An Efficient Information Maximization Based Adaptive Congestion Control Scheme in Wireless Sensor Network

Intelligent communication technology can enhance user experience and improve people’s lifestyle. However, due to the limited resources of wireless sensor networks (WSNs), the congestion occurs when the node’s traffic load exceeds it’s the available capacity. Congestion may cause serious problems such as high packet loss and low throughput, which is an extremely deleterious impact on the performance of WSNs. To tackle this issue, a differentiated rate control data collection (DRCDC) scheme is proposed to avoid or alleviate the network congestion. Different from the previous scheme, the DRCDC scheme can mitigate the congestion by intelligently reducing the data that contains less information, and maintain the distortion rate of information collected by the network is small. The DRCDC mainly avoids or mitigates congestion on the spatial and temporal through information entropy theory, and at the same time makes the information collected by the network has the lowest distortion rate. 1) Congestion mitigation in spatial. Since there is a spatial correlation between sensing data, so in the case of collecting a certain amount of data, some missing data in space can be recovered from another spatially acquired data by matrix completion theory. Therefore, in the DRCDC scheme, when congestion occurs, the amount of data transmitted (forwarded) for nodes are congested will be reduced by an intelligent approach, thereby being able to mitigate congestion. 2) Congestion mitigation in temporal. when congestion occurs, reducing the data collection of time slots containing small information to reduce the flow rate that needs to be transmitted, thereby avoiding congestion while minimizing data distortion rate of the network. The experimental results of the DRCDC scheme in a planar network show better performance than the traditional data collection schemes and reducing the packet loss 2.8%–6.8% while reduce the maximum delay by 34.2%–76.3%.

[1]  Rong Du,et al.  Effective Urban Traffic Monitoring by Vehicular Sensor Networks , 2015, IEEE Transactions on Vehicular Technology.

[2]  Zhiwen Zeng,et al.  Adaptive duty cycle control–based opportunistic routing scheme to reduce delay in cyber physical systems , 2019, Int. J. Distributed Sens. Networks.

[3]  Anfeng Liu,et al.  UAVs joint vehicles as data mules for fast codes dissemination for edge networking in Smart City , 2019, Peer-to-Peer Networking and Applications.

[4]  Jiming Chen,et al.  Congestion avoidance, detection and alleviation in wireless sensor networks , 2009, Journal of Zhejiang University SCIENCE C.

[5]  Toshitaka Tsuda,et al.  Data Driven Cyber-Physical System for Landslide Detection , 2019, Mob. Networks Appl..

[6]  Anfeng Liu,et al.  Content Propagation for Content-Centric Networking Systems From Location-Based Social Networks , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[7]  Zhetao Li,et al.  Compressed sensing for image reconstruction via back-off and rectification of greedy algorithm , 2019, Signal Process..

[8]  Wei Liu,et al.  A Queuing Delay Utilization Scheme for On-Path Service Aggregation in Services-Oriented Computing Networks , 2019, IEEE Access.

[9]  Emmanuel J. Candès,et al.  A Singular Value Thresholding Algorithm for Matrix Completion , 2008, SIAM J. Optim..

[10]  Tarek F. Abdelzaher,et al.  An Adaptive-Reliability Cyber-Physical Transport Protocol for Spatio-temporal Data , 2009, 2009 30th IEEE Real-Time Systems Symposium.

[11]  Xiaoheng Deng,et al.  Finding overlapping communities based on Markov chain and link clustering , 2016, Peer-to-Peer Networking and Applications.

[12]  Xiong Li,et al.  Deployment Optimization of Data Centers in Vehicular Networks , 2019, IEEE Access.

[13]  Xiong Li,et al.  Optimizing the Coverage via the UAVs With Lower Costs for Information-Centric Internet of Things , 2019, IEEE Access.

[14]  Xiong Li,et al.  A Collaboration Platform for Effective Task and Data Reporter Selection in Crowdsourcing Network , 2019, IEEE Access.

[15]  Shaobo Zhang,et al.  A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services , 2019, Future Gener. Comput. Syst..

[16]  Yang Cao,et al.  Secure Transmission for Interference Networks: User Selection and Transceiver Design , 2019, IEEE Systems Journal.

[17]  Gaogang Xie,et al.  Low Cost and High Accuracy Data Gathering in WSNs with Matrix Completion , 2018, IEEE Transactions on Mobile Computing.

[18]  Riaan Wolhuter,et al.  An Adaptive Congestion Control and Fairness Scheduling Strategy for Wireless Mesh Networks , 2015, 2015 IEEE Symposium Series on Computational Intelligence.

[19]  Xiao Liu,et al.  A statistical approach to participant selection in location-based social networks for offline event marketing , 2019, Inf. Sci..

[20]  Guan Gui,et al.  Relay Cooperation Enhanced Backscatter Communication for Internet-of-Things , 2019, IEEE Internet of Things Journal.

[21]  Naixue Xiong,et al.  Design and Analysis of Probing Route to Defense Sink-Hole Attacks for Internet of Things Security , 2020, IEEE Transactions on Network Science and Engineering.

[22]  Zhetao Li,et al.  Minimizing Convergecast Time and Energy Consumption in Green Internet of Things , 2020, IEEE Transactions on Emerging Topics in Computing.

[23]  Zhiwen Zeng,et al.  Improving Energy Efficiency of Multimedia Content Dissemination by Adaptive Clustering and D2D Multicast , 2019, Mob. Inf. Syst..

[24]  Weijia Jia,et al.  A novel trust mechanism based on Fog Computing in Sensor-Cloud System , 2020, Future Gener. Comput. Syst..

