opportunistic network
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Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8058
Author(s):  
Christian E. Galarza ◽  
Jonathan M. Palma ◽  
Cecilia F. Morais ◽  
Jaime Utria ◽  
Leonardo P. Carvalho ◽  
...  

This paper proposes a new theoretical stochastic model based on an abstraction of the opportunistic model for opportunistic networks. The model is capable of systematically computing the network parameters, such as the number of possible routes, the probability of successful transmission, the expected number of broadcast transmissions, and the expected number of receptions. The usual theoretical stochastic model explored in the methodologies available in the literature is based on Markov chains, and the main novelty of this paper is the employment of a percolation stochastic model, whose main benefit is to obtain the network parameters directly. Additionally, the proposed approach is capable to deal with values of probability specified by bounded intervals or by a density function. The model is validated via Monte Carlo simulations, and a computational toolbox (R-packet) is provided to make the reproduction of the results presented in the paper easier. The technique is illustrated through a numerical example where the proposed model is applied to compute the energy consumption when transmitting a packet via an opportunistic network.


Author(s):  
Rahul Sachdeva ◽  
◽  
Amita Dev ◽  

Opportunistic Networks can be defined as Delay Tolerant Network, which are formed dynamically with participating nodes’ help. Opportunistic Networks follows Store-Carry-Forward principle to deliver/route the data in the network. Routing in Opportunistic Network starts with the Seed Node (Source Node) which delivers the data with the help of Intermediate nodes. Intermediate nodes store the data while roaming in the network until it comes in contact with appropriate forwarding node (relay node) or destination node itself. An extensive literature survey is performed to analyse various routing protocols defined for Opportunistic Network. With mobility induced routing, establishing and maintaining the routing path is a major challenge. Further, Store-Carry-Forward routing paradigm imposes various challenges while implementing and executing the network. Due to the unavailability of the suitable relay node, data needs to be stored within the Node’s Memory, imposes buffer storage issues at the node level. Also, uncontrolled flooding may impose link-level Congestion and treated as overhead to maintain the network. Another major challenge can be maintaining the energy level of the nodes in the network. Recently developed ONE (Opportunistic Network Environment) Simulator is used to simulate and emulate the environment required by Opportunistic Network. Along with the extensive literature survey of the protocols, few of the existing protocols viz. Direct Delivery, ProPHET, Epidemic and Spray & Wait Routing are implemented using ONE Simulator to analyse their performance while in execution. Results are being compared, and the researchers’ future direction is identified to address the open problems and challenges in Opportunistic Network.


2021 ◽  
Author(s):  
Renu Dalal ◽  
Manju Khari

Abstract Frequent disconnection, high end-to-end latency, dynamic topology, sparse node density, lack of pre-existing infrastructure, and opportunistic message transmission on wireless link, makes routing difficult in Opportunistic network (Oppnet). In present scenario, Oppnet allows the people to interact with contrasting ways like with diverse mobility, groups, and etc. During transmission of messages in such network security and trust performs major role. Delay Tolerant Network (DTN) are much prone of having inherent risk of attack. Malicious node, selfish node, and attacks are major impact on deteriorating network performance. To prevent the network from such deteriorating factors, this paper introduces the new platform to provide reliable and authentic transmission of message in opportunistic network. Blockchain-based Routing in Opportunistic Network (BRON) uses the concept of Blockchain through which each node work as an authentic node and transmit the secure messages in Oppnet. Opportunistic Network Environment (ONE) tool is used to implement BRON. This protocol generates 36% reduced packet drops ratio, 57% enhanced delivery ratio, 55% lesser overhead ratio, 35.2% reduced average latency, and 65% lesser average buffer time as compared to direct delivery ratio with respect to number of nodes.


2021 ◽  
pp. 207-223
Author(s):  
Md. Khalid Mahbub Khan ◽  
Muhammad Sajjadur Rahim ◽  
Abu Zafor Md. Touhidul Islam

2021 ◽  
Author(s):  
Khuram Khalid

In this thesis, a history-based energy-efficient routing protocol (called AEHBPR) for opportunistic networks (OppNets) is proposed, which saves the energy consumption by avoiding unnecessary packets transmission in the network and by clearing the buffer of nodes carrying the copies of the already delivered packets. The proposed AEHBPR protocol is evaluated using the Opportunistic NEtwork (ONE) simulator with both synthetic and real mobility traces, showing a superior performance compared to the History-Based Prediction for Routing (HBPR) protocol and AEProphet, in terms of average remaining energy, number of dead nodes, number of delivered messages, and overhead ratio, where AEProphet is the ProPHet routing protocol for OppNets on which the same energy-aware mechanism has been implemented.


2021 ◽  
Author(s):  
Khuram Khalid

In this thesis, a history-based energy-efficient routing protocol (called AEHBPR) for opportunistic networks (OppNets) is proposed, which saves the energy consumption by avoiding unnecessary packets transmission in the network and by clearing the buffer of nodes carrying the copies of the already delivered packets. The proposed AEHBPR protocol is evaluated using the Opportunistic NEtwork (ONE) simulator with both synthetic and real mobility traces, showing a superior performance compared to the History-Based Prediction for Routing (HBPR) protocol and AEProphet, in terms of average remaining energy, number of dead nodes, number of delivered messages, and overhead ratio, where AEProphet is the ProPHet routing protocol for OppNets on which the same energy-aware mechanism has been implemented.


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