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.

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 An Efficient Routing Protocol Using the History of Delivery Predictability in Opportunistic Networks

2018 ◽  
Vol 8 (11) ◽  
pp. 2215 ◽  
Author(s):  
Eun Lee ◽  
Dong Seo ◽  
Yun Chung
Keyword(s):  
Routing Protocol ◽  
Opportunistic Networks ◽  
Opportunistic Routing ◽  
Delay Tolerant Network ◽  
Buffer Size ◽  
Destination Node ◽  
Delivery Ratio ◽  
Mobile Nodes ◽  
Final Destination ◽  
History Of

In opportunistic networks such as delay tolerant network, a message is delivered to a final destination node using the opportunistic routing protocol since there is no guaranteed routing path from a sending node to a receiving node and most of the connections between nodes are temporary. In opportunistic routing, a message is delivered using a ‘store-carry-forward’ strategy, where a message is stored in the buffer of a node, a node carries the message while moving, and the message is forwarded to another node when a contact occurs. In this paper, we propose an efficient opportunistic routing protocol using the history of delivery predictability of mobile nodes. In the proposed routing protocol, if a node receives a message from another node, the value of the delivery predictability of the receiving node to the destination node for the message is managed, which is defined as the previous delivery predictability. Then, when two nodes contact, a message is forwarded only if the delivery predictability of the other node is higher than both the delivery predictability and previous delivery predictability of the sending node. Performance analysis results show that the proposed protocol performs best, in terms of delivery ratio, overhead ratio, and delivery latency for varying buffer size, message generation interval, and the number of nodes.

scholarly journals Information Transmission Probability and Cache Management Method in Opportunistic Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Jia Wu ◽  
Zhigang Chen ◽  
Ming Zhao
Keyword(s):  
Data Transmission ◽  
Transmission Probability ◽  
Opportunistic Networks ◽  
Utilization Rate ◽  
Destination Node ◽  
Delivery Ratio ◽  
Cache Management ◽  
Network Efficiency ◽  
Network Algorithms ◽  
Management Method

In real network environment, nodes may acquire the communication destination during data transmission and find a suitable neighbor node to perform effective data classification transmission. This is similar to finding certain transmission targets during data transmission with mobile devices. However, the node cache space in networks is limited, and waiting for the destination node can also cause end-to-end delay. To improve the transmission environment, this study established Data Transmission Probability and Cache Management method. According to selection of high meeting probability node, cache space is reconstructed by node. It is good for nodes to improve delivery ratio and reduce delay. Through experiments and the comparison of opportunistic network algorithms, this method improves the cache utilization rate of nodes, reduces data transmission delay, and improves the overall network efficiency.

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 Performance Evaluation of Social Routing Protocols Based on the Effect of Delivery Ratio and Average Hop Count in Delay-tolerant Networks (DTN)

2019 ◽  
Vol 4 (12) ◽  
pp. 155-158
Author(s):  
Sujan Chandra Roy ◽  
Farhana Enam ◽  
Md. Ashraful Islam
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Ad Hoc ◽  
Delay Tolerant Networks ◽  
Opportunistic Networks ◽  
Destination Node ◽  
Delivery Ratio ◽  
Hop Count ◽  
Message Transmission ◽  
Delay Tolerant

Delay-Tolerant Networks (DTNs) are part of Opportunistic networks. In the case of opportunistic networks, the joined node of a network can have zero or partial knowledge about other nodes in a network. For this reason, the evident information towards the nodes in the existing network is most difficult to collect for forwarding the message. The application of Opportunistic networks is where have a high tolerance for long delays, high error rate, etc. DTNs are also sparse dynamic Ad-hoc networks were source to destination path does not present all-time for successfully message transmission. As DTN has no end-to-end path for message transmission source to destination node so, the routing design is so sophisticated. The social-based routing protocol is developed to improve the routing mechanism by focusing on social behavior and the interaction with the nodes of a network. Consequently, the performance analysis of existing several DTN routing protocols represents a significant role in designing or developing a new routing protocol for a specific scenario. This article investigates the execution of ordinary routing protocols of DTNs such as Epidemic, Binary Spray and Wait (BSNW), including two social-based routing protocols such as Scorp and dLife using Opportunistic Network Environment (ONE) simulator. The performance of these routing protocols is measured based on delivery ratio and average hop count with inevitable simulation settings. From the simulation result, it is condensed that for higher delivery ratio, BSNW is best, and for average hop count, dLife is the best routing protocol.  

