Cross-Layer Latency Minimization in Wireless Networks with SINR Constraints

Recently, there has been substantial interest in the design of cross-\ud layer protocols for wireless networks. These protocols optimize\ud certain performance metric(s) of interest (e.g. latency, energy, rate)\ud by jointly optimizing the performance of multiple layers of the\ud protocol stack. Algorithm designers often use geometric-graph-\ud theoretic models for radio interference to design such cross-layer\ud protocols. In this paper we study the problem of designing cross-\ud layer protocols for multi-hop wireless networks using a more real-\ud istic Signal to Interference plus Noise Ratio (SINR) model for radio\ud interference. The following cross-layer latency minimization prob-\ud lem is studied: Given a set V of transceivers, and a set of source-\ud destination pairs, (i) choose power levels for all the transceivers, (ii)\ud choose routes for all connections, and (iii) construct an end-to-end\ud schedule such that the SINR constraints are satisfied at each time\ud step so as to minimize the make-span of the schedule (the time\ud by which all packets have reached their respective destinations).\ud We present a polynomial-time algorithm with provable worst-case\ud performance guarantee for this cross-layer latency minimization\ud problem. As corollaries of the algorithmic technique we show that\ud a number of variants of the cross-layer latency minimization prob-\ud lem can also be approximated efficiently in polynomial time. Our\ud work extends the results of Kumar et al. (Proc. SODA, 2004) and\ud Moscibroda et al. (Proc. MOBIHOC, 2006). Although our algo-\ud rithm considers multiple layers of the protocol stack, it can natu-\ud rally be viewed as compositions of tasks specific to each layer —\ud this allows us to improve the overall performance while preserving\ud the modularity of the layered structure.\u

Approximation Algorithms for Computing Capacity of Wireless Networks with SINR constraints

Abstract—A fundamental problem in wireless networks is to estimate its throughput capacity- given a set of wireless nodes, and a set of connections, what is the maximum rate at which data can be sent on these connections. Most of the research in this direction has focused on either random distributions of points, or has assumed simple graph-based models for wireless interference. In this paper, we study capacity estimation problem using the more general Signal to Interference Plus Noise Ratio (SINR) model for interference, on arbitrary wireless networks. The problem becomes much harder in this setting, because of the non-locality of the SINR model. Recent work by Moscibroda et al. [16], [18] has shown that the throughput in this model can differ from graph based models significantly. We develop polynomial time algorithms to provably approximate the total throughput in this setting. I