networks and Communications
View Paper: https://www.semanticscholar.org/paper/bf729d5b4d1a98c253f07cf055e7ee148dd0d31f
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In Computer Networks and Communications
- Konstantinos Psounis
- Thrasyvoulos Spyropoulos
- Cauligi S. Raghavendra
- Zhili Sun
- Arun Venkataramani
- Aruna Devi Balasubramanian
- Brian Neil Levine
- Guohong Cao
Citations in the corpus
- Spray and Focus: Efficient Mobility-Assisted Routing for Heterogeneous and Correlated Mobility (2007, methodology): “For this reason, we would also like to compare the performance of all protocols under a more realistic mobility model, called “Community-based Mobility Model”, that is motivated by such traces and better resembles real node movement [30].”
- Efficient Routing in Intermittently Connected Mobile Networks: The Multiple-Copy Case (2008, methodology): “these [42] exhibit such (approximately) exponential encounter characteristics.”
- Modeling Time-Variant User Mobility in Wireless Mobile Networks (2007, methodology): “Since random direction movement covers the whole simulation area with equal probability [ 16 ], and the target coordinate is chosen at random, it falls in this newly covered area with probability 2Kvr=N2, and hence the unit-”
- DTN routing as a resource allocation problem (2007, background): “Some theoretical works [37, 32, 30] derive closed-form expressions for average delay and number of replicas in the system as a function of the number of nodes and mobility patterns.”
- A parsimonious model of mobile partitioned networks with clustering (2009, background): “in [26], and further extended in [11], is designed to recreate the characteristics of mobility in sparse networks.”
- Multicasting in delay tolerant networks: a social network perspective (2009, methodology): “Since social relations among mobile users are more likely to be long-term characteristics and less volatile than node mobility, social-based forwarding schemes outperform traditional approaches based on oblivious heuristics [22] or mobility-based predictions [13, 25, 20].”