Causal and Total Order in Opportunistic Networks

2016 ◽  
pp. 221-262 ◽  
Author(s):  
Mihail Costea ◽  
Radu-Ioan Ciobanu ◽  
Radu-Corneliu Marin ◽  
Ciprian Dobre ◽  
Constandinos X. Mavromoustakis ◽  
...  
Keyword(s):  
Opportunistic Networks ◽  
Total Order ◽  
Data Type ◽  
Opportunistic Network ◽  
Causal Order ◽  
Network Applications ◽  
Hit Rate ◽  
Replicated Data ◽  
Type Algorithm ◽  
Network Emulator

Opportunistic network applications are usually assumed to work only with unordered immutable messages, like photos, videos or music files, while applications that depend on ordered or mutable messages, like chat or shared contents editing applications, are ignored. In this chapter, we examine how causal and total ordering can be achieved in an opportunistic network. By leveraging on existing dissemination algorithms, we investigate if causal order can be efficiently achieved in terms of hit rate and latency compared to not using any order. Afterwards, we propose a Commutative Replicated Data Type algorithm based on Logoot that uses the nature of opportunistic networks to its advantage. Finally, we present the results of the experiments for the new algorithm by using an opportunistic network emulator, mobility traces and chat traces.

scholarly journals A Novel Theoretical Probabilistic Model for Opportunistic Routing with Applications in Energy Consumption for WSNs

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8058
Author(s):  
Christian E. Galarza ◽  
Jonathan M. Palma ◽  
Cecilia F. Morais ◽  
Jaime Utria ◽  
Leonardo P. Carvalho ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Energy Consumption ◽  
Stochastic Model ◽  
Opportunistic Networks ◽  
Opportunistic Routing ◽  
Opportunistic Network ◽  
Expected Number ◽  
Successful Transmission ◽  
Network Parameters ◽  
Proposed Model

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.

Survey on Node Mobility Model for Opportunistic Network

2011 ◽  
Vol 52-54 ◽  
pp. 1253-1257 ◽  
Author(s):  
Ming Xia Yang ◽  
Shuang Xia Han ◽  
Cai Yun Yang ◽  
Lu Zhang ◽  
Dong Fen Ye
Keyword(s):  
Wireless Sensor Networks ◽  
Ad Hoc ◽  
Mobility Model ◽  
Opportunistic Networks ◽  
Wireless Sensor ◽  
Node Mobility ◽  
Mobility Models ◽  
Opportunistic Network ◽  
Research Focus ◽  
Mobile Ad Hoc

Opportunistic networks is one of the newest hot research spots in wireless networks after mobile ad hoc net-works(MANET) and wireless sensor networks(WSN). Mobility model describes mobility manners of nodes. It has been widely used in research on wireless network. This paper firstly introduced, classifies, and compares the current familiar mobility models. Secondly, it classifies, and compares the current familiar mobility models. Next, it was discussed that current research focus on new mobility models, analysis of nodes mobility features, trace strategy, and evaluation of mobility model. Finally, this paper involved what calls for further study.

scholarly journals Impact of Node Density on the QoS Parameters of Routing Protocols in Opportunistic Networks for Smart Spaces

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Puneet Garg ◽  
Ashutosh Dixit ◽  
Preeti Sethi ◽  
Plácido Rogerio Pinheiro
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Smart Cities ◽  
Opportunistic Networks ◽  
Opportunistic Routing ◽  
Maximum Output ◽  
Opportunistic Network ◽  
Smart Spaces ◽  
Node Density ◽  
Wide Range

The need and importance of Smart Spaces have been potentially realized by the researchers due to its applicability in the current lifestyle. Opportunistic network, a successor of mobile ad hoc networks and a budding technology of network, is a best-suited technology for implementing Smart Spaces due to its wide range of applications in real-life scenarios ranging from building smart cities to interplanetary communication. There are numerous routing protocols which are available in opportunistic network, each having their pros and cons; however, no research till the time of listing has been done which can quantitatively demonstrate the maximum performance of these protocols and standardize the comparison of opportunistic routing protocols which has been a major cause of ambiguous performance evaluation studies. The work here presents a categorical view of the opportunistic routing protocol family and thereby compares and contrasts the various simulators suited for their simulation. Thereafter, the most popular protocols (selecting at least one protocol from each category) are compared based on node density on as many as 8 standard performance metrics using ONE simulator to observe their scalability, realism, and comparability. The work concludes by presenting the merits and demerits of each of the protocols discussed as well as specifying the best routing protocol among all the available protocols for Smart Spaces with maximum output. It is believed that the results achieved by the implemented methodology will help future researchers to choose appropriate routing protocol to delve into their research under different scenarios.

