Immunity-Based Epidemic Routing in Intermittent Networks

Mundur, Padma; Seligman, Matthew; Lee, Jin Na

doi:10.1109/sahcn.2008.86

Cited by 11 publications

(6 citation statements)

References 1 publication

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“…Authors introduce the idea of immunity to improve the basic Epidemic Routing strategy in [48]. Each node maintains a list of delivered messages, called the immunity list.…”

Section: Nonknowledge-based Routing Protocolsmentioning

confidence: 99%

Study on Routing Protocols for Delay Tolerant Mobile Networks

Gong

2013

International Journal of Distributed Sensor Networks

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Delay tolerant mobile networks feature with intermittent connectivity, huge transmission delay, nodal mobility, and so forth. ere is usually no end-to-end path in the networks and it poses great challenges for routing in DTMNs. In this paper, the architecture of DTMNs is introduced at �rst, including the characteristics of DTMNs, routing challenges, and metric and mobility models. And then, the state-of-the-art routing protocols for DTMNs are discussed and analyzed. Routing strategies are classi�ed into three categories: nonknowledge-based approach, knowledge-based approach, and social-based approach. Finally, some research issues about DTMNs are presented.

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“…Authors introduce the idea of immunity to improve the basic Epidemic Routing strategy in [48]. Each node maintains a list of delivered messages, called the immunity list.…”

Section: Nonknowledge-based Routing Protocolsmentioning

confidence: 99%

Study on Routing Protocols for Delay Tolerant Mobile Networks

Gong

2013

International Journal of Distributed Sensor Networks

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“…Moreover, the use of anti-packets, which are usually small in size, reduce the number of bundles that are exchanged in each encounter. Example protocols that employ this optimization include epidemic with immunity [12] and P-Q epidemic [10]. In epidemic with immunity [12], nodes deliver and drop bundles according to two lists: m-list and i-list.…”

Section: B Optimizationsmentioning

confidence: 99%

“…Example protocols that employ this optimization include epidemic with immunity [12] and P-Q epidemic [10]. In epidemic with immunity [12], nodes deliver and drop bundles according to two lists: m-list and i-list. The m-list is similar to the summary bundles vector in pure epidemic, which records received bundles.…”

Section: B Optimizationsmentioning

confidence: 99%

A Unified Study of Epidemic Routing Protocols and their Enhancements

Feng

Chin

2012

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops &Amp; PhD Forum

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Abstract-Epidemic protocols belong to a class of routing paradigm that have wide ranging applications in Delay TolerantNetworks (DTNs) due to their simplicity, low delays, and little to no reliance on special nodes. To this end, a comprehensive study of their performance will serve as an important guide to future protocol designers. Unfortunately, to date, there is no work that studies epidemic routing protocols using a common framework that evaluates their performance objectively using the same mobility model and parameters. To this end, we study four categories of epidemic routing protocols. Namely, P-Q epidemic, epidemic with Time-To-Live (TTL), epidemic with Encounter Count (EC) and epidemic with immunity table. Our results show that the probability of transmissions as used in P-Q epidemic may increase delay and decrease delivery ratio. Apart from that, an incorrect TTL value leads to premature discarding of bundles, and thereby, has a non negligible impact on delivery ratio. Epidemic with EC suffers from high buffer occupancy levels and long delivery delays. In addition, epidemic with immunity suffers from high overheads. Henceforth, we propose three enhancements: dynamic TTL, EC+TTL and cumulative immunity to address the aforementioned limitations. Our results show that dynamic TTL improves delivery ratio by more than 20%, EC+TTL reduces buffer occupancy level by 40%, and improve delivery ratio by at least 40% at high loads. Cumulative immunity reduces the buffer occupancy level of nodes by at least 15% whilst incuring an order of magnitude less signaling overheads.

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“…e main drawback of the Epidemic scheme is its high overhead. Many schemes are proposed to decrease the overhead in Epidemic-based approaches by limiting the number of message replicas [14][15][16]. An effective scheme to control replication spread is the vaccine [17].…”

Section: Introductionmentioning

confidence: 99%

EpSoc: Social-Based Epidemic-Based Routing Protocol in Opportunistic Mobile Social Network

Lenando

Alrfaay

2018

Mobile Information Systems

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In opportunistic networks, the nature of intermittent and disruptive connections degrades the efficiency of routing. Epidemic routing protocol is used as a benchmark for most of routing protocols in opportunistic mobile social networks (OMSNs) due to its high message delivery and latency. However, Epidemic incurs high cost in terms of overhead and hop count. In this paper, we propose a hybrid routing protocol called EpSoc which utilizes the Epidemic routing forwarding strategy and exploits an important social feature, that is, degree centrality. Two techniques are used in EpSoc. Messages’ TTL is adjusted based on the degree centrality of nodes, and the message blocking mechanism is used to control replication. Simulation results show that EpSoc increases the delivery ratio and decreases the overhead ratio, the average latency, and the hop counts as compared to Epidemic and Bubble Rap.

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Immunity-Based Epidemic Routing in Intermittent Networks

Cited by 11 publications

References 1 publication

Study on Routing Protocols for Delay Tolerant Mobile Networks

Study on Routing Protocols for Delay Tolerant Mobile Networks

A Unified Study of Epidemic Routing Protocols and their Enhancements

EpSoc: Social-Based Epidemic-Based Routing Protocol in Opportunistic Mobile Social Network

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