Transmission Control under Multi-Service Disciplines in Wireless Sensor Networks

The wireless sensor network(WSN),as the terminal data acquisition system of the 5G network,has attracted attention due to advantages such as low cost and easy deployment.Its development is mainly restricted by energy.The traditional transmission control scheme is not suitable for WSNs due to the significant information interaction.A switchable transmission control scheme for WSNs based on a queuing game(SQGTC)is proposed to improve network performance.Considering that sensor nodes compete for the resources of sink nodes to realize data transmission,the competitive relationship between nodes is described from the perspective of a game.Different types of sensor node requests require a sink node to provide different service disciplines.Mathematical models of social welfare are established for a sink node under the service disciplines of first-come,first-served(FCFS),egalitarian processor sharing(EPS),and shortest service first(SSF).The optimal service strategies are obtained by maximizing social welfare.The sensor nodes provide the expected benefits and satisfy the service requirements of the requests,and the sink node switches the transmission control strategy for the service.Simulation results show that the proposed scheme improves the data transmission efficiency of WSNs and achieves the optimal allocation of resources.

On the Strong Approximation for a Simple Reentrant Line in Light Traffic Under First-buffer First-served Service Discipline

For a 2-station and 3-class reentrant line under first-buffer first-served(FBFS)service discipline in light traffic,we firstly construct the strong approximations for performance measures including the queue length,workload,busy time and idle time processes.Based on the obtained strong approximations,we use a strong approximation method to find all the law of the iterated logarithms(LILs)for the above four performance measures,which are expressed as some functions of system parameters:means and variances of interarrival and service times,and characterize the fluctuations around their fluid approximations.

On the Fluid Approximation for a Multiclass Queue under Non-Preemptive SBP Service Discipline

A multi-class single server queue under non-preemptive static buffer priority （SBP） service discipline is considered in this paper. Using a bounding technique, we obtain the fluid approximation for the queue length and busy time processes. Furthermore, we prove that the convergence rate of the fluid approximation for the queue length and busy time processes is exponential for large N. Additionally, a sufficient condition for stability is obtained.

Strong Approximations for a Kumar-Seidman Network under a Priority Service Discipline

In this paper,we derive the strong approximations for a four-class two station multi-class queuing network（Kumar-Seidman network） under a priority service discipline.Within a group,jobs are served in the order of arrival,that is,a first-in-first-out disciple,and among groups,jobs are served under a pre-emptiveresume priority disciple.We show that if the input data（i.e.,the arrival and service processe） satisfy an approximation（such as the functional law-of-iterated logarithm approximation or the strong approximation）,the output data（the departure processes） and the performance measures（such as the queue length,the work load and the sojourn time process） satisfy a similar approximation.