This paper presents an efficient hierarchical 3D capacitance extraction algorithm - ICCAP. Most previous capacitance extraction algorithms introduce intermediate variables to facilitate the hierarchical potential calculation but still preserve the leaf panels as the basis. In this paper, we discover that those intermediate variables are fundamentally much better basis than leaf panels. As a result, we are able to explicitly construct the sparse potential coefficient matrix and solve it with linear memory in linear runtime. Furthermore, the explicit sparse formulation not only enables the usage of preconditioned iterative Krylov subspace methods but also the reordering technique. A new reordering technique is proposed to further reduce over 20% of memory consumption and runtime in comparison to no reordering techniques applied. Experimental results demonstrate the superior runtime and memory consumption of ICCAP over previous approaches while achieving similar accuracy.

To evaluate the behavior of TCP on a path with a wireless link, we build a wireline-wireless network model, and assume the wireless link is the bottleneck which causes packets to be buffered at the wireline-wireless interface buffer. A reliable link layer protocol is assumed on the wireless link which hides the fluctuations of the wireless medium from TCP. We first build the link layer model and the wireless channel Markov chain model, and use the matrix geometric method to evaluate the packet loss probability. We then analyze the long-term steady-state send rate and throughput of a TCP connection.