Fairness-Aware Data Offloading in Wireless Body Area Networks with QoS Constraint

In recent years, the rapid development of Wireless Body Area Networks (WBANs) has provided efficient healthcare services to emergent medical patients. Nevertheless, the WBANs provide efficient healthcare services; however, the mobility and interference in WBANs inherently affect the quality of links between sensors and coordinators. Therefore, with poor link qualities, selecting the optimal coordinators among sensor nodes is necessary to minimize the network’s heavy energy consumption rate and traffic load. Additionally, in mobile architecture, it is necessary to offload the medical data efficiently from sensor nodes to selected optimal coordinators to manage the Quality-of-Service (QoS) of sensor nodes. Thus, unlike most existing works in this paper, we propose a fairness-aware data offloading scheme for inter-BAN communication to optimize the traffic load and QoS of WBANs. Extensive simulation results show that FARE improves section rate, data offloading price, and throughput over other existing solutions.

[1]  Tri Gia Nguyen,et al.  Quality-Driven Energy-Efficient Big Data Aggregation in WBANs , 2022, IEEE Sensors Letters.

[2]  Yong Li,et al.  Distributed Pricing Policy for Cloud-Assisted Body-to-Body Networks with Optimal QoS and Energy Considerations , 2021, IEEE Transactions on Services Computing.

[3]  Sudip Misra,et al.  Traffic-Aware Efficient Mapping of Wireless Body Area Networks to Health Cloud Service Providers in Critical Emergency Situations , 2018, IEEE Transactions on Mobile Computing.

[4]  Sudip Misra,et al.  Dynamic Connectivity Establishment and Cooperative Scheduling for QoS-Aware Wireless Body Area Networks , 2018, IEEE Transactions on Mobile Computing.

[5]  Sheng Chen,et al.  QoS-Aware Heuristic Scheduling with Delay-Constraint for WBSNs , 2018, 2018 IEEE International Conference on Communications (ICC).

[6]  Luca Benini,et al.  Energy-Aware Bio-Signal Compressed Sensing Reconstruction on the WBSN-Gateway , 2018, IEEE Transactions on Emerging Topics in Computing.

[7]  Sudip Misra,et al.  Link-Quality-Aware Resource Allocation With Load Balance in Wireless Body Area Networks , 2018, IEEE Systems Journal.

[8]  Sudip Misra,et al.  Energy-Efficient and Distributed Network Management Cost Minimization in Opportunistic Wireless Body Area Networks , 2018, IEEE Transactions on Mobile Computing.

[9]  Fan Wu,et al.  Data Quality Guided Incentive Mechanism Design for Crowdsensing , 2018, IEEE Transactions on Mobile Computing.

[10]  Sudip Misra,et al.  EReM: Energy-Efficient Resource Management in Body Area Networks with Fault Tolerance , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.

[11]  Abdallah Makhoul,et al.  Self-Adaptive Data Collection and Fusion for Health Monitoring Based on Body Sensor Networks , 2016, IEEE Transactions on Industrial Informatics.

[12]  Xiaoli Zhou,et al.  Energy Efficiency Optimization by Resource Allocation in Wireless Body Area Networks , 2014, 2014 IEEE 79th Vehicular Technology Conference (VTC Spring).

[13]  Nadeem Javaid,et al.  FEEL: Forwarding Data Energy Efficiently with Load Balancing in Wireless Body Area Networks , 2014, 2014 IEEE 28th International Conference on Advanced Information Networking and Applications.

[14]  Rong Chai,et al.  Joint power allocation and coordinator deployment for Wireless Body Area Network , 2013, 2013 International Conference on Wireless Communications and Signal Processing.

[15]  Twan Basten,et al.  MoBAN: a configurable mobility model for wireless body area networks , 2011, SimuTools.

[16]  Max J. Ammann,et al.  Impact of Hub Location on the Performance of Wireless Body Area Networks for Fitness Applications , 2015, IEEE Antennas and Wireless Propagation Letters.