Performance Analysis of TCP Variants using AODV and DSDV Routing Protocols in MANETs

2019 ◽  
Vol 13 ◽  
Author(s):  
Rajnesh Singh ◽  
Neeta Singh ◽  
Aarti Gautam Dinker
Keyword(s):  
Ad Hoc Networks ◽  
Routing Protocols ◽  
Ad Hoc ◽  
Packet Delivery Ratio ◽  
Transport Layer ◽  
Destination Node ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Two Measures ◽  
Hoc Networks

TCP is the most reliable transport layer protocol that provides reliable data delivery from source to destination node. TCP works well in wired networks but it is assumed that TCP is less preferred for ad-hoc networks. However, for application in ad-hoc networks, TCP can be modified to improve its performance. Various researchers have proposed improvised variants of TCP by only one or two measures. These one or two measures do not seem to be sufficient for proper analysis of improvised version of TCP. So, in this paper, the performance of different TCP versions is investigated with DSDV and AODV routing Protocols. We analyzed various performance measures such as throughput, delay, packet drop, packet delivery ratio and number of acknowledgements. The simulation results are carried out by varying number of nodes in network simulator tool NS2. It is observed that TCP Newreno achieved higher throughput and packet delivery ratio with both AODV and DSDV routing protocols.Whereas TCP Vegas achieved minimum delay and packet loss with both DSDV and AODV protocol. However TCP sack achieved minimum acknowledgment with both AODV and DSDV routing protocols. In this paper the comparison of all these TCP variants shows that TCP Newreno provides better performance with both AODV and DSDV protocols.

scholarly journals Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network

2021 ◽  
Vol 12 (2) ◽  
pp. 1-22
Author(s):  
Jianguo Chen ◽  
Kenli Li ◽  
Keqin Li ◽  
Philip S. Yu ◽  
Zeng Zeng
Keyword(s):  
Large Scale ◽  
Sequence Data ◽  
Location Prediction ◽  
City Management ◽  
Dynamic Planning ◽  
Graph Sequence ◽  
Graph Modeling ◽  
The Government ◽  
Location Clustering ◽  
Station Location

Benefiting from convenient cycling and flexible parking locations, the Dockless Public Bicycle-sharing (DL-PBS) network becomes increasingly popular in many countries. However, redundant and low-utility stations waste public urban space and maintenance costs of DL-PBS vendors. In this article, we propose a Bicycle Station Dynamic Planning (BSDP) system to dynamically provide the optimal bicycle station layout for the DL-PBS network. The BSDP system contains four modules: bicycle drop-off location clustering, bicycle-station graph modeling, bicycle-station location prediction, and bicycle-station layout recommendation. In the bicycle drop-off location clustering module, candidate bicycle stations are clustered from each spatio-temporal subset of the large-scale cycling trajectory records. In the bicycle-station graph modeling module, a weighted digraph model is built based on the clustering results and inferior stations with low station revenue and utility are filtered. Then, graph models across time periods are combined to create a graph sequence model. In the bicycle-station location prediction module, the GGNN model is used to train the graph sequence data and dynamically predict bicycle stations in the next period. In the bicycle-station layout recommendation module, the predicted bicycle stations are fine-tuned according to the government urban management plan, which ensures that the recommended station layout is conducive to city management, vendor revenue, and user convenience. Experiments on actual DL-PBS networks verify the effectiveness, accuracy, and feasibility of the proposed BSDP system.

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.

scholarly journals A Stackelberg-Game-Based Power Control Algorithm for Wireless Mesh Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yanbing Liu ◽  
Tao Wu ◽  
Jun Huang ◽  
Shousheng Jia
Keyword(s):  
Power Control ◽  
Wireless Mesh Networks ◽  
Control Algorithm ◽  
Large Scale ◽  
Mesh Networks ◽  
Stackelberg Game ◽  
Noncooperative Game ◽  
Destination Node ◽  
Wireless Mesh ◽  
Power Control Algorithm

Wireless mesh networks (WMNs) are a promising networking paradigm for next generation wireless networking system. Power control plays a vital role in WMNs and is realized to be a crucial step toward large-scale WMNs deployment. In this paper, we address the problem of how to allocate the power for both optimizing quality of service (QoS) and saving the power consumption in WMNs based on the game theory. We first formulate the problem as a noncooperative game, in which the QoS attributes and the power of each node are defined as a utility function, and all the nodes attempt to maximize their own utility. In such game, we correlate all the interfering nodes to be an interfering object and the receiving node to be the interfering object's virtual destination node. We then present an equilibrium solution for the noncooperative game using Stackelberg model, and we propose an iterative, distributed power control algorithm for WMNs. Also, we conduct numeric experiments to evaluate the system performance, our results show that the proposed algorithm can balance nodes to share the limited network resources and maximize total utility, and thus it is efficient and effective for solving the power control problem in WMNs.

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