Reliable packet transmission in WBAN with dynamic and optimized QoS using multi-objective lion cooperative hunt optimizer

Abstract

Recent studies demonstrate that handling a patient’s health-related data needs dynamic Quality of Service (QoS) to cope up with significant changes in the functioning of a Patient Monitoring Wireless Body Area Network (PA-WBAN). This kind of system demands a remarkable improvement in the QoS as it is dealing with the reliable transmission of a large volume of assorted data in a frequently changing environment. The QoS in a PA-WBAN is not only about how it senses or reads data from various body parts but is how it deciphers the sensed data. In the patient monitoring system, if the required data is not available in a readable format or not in a specific time, then this data becomes useless and is of no use. However, to harmonize these requirements, two approaches are proposed in this paper. The first protocol is developed for obtaining dynamic QoS for reliable packet transmission. It offers both node and packet-level dynamic-priority assignment policy, which further helps in fair and dynamic resource allocation, queuing, scheduling, retransmission, drop, and delay. It provides fair queuing and percentile scheduling policies, which estimates service rate for each priority queue and serves only highly significant packets with high waiting time during scheduling. Additionally, it offers application-specific reliability through a predictive retransmission and loss recovery policy. During retransmission and loss recovery, it calculates a retransmission rate for each sensor node and retransmits only that amount of packets from each sensor node. It also controls congestion with its dynamic priority-based rate adjustment and packet drop policies. It further provides a concept of time-bound based packet transmission policy that minimizes delay and jitter more appropriately. The second protocol is designed for attaining optimized QoS in the dynamic and assorted PA-WBAN. It applies a Lion Cooperative Hunt Optimization (LCHO) technique for the optimization of multi-objective QoS. Both theoretical and simulation results examine the usefulness of the proposed protocols and illustrate its advantage over the existing protocols.