A Purpose-Driven User Mobility Model for Opportunistic Networks

2010 ◽  
Vol 171-172 ◽  
pp. 804-809
Author(s):  
Jian Bo Xu ◽  
Guang Yang
Keyword(s):  
Human Movement ◽  
Mobility Model ◽  
Opportunistic Networks ◽  
User Mobility ◽  
Node Mobility ◽  
Opportunistic Network ◽  
Data Forwarding ◽  
Challenging Tasks ◽  
Efficient Data ◽  
Two Sides

An opportunistic Network is a network consisting exclusively of users’ mobile devices, with mobility being one of its essential features. Under the circumstances that a path may never exist between the two sides of communication, an opportunistic network exploits node mobility to realize delayed data delivery by capturing the opportunities of node meeting to relay messages. Designing efficient data forwarding strategies is one of the most challenging tasks in opportunistic network research, while currently the validation of any protocol for data forwarding almost absolutely relies on simulations of which node mobility models are one of the fundamental components. In this paper, we suggest a purpose-driven user mobility model for opportunistic networks which, to our best knowledge, is the first work considering the factor of purposes behind users’ movement. On the basis of location functionalization, our model can gain a better approximation of human movement patterns.

scholarly journals Study on similarity indices for link prediction in opportunistic networks

2018 ◽  
Vol 10 (10) ◽  
pp. 168781401880319
Author(s):  
Xulin Cai ◽  
Jian Shu ◽  
Linlan Liu
Keyword(s):  
Social Network ◽  
Link Prediction ◽  
Opportunistic Networks ◽  
Network Evolution ◽  
Experimental Results ◽  
Superior Performance ◽  
Node Mobility ◽  
Opportunistic Network ◽  
Similarity Indices ◽  
Intermittent Contact

Link prediction aims to estimate the existence of links between nodes, using information of network structures and node properties. According to the characteristics of node mobility, node intermittent contact, and high delay of opportunistic network, novel similarity indices are constructed based on CN, AA, and RA. The indices CN, AA, and RA do not consider the historic information of networks. Similarity indices, T_CN, T_AA, and T_RA, based on temporal characteristics are proposed. These take the historic information of network evolution into consideration. Using historic information of the evolution of opportunistic networks and 2-hop neighbor information of the nodes, similarity indices based on the temporal-spatial characteristics, O_CN, O_AA, and O_RA, are proposed. Based on the imote traces cambridge (ITC) and detected social network (DSN) datasets, the experimental results indicate that similarity indices O_CN, O_AA, and O_RA outperform CN, AA, and RA. Furthermore, index O_AA has superior performance.

scholarly journals A history-based energy-efficient routing protocol for opportunistic networks

2021 ◽  
Author(s):  
Khuram Khalid
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Opportunistic Networks ◽  
Superior Performance ◽  
Opportunistic Network ◽  
Energy Aware ◽  
Energy Efficient Routing ◽  
One Simulator ◽  
Overhead Ratio

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.

scholarly journals Node Authentication Using NTRU Algorithm in Opportunistic Network

2019 ◽  
Vol 20 (1) ◽  
pp. 83-92 ◽  
Author(s):  
Musaeed Abouaroek ◽  
Khaleel Ahmad
Keyword(s):  
Natural Disasters ◽  
Mobile Devices ◽  
Mobile Phones ◽  
Opportunistic Networks ◽  
Wireless Technology ◽  
Opportunistic Network ◽  
Information And Communication ◽  
Delay Tolerant ◽  
Quantum Cryptosystem ◽  
Communication Operations

The demand for using wireless paradigms for performing various information and communication operations has been exploded. The opportunistic networks is a special type of delay tolerant networks proposed to operate in an emergency manner to facilitate mobile connectivity between the nodes when there is no connectivity. These emergencies are caused either by human-made or natural disasters. Opportunistic Networks depend on mobile phones and other mobile devices that carry wireless technology. This paper is an attempt to expand the opportunistic network through the authentication nodes. We propose an NTRU algorithm for node authentication in opportunistic networks .NTRU algorithm is an asymmetric post-quantum cryptosystem. This algorithm is unbreakable and robust compared to RSA and ECC cryptosystem.

scholarly journals A Routing Algorithm for the Sparse Opportunistic Networks Based on Node Intimacy

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Gang Xu ◽  
Xinyue Wang ◽  
Na Zhang ◽  
Zhifei Wang ◽  
Lin Yu ◽  
...  
Keyword(s):  
Routing Algorithm ◽  
Opportunistic Networks ◽  
Network Routing ◽  
Routing Algorithms ◽  
Time Slice ◽  
Message Delivery ◽  
Opportunistic Network ◽  
Network Resources ◽  
Subsequent Time

Opportunistic networks are becoming more and more important in the Internet of Things. The opportunistic network routing algorithm is a very important algorithm, especially based on the historical encounters of the nodes. Such an algorithm can improve message delivery quality in scenarios where nodes meet regularly. At present, many kinds of opportunistic network routing algorithms based on historical message have been provided. According to the encounter information of the nodes in the last time slice, the routing algorithms predict probability that nodes will meet in the subsequent time slice. However, if opportunistic network is constructed in remote rural and pastoral areas with few nodes, there are few encounters in the network. Then, due to the inability to obtain sufficient encounter information, the existing routing algorithms cannot accurately predict whether there are encounters between nodes in subsequent time slices. For the purpose of improving the accuracy in the environment of sparse opportunistic networks, a prediction model based on nodes intimacy is proposed. And opportunistic network routing algorithm is designed. The experimental results show that the ONBTM model effectively improves the delivery quality of messages in sparse opportunistic networks and reduces network resources consumed during message delivery.

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