scholarly journals NPLP: An Improved Routing-Forwarding Strategy Utilizing Node Profile and Location Prediction for Opportunistic Networks

Information ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 306
Author(s):  
Bangyuan Chen ◽  
Lingna Chen
Keyword(s):  
Urban Areas ◽  
Data Dissemination ◽  
Opportunistic Networks ◽  
Mobile Node ◽  
Network Routing ◽  
Delivery Ratio ◽  
Location Prediction ◽  
Node Location ◽  
Forwarding Strategy ◽  
Routing State

Opportunistic networks are considered as the promising network structures to implement traditional and typical infrastructure-based communication by enabling smart mobile devices in the networks to contact with each other within a fixed communication area. Because of the intermittent and unstable connections between sources and destinations, message routing and forwarding in opportunistic networks have become challenging and troublesome problems recently. In this paper, to improve the data dissemination environment, we propose an improved routing-forwarding strategy utilizing node profile and location prediction for opportunistic networks, which mainly includes three continuous phases: the collecting and updating of routing state information, community detection and optimization and node location prediction. Each mobile node in the networks is able to establish a network routing matrix after the entire process of information collecting and updating. Due to the concentrated population in urban areas and relatively few people in remote areas, the distribution of location prediction roughly presents a type of symmetry in opportunistic networks. Afterwards, the community optimization and location prediction mechanisms could be regarded as an significant foundation for data dissemination in the networks. Ultimately, experimental results demonstrate that the proposed algorithm could slightly enhance the delivery ratio and substantially degrade the network overhead and end-to-end delay as compared with the other four routing strategies.

scholarly journals Location Prediction-Based Data Dissemination Using Swarm Intelligence in Opportunistic Cognitive Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Jie Li ◽  
Xingwei Wang ◽  
Jie Jia ◽  
Pengfei Wang ◽  
Yan Zhou ◽  
...  
Keyword(s):  
Swarm Intelligence ◽  
Large Scale ◽  
Data Dissemination ◽  
Opportunistic Networks ◽  
Cognitive Networks ◽  
Destination Node ◽  
Delivery Ratio ◽  
Location Prediction ◽  
Biologically Inspired ◽  
Pervasive Environment

Swarm intelligence is widely used in the application of communication networks. In this paper we adopt a biologically inspired strategy to investigate the data dissemination problem in the opportunistic cognitive networks (OCNs). We model the system as a centralized and distributed hybrid system including a location prediction server and a pervasive environment deploying the large-scale human-centric devices. To exploit such environment, data gathering and dissemination are fundamentally based on the contact opportunities. To tackle the lack of contemporaneous end-to-end connectivity in opportunistic networks, we apply ant colony optimization as a cognitive heuristic technology to formulate a self-adaptive dissemination-based routing scheme in opportunistic cognitive networks. This routing strategy has attempted to find the most appropriate nodes conveying messages to the destination node based on the location prediction information and intimacy between nodes, which uses the online unsupervised learning on geographical locations and the biologically inspired algorithm on the relationship of nodes to estimate the delivery probability. Extensive simulation is carried out on the real-world traces to evaluate the accuracy of the location prediction and the proposed scheme in terms of transmission cost, delivery ratio, average hops, and delivery latency, which achieves better routing performances compared to the typical routing schemes in OCNs.

Optimized Routing for Efficient Data Dissemination in MANET to Meet the Fast-Changing Technology

2018 ◽  
Vol 26 (3) ◽  
pp. 25-36
Author(s):  
Deo Prakash ◽  
Neeraj Kumar ◽  
M.L. Garg
Keyword(s):  
Ad Hoc ◽  
Data Dissemination ◽  
Dynamic Network ◽  
Mobile Node ◽  
Delivery Ratio ◽  
Communication Link ◽  
Centralized Control ◽  
Mobile Adhoc Network ◽  
Link Stability ◽  
Efficient Data

Mobile Adhoc Network (MANET) is a dynamic network without any centralized control. Due to frequent topological change, routing has been always a challenging task in these networks. This article presents optimized routing for efficient data dissemination in MANETs to meet the fast-changing technology of today's world. A novel metric for such optimized routing in MANET is proposed. The main parameters considered to evaluate this metric are the energy consumed during the communication, link stability, Packet Delivery Ratio (PDR) and traffic. The concept is based on a scenario in which a mobile node (source) sends data packets to another mobile node (destination) through its dynamically connected neighboring nodes. The path which consumes the lowest energy and also shows highest link stability is selected for consideration. In case the paths consume the same amount of energy, the highest stable path is chosen. In this manner, the most optimized path is selected. The authors' routing approach shows more efficiency than earlier in dissemination of data and information over the Mobile Ad-Hoc Networks.

