The back-pressure algorithm is a well-known throughput-optimal algorithm. However, its delay performance may be quite poor even when the traffic load is not close to network capacity due to the following two reasons. First, each node has to maintain a separate queue for each commodity in the network, and only one queue is served at a time. Second, the backpressure routing algorithm may route some packets along very long routes. In this paper, we present solutions to address both of the above issues, and hence, improve the delay performance of the back-pressure algorithm. One of the suggested solutions also decreases the complexity of the queueing data structures to be maintained at each node.

This paper proposes a new class of simple, distributed algorithms for scheduling in wireless networks. The algorithms generate new schedules in a distributed manner via simple local changes to existing schedules. The class is parameterized by integers k ≥ 1. We show that algorithm k of our class achieves k/(k + 2) of the capacity region, for every k ≥ 1.The algorithms have small and constant worst-case overheads: in particular, algorithm k generates a new schedule using (a) time less than 4k + 2 round-trip times between neighboring nodes in the network, and (b) at most three control transmissions by any given node, for any k. The control signals are explicitly specified, and face the same interference effects as normal data transmissions.Our class of distributed wireless scheduling algorithms are the first ones guaranteed to achieve any fixed fraction of the capacity region while using small and constant overheads that do not scale with network size. The parameter k explicitly captures the tradeoff between control overhead and scheduler throughput performance and provides a tuning knob protocol designers can use to harness this trade-off in practice.

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Abstract-The back-pressure algorithm is a well-known throughput-optimal algorithm. However, its implementation requires that each node has to maintain a separate queue for each commodity in the network, and only one queue is served at a time. This fact may lead to a poor delay performance even when the traffic load is not close to network capacity. Also, since the number of commodities in the network is usually very large, the queueing data structure has to be maintained at each node is respectively complex. In this paper, we present a solution to address both of the above issues in the case of fixed-routing network scenario where the route of each flow is chosen upon arrival. Our proposed architecture allows each node to maintain only per-neighbor queues, and moreover, improves the delay performance of the back-pressure algorithm.

This paper proposes a new class of simple, distributed algorithms for scheduling in multihop wireless networks under the primary interference model. The class is parameterized by integers 1. We show that algorithm of our class achieves ( + 2) of the capacity region, for every 1. The algorithms have small and constant worst-case overheads. In particular, algorithm generates a new schedule using a) time less than 4 + 2 round-trip times between neighboring nodes in the network and b) at most three control transmissions by any given node for any . The control signals are explicitly specified and face the same interference effects as normal data transmissions. Our class of distributed wireless scheduling algorithms are the first ones guaranteed to achieve any fixed fraction of the capacity region while using small and constant overheads that do not scale with network size. The parameter explicitly captures the tradeoff between control overhead and throughput performance and provides a tuning-knob protocol designers can use to harness this tradeoff in practice.