Distributed throughput-optimal scheduling framework with delay analysis in multi-hop wireless networks

In wireless networks, due to the shared medium, we require sophisticated algorithms to schedule concurrent transmissions that meet the interference constraint where two nodes cannot transmit simultaneously in a guaranteed interference range of each other. For the general ( K -hop) interference model,11 s the generalization of the interference model where two nodes cannot transmit simultaneously if they are within K-hop neighbors of each other due to the shared wireless medium. ially with K ≥ 2 , the throughput-optimal centralized scheduler needs to solve a NP-Hard problem. It leads to the desire of a distributed, low-complexity but throughput-optimal scheduling algorithm. Inspired by this problem, we generalize a randomized scheduling framework for a K -hop interference model and prove that any scheduling algorithm can achieve the capacity of the system if it satisfies the constraints of this framework. Then, we develop two randomized distributed scheduling algorithms which can be integrated into this framework. In spite of having the constant time-complexity, the first proposed algorithm can lead to the exponential growth of the network delay. The second one is a maximal matching algorithm having better delay performance with polynomial growth of delay in the network size. We also show that the whole time-complexity of this randomized distributed scheduling framework is polynomial in network size with any finite value of K .