GPS Based Location Prediction and Authentication during Inter-MSC Handover

2014 ◽  
Vol 602-605 ◽  
pp. 2326-2329 ◽  
Author(s):  
K. Regin Bose ◽  
V. Sankaranarayanan
Keyword(s):  
Time Delay ◽  
Data Transfer ◽  
Mobile Node ◽  
Base Station ◽  
Location Prediction ◽  
Information Centre ◽  
Exact Location ◽  
Mobile Information ◽  
Node Location

In this paper a reliable secured handover with less time delay is suggested. To enhance the reliability of data transfer during handover, the exact location of the Mobile Node (MN) is to be known. Hence a GPS based Mobile Node location and direction prediction is suggested, which helps to handover to the appropriate Base Station. The security in transfer of data is ensured by a novel Mobile Information Centre (MIC) based dual authentication algorithm.

scholarly journals A Data Dissemination Method Based on Region Type Correlations for Mobile Opportunistic Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Linfeng Liu ◽  
Daoliang Chen
Keyword(s):  
Data Dissemination ◽  
Opportunistic Networks ◽  
Delivery Ratio ◽  
Mobility Patterns ◽  
Relay Nodes ◽  
Data Packets ◽  
Mobile Opportunistic Networks ◽  
Communication Devices ◽  
Markov Decision ◽  
Markov Decision Model

In Mobile Opportunistic Networks (MONs), due to the node movements and the uncontrollable on/off switches of the carried communication devices, the contacts between nodes may be scarce and momentary, and thus a data packet should be transferred through some discrete hops. To avoid the costly flooding of data packets, the data packets are typically disseminated to some relay nodes selected by data holders. However, the mobility patterns of nodes will become different in different types of regions (such as residential regions, commercial regions, scenery regions, or industrial regions); i.e., the movement directions and movement ranges of nodes are frequently varied when the nodes move among various regions. At present, the issues regarding the region types and region type correlations have not been investigated for the data dissemination in existing works. To this end, we propose a Region Type based Data Dissemination Method (RTDDM) for MONs, which exploits the region type correlations and selects the proper relay nodes through a Markov decision model. To verify the performance of RTDDM, we give some theoretical analysis as well as an elaborated simulation study, the results of which show that RTDDM can improve the delivery ratio and reduce the delivery delay, especially in the applications with various region types.

Friend-Based Prediction Routing Protocol in Socially-Aware Opportunistic Networks

2014 ◽  
Vol 519-520 ◽  
pp. 241-244
Author(s):  
Li Liu
Keyword(s):  
Mobile Devices ◽  
Routing Protocol ◽  
Social Relationship ◽  
Data Dissemination ◽  
Opportunistic Networks ◽  
Delivery Ratio ◽  
Average Latency ◽  
Simulation Results ◽  
Carry And Forward ◽  
Intermittently Connected

Mobile devices are popular used in peoples life. Generally, most of portable mobile devices are carried by people. Thus, the mobility of mobile devices is influenced heavily by peoples social relationship. Socially-aware Opportunistic Networks are used in intermittently connected networks by use of store-carry-and-forward fashion. It is mainly based on social relationship to design solutions for problem such as routing protocol or data dissemination. In this paper, we exploit social relationship about friendships information among people and use them to predict the contact opportunities. We present Friend-based Prediction routing protocol (FBP) and establish experiment based on ONE. The simulation results show that the efficiency of FBP outperforms Epidemic and PROPHET in higher delivery ratio, lower overhead and shorter average latency.

scholarly journals Novel Opportunistic Network Routing Based on Social Rank for Device-to-Device Communication

