2015
DOI: 10.1016/j.jnca.2015.02.001
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Information centric network: Research challenges and opportunities

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Cited by 209 publications
(78 citation statements)
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References 35 publications
(43 reference statements)
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“…The authors further extracted the network traffic characteristic and unleashed the power of packet schedulers with fine-grained balancing method. Compared to CRC and other hash functions, highest random weight (HRW) hashing stands out due to the characteristics like theoreticallyproven good data locality, flow-level load balancing, minimal disruption and low overhead [10], [17]- [19]. Kuang et al [10] proposed E-AHRW, which was based on the adaptive HRW schemes.…”
Section: Related Workmentioning
confidence: 99%
“…The authors further extracted the network traffic characteristic and unleashed the power of packet schedulers with fine-grained balancing method. Compared to CRC and other hash functions, highest random weight (HRW) hashing stands out due to the characteristics like theoreticallyproven good data locality, flow-level load balancing, minimal disruption and low overhead [10], [17]- [19]. Kuang et al [10] proposed E-AHRW, which was based on the adaptive HRW schemes.…”
Section: Related Workmentioning
confidence: 99%
“…ICN mainly has two naming structures: the hierarchical naming and the flat names [17] . The ICN names are human readable not like the IP address and are used for identifying and routing the requests.…”
Section: Namingmentioning
confidence: 99%
“…Many algorithms are based on green technology assumptions for ad hoc networks [22,23]. Other works are based on multilayer clusters [24], routing quality games [25], spatial reusability [26], and other solutions can be found in [27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44], and complex surveys in works [45,46].…”
Section: State Of the Artmentioning
confidence: 99%