Augmented DTN based energy efficient routing protocol for vehicular ad hoc networks

Paramasivan, B.; Bhuvaneswari, M.; Pitchai, K. Mohaideen

doi:10.1109/icsens.2015.7370257

Cited by 13 publications

(13 citation statements)

References 11 publications

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“…The probability of two nodes meeting at least once between before the time t can be expressed as P(W 1 t) = P(X t ≥ 1) = 1 − P(X t < 1) = 1 − e −λt calculated by formula (27). The result is the same as that calculated by formula (24). According to formula (27), the probability function of the Irish distribution is shown in formula 28:…”

Section: Analysis Of Waiting Time Probabilitymentioning

confidence: 87%

“…We can see that the probability of meeting n times between nodes for a period of time T is more reflected the dynamic changes of the network over time than the probability of meeting at least once through formula (24). Thus, we choose that nodes meet n times instead of at least one time to evaluate the possibility of the meeting between the nodes within a period of time T .…”

Section: Deductionmentioning

confidence: 99%

“…Routing protocols [21,22,23] are inclined to restrict the number of copies to select relay nodes according to the historical information of node encounter. Energy Efficient Routing Protocol for Vehicular Ad hoc Networks (ADTNEER) [24] uses geographical angular region based routing to choose most suitable next hop thereby achieving proper network connectivity among nodes with minimum energy consumption. [25] considers nodes' remaining energy and available free buffer for receiving copies of messages to reduce network overhead and at the same time improve delivery ratio.…”

Section: Introductionmentioning

confidence: 99%

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Opportunistic protocol based on social probability and resources efficiency for the intelligent and connected transportation system

et al. 2019

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Section: Analysis Of Waiting Time Probabilitymentioning

confidence: 87%

Section: Deductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Opportunistic protocol based on social probability and resources efficiency for the intelligent and connected transportation system

et al. 2019

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“…A modification to the traditional TCP/IP networking architecture is proposed in [169] to suite vehicular DTNs, where: (i) the bundle layer was added above the MAC and below the networking layer (instead of being above the transport layer as in [173]), to aggregate and de-aggregate traffic faster in a DTN setup instead of using small IP packets, and (ii) the data and control plane are separated. In [174], multihop transmissions in vehicular DTNs were investigated. An efficient approach to transmit the data to other vehicles going in the same direction to speed up delivery is proposed.…”

Section: E Delay Tolerant Network (Dtns)mentioning

confidence: 99%

A Key 6G Challenge and Opportunity—Connecting the Base of the Pyramid: A Survey on Rural Connectivity

2020

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Providing connectivity to around half of the world population living in rural or underprivileged areas is a tremendous challenge, but also a unique opportunity. Access to the internet would provide the population living in these areas a possibility to progress on the educational, health, environment, and business levels. In this paper, a survey of technologies for providing connectivity to rural areas, and that can help address this challenge, is provided. Although access/fronthaul and backhaul techniques are discussed in the paper, it is noted that the major limitation for providing connectivity to rural and underprivileged areas is the cost of backhaul deployment. In addition, energy requirements and cost efficiency of the studied technologies are analyzed. In fact, the challenges faced for deploying an electricity network, as a prerequisite for deploying communication networks, are huge in these areas and they are granted an important share of the discussions in this paper. Furthermore, typical application scenarios in rural areas are discussed, and several country-specific use cases are surveyed. The main

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“…It is not concentrated on optimal resource allocation. Paramasivan et al [18] introduced a VANET routing protocol by combining link state information, connection lifetime prediction and store-stay-spray mechanism. It uses geographical-angular-region-based routing to choose the most suitable next hop for PF.…”

Section: Related Workmentioning

confidence: 99%

Stochastic dynamic programming model for optimal resource allocation in vehicular ad hoc networks

Bhuvaneswari¹,

Paramasivan²,

Kandasamy

2018

Sādhanā

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Vehicular ad hoc network (VANET) is an emerging trend where vehicles communicate with each other and possibly with a roadside unit to assist various applications like monitoring, managing and optimizing the transportation system. Collaboration among vehicles is significant in VANET. Resource constraint is one of the great challenges of VANETs. Because of the absence of centralized management, there is pitfall in optimal resource allocation, which leads to ineffective routing. Effective reliable routing is quite essential to achieve intelligent transportation. Stochastic dynamic programming is currently employed as a tool to analyse, develop and solve network resource constraint and allocation issues of resources in VANET. We have considered this work as a geographical-angular-zone-based two-phase dynamic resource allocation problem with a homogeneous resource class. This work uses a stochastic dynamic programming algorithm based on relaxed approximation to generate optimal resource allocation strategies over time in response to past task completion status history. The second phase resource allocation uses the observed outcome of the first phase task completion to provide optimal viability in resulting decisions. The proposed work will be further extended for the scenario that deals with heterogeneous resource class. Simulation results show that the proposed scheme works significantly well for the problems with identical resources.

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Augmented DTN based energy efficient routing protocol for vehicular ad hoc networks

Cited by 13 publications

References 11 publications

Opportunistic protocol based on social probability and resources efficiency for the intelligent and connected transportation system

Opportunistic protocol based on social probability and resources efficiency for the intelligent and connected transportation system

A Key 6G Challenge and Opportunity—Connecting the Base of the Pyramid: A Survey on Rural Connectivity

Stochastic dynamic programming model for optimal resource allocation in vehicular ad hoc networks

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