Data Traffic Offloading and Rate Control for Vehicles Using Radio Environment, Network Load and Route Planning

To cope with an exponentially increasing demand on mobile data traffic in cellular network, proximity-based opportunistic vehicular communications can be exploited as a complementary mean to offload and reduce the load of cellular network. In this paper, we propose a two-phase approach for mobile data traffic offloading, which exploits opportunistic contact and future utility with user mobility. The proposed approach includes one phase of initial source selection and subsequent phase of data forwarding. In phase 1, we build a weighted reachability graph, which is a very useful high-level abstraction for studying vehicular communication over time. Then, we propose an initial source selection algorithm, named VRank, and apply it in the weight reachability graph to identify some influential vehicles to serve as initial sources according to the rank of VRank. In phase 2, we formulate the forwarding schedule problem as a global utility maximization problem, which takes heterogeneous user interest and future utility contribution into consideration. Then, we propose an efficient scheme MGUP to solve the problem by providing a solution that decides which object should be broadcast. The effectiveness of our algorithm is verified through extensive simulation using real vehicular trace.

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An Adaptive Data Traffic Offloading Model for Cellular Machine-to-Machine Networks

Internet of Vehicles - Safe and Intelligent Mobility - Lecture Notes in Computer Science ◽

10.1007/978-3-319-27293-1_23 ◽

2015 ◽

pp. 261-272 ◽

Cited By ~ 1

Author(s):

Tao Lei ◽

Shang-guang Wang ◽

Fang-chun Yang

Keyword(s):

Data Traffic ◽

Machine To Machine ◽

Traffic Offloading

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Mobile Data Traffic Offloading with Content Centric Networking

Advances in Intelligent Systems and Computing - Computational Intelligence Methods for Green Technology and Sustainable Development ◽

10.1007/978-3-030-62324-1_1 ◽

2020 ◽

pp. 3-14

Author(s):

Dung Ong Mau ◽

Tuyen Dinh Quang ◽

Anh Phan Tuan ◽

Nga Vu Thi Hong ◽

Quyen Le Ly Quyen

Keyword(s):

Data Traffic ◽

Mobile Data ◽

Content Centric Networking ◽

Traffic Offloading

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CS/CB CoMP scheme with semi-static data traffic offloading in HetNets

2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) ◽

10.1109/pimrc.2013.6666349 ◽

2013 ◽

Cited By ~ 2

Author(s):

Gregory Morozov ◽

Alexei Davydov

Keyword(s):

Data Traffic ◽

Traffic Offloading ◽

Static Data

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A New Efficient Cache Replacement Strategy for Named Data Networking

International journal of Computer Networks & Communications ◽

10.5121/ijcnc.2021.13502 ◽

2021 ◽

Vol 13 (5) ◽

pp. 19-35

Author(s):

Saad Al-Ahmadi

Keyword(s):

Future Internet ◽

Data Availability ◽

Cache Replacement ◽

Data Traffic ◽

Named Data Networking ◽

Future Internet Architecture ◽

Replacement Strategy ◽

Content Retrieval ◽

Network Load ◽

Data Networking

The Information-Centric Network (ICN) is a future internet architecture with efficient content retrieval and distribution. Named Data Networking (NDN) is one of the proposed architectures for ICN. NDN’s innetwork caching improves data availability, reduce retrieval delays, network load, alleviate producer load, and limit data traffic. Despite the existence of several caching decision algorithms, the fetching and distribution of contents with minimum resource utilization remains a great challenge. In this paper, we introduce a new cache replacement strategy called Enhanced Time and Frequency Cache Replacement strategy (ETFCR) where both cache hit frequency and cache retrieval time are used to select evicted data chunks. ETFCR adds time cycles between the last two requests to adjust data chunk’s popularity and cache hits. We conducted extensive simulations using the ccnSim simulator to evaluate the performance of ETFCR and compare it to that of some well-known cache replacement strategies. Simulations results show that ETFCR outperforms the other cache replacement strategies in terms of cache hit ratio, and lower content retrieval delay.

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The Performance Analysis of CDMA Traffic Access Self-Similar Equalization Protocol

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.490-491.1205 ◽

2014 ◽

Vol 490-491 ◽

pp. 1205-1208

Author(s):

Liang Zheng ◽

Bin Yan

Keyword(s):

Performance Analysis ◽

Power Law ◽

Performance Optimization ◽

Random Access ◽

Data Traffic ◽

Similar Model ◽

Network Load ◽

Self Similar ◽

Simulation Results ◽

Access Technique

The random access technique has a bigger influence to the performance optimization of CDMA data traffic. A CDMA random access technique based on self-similar model and its performance analysis are put forward in this paper. The simulation results indicate that the access performance of CDMA data traffic based on self-similar model is attenuated by power law, related to such parameters as fractal coefficient H and network load G. The CDMA traffic access self-similar equalization protocol (TASEP) is put forward and it can improve the access performance of CDMA data traffic distinctly.

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Application of an Improved Recurrent Neural Network in Network Security Situation Prediction

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.951.173 ◽

2014 ◽

Vol 951 ◽

pp. 173-176

Author(s):

Jun Ping Cai ◽

Lei Qu ◽

Gang Chen ◽

Jun Yang

Keyword(s):

Neural Network ◽

Neural Networks ◽

Network Security ◽

Network Topology ◽

High Efficiency ◽

High Accuracy ◽

Data Traffic ◽

Network Load ◽

Nonlinear Complexity ◽

Recursive Neural Networks

The expansion of the network becomes size, network mode is diversification, network topology structure becomes more complex, the data traffic rises rapidly in the network, causes the network load increases, attack, fault and other unexpected network security events are more severe. Neural network to deal with nonlinear, complexity advantage of this paper, network security situation prediction based on improved recursive neural networks, experimental results show that the high efficiency of the method, results are compared with the actual values, low error, high accuracy.

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