[25]  Xiaoheng Deng,et al.  Performance Analysis for IEEE 802.11s Wireless Mesh Network in Smart Grid , 2017, Wirel. Pers. Commun..

[26]  Ke Wang,et al.  Using Imbalanced Triangle Synthetic Data for Machine Learning Anomaly Detection , 2019, Computers, Materials & Continua.

[27]  Wei Liu,et al.  A Cost-Efficient Greedy Code Dissemination Scheme Through Vehicle to Sensing Devices (V2SD) Communication in Smart City , 2019, IEEE Access.

[28]  Shigeng Zhang,et al.  Characterizing the Capability of Vehicular Fog Computing in Large-scale Urban Environment , 2018, Mob. Networks Appl..

[29]  Naixue Xiong,et al.  A novel code data dissemination scheme for Internet of Things through mobile vehicle of smart cities , 2019, Future Gener. Comput. Syst..

[30]  Xiao Liu,et al.  Optimizing Trajectory of Unmanned Aerial Vehicles for Efficient Data Acquisition: A Matrix Completion Approach , 2019, IEEE Internet of Things Journal.

[31]  Ramesh Govindan,et al.  RCRT: rate-controlled reliable transport for wireless sensor networks , 2007, SenSys '07.

[32]  Maryam Ahmadi,et al.  Dynamically constructing and maintaining virtual access points in a macro cell with selfish nodes , 2015, J. Syst. Softw..

[33]  Zhiwen Zeng,et al.  An Adaptive Collection Scheme-Based Matrix Completion for Data Gathering in Energy-Harvesting Wireless Sensor Networks , 2019, IEEE Access.

[34]  Naixue Xiong,et al.  Energy-Efficient Resource Sharing Scheme With Out-Band D2D Relay-Aided Communications in C-RAN-Based Underlay Cellular Networks , 2019, IEEE Access.

[35]  Zhiwen Zeng,et al.  Adaption Resizing Communication Buffer to Maximize Lifetime and Reduce Delay for WVSNs , 2019, IEEE Access.

[36]  C. J. Raman,et al.  FCC: Fast congestion control scheme for wireless sensor networks using hybrid optimal routing algorithm , 2018, Cluster Computing.

[37]  Fengqi Yu,et al.  ECODA: Enhanced congestion detection and avoidance for multiple class of traffic in sensor networks , 2009 .

[38]  Anfeng Liu,et al.  Pipeline slot based fast rerouting scheme for delay optimization in duty cycle based M2M communications , 2019, Peer-to-Peer Networking and Applications.

[39]  Ju Ren,et al.  Joint Channel Access and Sampling Rate Control in Energy Harvesting Cognitive Radio Sensor Networks , 2019, IEEE Transactions on Emerging Topics in Computing.

[40]  Ning Zhang,et al.  DDC: Dynamic duty cycle for improving delay and energy efficiency in wireless sensor networks , 2019, J. Netw. Comput. Appl..

[41]  Jie Gao,et al.  Partial Offloading Scheduling and Power Allocation for Mobile Edge Computing Systems , 2019, IEEE Internet of Things Journal.

[42]  Lei Yu,et al.  Data Collection with Accuracy-Aware Congestion Control in Sensor Networks , 2019, IEEE Transactions on Mobile Computing.

[43]  Anfeng Liu,et al.  Duty Cycle Adaptive Adjustment Based Device to Device (D2D) Communication Scheme for WSNs , 2018, IEEE Access.

[44]  Qiang Ye,et al.  STCDG: An Efficient Data Gathering Algorithm Based on Matrix Completion for Wireless Sensor Networks , 2013, IEEE Transactions on Wireless Communications.

[45]  Kim-Kwang Raymond Choo,et al.  Enhancing privacy through uniform grid and caching in location-based services , 2017, Future Gener. Comput. Syst..

[46]  Fang Huang,et al.  CNN-VWII: An Efficient Approach for Large-Scale Video Retrieval by Image Queries , 2018, Pattern Recognit. Lett..

[47]  Sudip Misra,et al.  Assessment of the Suitability of Fog Computing in the Context of Internet of Things , 2018, IEEE Transactions on Cloud Computing.

[48]  Özgür B. Akan,et al.  ESRT: event-to-sink reliable transport in wireless sensor networks , 2003, MobiHoc '03.

[49]  Xiong Li,et al.  To Reduce Delay, Energy Consumption and Collision through Optimization Duty-Cycle and Size of Forwarding Node Set in WSNs , 2019, IEEE Access.

[50]  Long Wang,et al.  A Novel Human Activity Recognition Scheme for Smart Health Using Multilayer Extreme Learning Machine , 2019, IEEE Internet of Things Journal.

[51]  Kai Zhou,et al.  Flexible Adjustments Between Energy and Capacity for Topology Control in Heterogeneous Wireless Multi-hop Networks , 2016, Journal of Network and Systems Management.

[52]  Hao Zhang,et al.  Attribute-Based Privacy-Preserving Data Sharing for Dynamic Groups in Cloud Computing , 2019, IEEE Systems Journal.

[53]  Md Zakirul Alam Bhuiyan,et al.  A Secure IoT Service Architecture With an Efficient Balance Dynamics Based on Cloud and Edge Computing , 2019, IEEE Internet of Things Journal.

[54]  Jingpei Dan,et al.  Stable adaptive channel estimation method under impulsive noise environments , 2017, Int. J. Commun. Syst..

[55]  Naixue Xiong,et al.  Minimizing Delay and Transmission Times with Long Lifetime in Code Dissemination Scheme for High Loss Ratio and Low Duty Cycle Wireless Sensor Networks , 2018, Sensors.