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Tong Wang ◽  
Yongzhe Zhou ◽  
Yunfeng Wang ◽  
Mengbo Tang
Keyword(s):  
Communication Networks ◽  
Social Rank ◽  
Large Data ◽  
Opportunistic Networks ◽  
Network Routing ◽  
Delivery Ratio ◽  
Opportunistic Network ◽  
Fifth Generation ◽  
Device To Device ◽  
Data Files

In recent years, there has been dramatic proliferation of research concerned with fifth-generation (5G) mobile communication networks, among which device-to-device (D2D) communication is one of the key technologies. Due to the intermittent connection of nodes, the D2D network topology may be disconnected frequently, which will lead to failure in transmission of large data files. In opportunistic networks, in case of encountering nodes which never meet before a flood message blindly to cause tremendous network overhead, a novel opportunistic network routing protocol based on social rank and intermeeting time (SRIT) is proposed in this paper. An improved utility approach applied in utility replication based on encounter durations and intermeeting time is put forward to enhance the routing efficiency. Meanwhile, in order to select better candidate nodes in the network, a social graph among people is established when they socially relate to each other in social rank replication. The results under the scenario show an advantage of the proposed opportunistic network routing based on social rank and intermeeting time (SRIT) over the compared algorithms in terms of delivery ratio, average delivery latency, and overhead ratio.

scholarly journals A Location Prediction Algorithm with Daily Routines in Location-Based Participatory Sensing Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Ruiyun Yu ◽  
Xingyou Xia ◽  
Shiyang Liao ◽  
Xingwei Wang
Keyword(s):  
Markov Model ◽  
Strong Relationship ◽  
Mobile Node ◽  
Prediction Algorithm ◽  
Participatory Sensing ◽  
Location Prediction ◽  
Mobile Nodes ◽  
Daily Routines ◽  
Sensing Systems ◽  
Node Location

Mobile node location predication is critical to efficient data acquisition and message forwarding in participatory sensing systems. This paper proposes a social-relationship-based mobile node location prediction algorithm using daily routines (SMLPR). The SMLPR algorithm models application scenarios based on geographic locations and extracts social relationships of mobile nodes from nodes’ mobility. After considering the dynamism of users’ behavior resulting from their daily routines, the SMLPR algorithm preliminarily predicts node’s mobility based on the hidden Markov model in different daily periods of time and then amends the prediction results using location information of other nodes which have strong relationship with the node. Finally, the UCSD WTD dataset are exploited for simulations. Simulation results show that SMLPR acquires higher prediction accuracy than proposals based on the Markov model.

BlueFlood

2021 ◽  
Vol 2 (4) ◽  
pp. 1-30
Author(s):  
Beshr Al Nahas ◽  
Antonio Escobar-Molero ◽  
Jirka Klaue ◽  
Simon Duquennoy ◽  
Olaf Landsiedel
Keyword(s):  
Experimental Study ◽  
Bit Error Rate ◽  
Error Rate ◽  
Data Dissemination ◽  
Delivery Ratio ◽  
Controlled Experiments ◽  
Seamless Integration ◽  
Peer Communication ◽  
Shift Keying ◽  
University Buildings

Bluetooth is an omnipresent technology, available on billions of devices today. While it has been traditionally limited to peer-to-peer communication and star networks, the recent Bluetooth Mesh standard extends it to multi-hop networking. In addition, the Bluetooth 5 standard introduces new modes to allow for increased reliability. In this article, we evaluate the feasibility of concurrent transmissions (CT) in Bluetooth via modeling and controlled experiments and then devise an efficient network-wide data dissemination protocol, BlueFlood, based on CT for multi-hop Bluetooth networks. First, we model and analyze how CT distorts the received waveform and characterize the Bit Error Rate of a Frequency-Shift Keying receiver to show that CT is feasible over Bluetooth. Second, we verify our analytic results with a controlled experimental study of CT over Bluetooth PHY. Third, we present BlueFlood, a fast and efficient network-wide data dissemination in multi-hop Bluetooth networks. In our experimental evaluation, in two testbeds deployed in university buildings, we show that BlueFlood achieves 99.9% end-to-end delivery ratio with a duty-cycle of 0.4% for periodic dissemination of advertising packets of 38 bytes with 200 milliseconds intervals at 2 Mbps. Moreover, we show that BlueFlood can be received by off-the-shelf devices such as smartphones, paving a seamless integration with existing technologies.

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