Service Centric Scheduling With Strict Deadlines

Wireless networks are evolving to meet the needs of transforming wireless services. The demands of wireless service users should guide the evolution of networks to be service centric, meaning towards greater and more efficient service provisioning capabilities. Users commonly abandon delayed services and many services are rendered useless due to delay. Such delays can be caused by collisions or the stochastic nature of wireless networks. Through scheduling, a wireless network can overcome these obstacles. To meet the need for timely services, we present a service centric scheduling framework aimed at maximizing service payoffs under strict deadlines. We consider three scenarios for the amount of network information available for scheduling: full, local, and statistical. An optimization framework under full network information is presented along with a method for deriving the optimal solution. With local information scenario, which is a more practical consideration than full information, we present a greedy strategy and an approach via optimal stopping theory to derive an optimal threshold to minimize the time to transmission. A fixed scheme and an opportunistic scheme are presented under the assumption that statistical network information is available alongside local information. Our opportunistic scheme maximizes the average service payoff. A complexity reducing technique which potentially decreases the required computations to make the optimal opportunistic decision is also presented. We evaluate the performance of the various schemes via simulations.