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Abstract-In this paper, we address the following two questions concerning the capacity and configuration of fixed wireless networks: (i) given a set of wireless nodes with arbitrary but fixed locations, and a set of data flows, what is the max-min achievable throughput? and (ii) how should the network be configured to achieve the optimum? We consider these questions from a networking standpoint assuming point-to-point links, and employ a rigorous physical layer model to model conflict relationships between them. Since we seek capacity results, we assume that the network is operated using an appropriate schedule of conflict-free link activations. We develop and investigate a novel optimization framework to determine the optimal throughput and configuration, i.e., flow routes, link activation schedules and physical layer parameters. Determining the optimal throughput is a computationally hard problem, in general. However, using a smart enumerative technique we obtain numerical results for several different scenarios of interest. We obtain several important insights into the structure of the optimal routes, schedules and physical layer parameters. Besides determining the achievable throughput, we believe that our optimization-based framework can also be used as a tool, for configuring scheduled wireless networks, such as those based on IEEE 802.16.Index Terms-Capacity, fixed wireless networks, IEEE 802.16, mesh networks, optimal scheduling and routing.

Abstract-In wireless communications, the desired wireless signal is typically decoded by treating the sum of all the other ongoing signal transmissions as noise. In the networking literature, this phenomenon is typically abstracted using a wireless channel interference model. The level of detail in the interference model, evidently determines the accuracy of the results based upon the model. Several works in the networking literature have made use of simplistic interference models, e.g., fixed ranges for communication and interference, the capture threshold model (used in the ns2 network simulator), the protocol model, and so on. At the same time, fairly complex interference models such as those based on the SINR (signal-to-interference-and-noise ratio) have also been proposed and used. We investigate the impact of the choice of the interference model, on the conclusions that can be drawn regarding the performance of wireless networks, by comparing different wireless interference models. We find that both in the case of random access networks, as well as in the case of scheduled networks (where node transmissions are scheduled to be completely conflict-free), different interference models can produce significantly different results. Therefore, a lot of caution should be exercised before accepting or interpreting results based on simplified interference models. Further, we feel that an SINR-based model is the minimum level of detail that should be employed to model wireless channel interference in a networking context.

In a wireline network, nodes form links with only those nodes they are wired to, and the links do not interfere with one another. In contrast, in a wireless network, signal transmissions are intrinsically broadcast, and suffer from mutual interference. In several physical layer technologies, a wireless signal is decoded by treating the sum of all the other on-going signal transmissions as noise. Hence, from a networking standpoint, there is a need to model wireless channel interference. An accurate interference model is especially important in a multi-hop network context, since there could be several simultaneous wireless transmissions. Several works in the literature have made use of simplified interference models. Some works assume a fixed range for communication and interference, while others are based on concepts like capture threshold where the desired signal strength is compared with interference from a single node at a time, rather than cumulatively. In particular, the latter model is used in ns2 which is the most common simulation tool. Under isotropic pathloss, the capture threshold model is also equivalent to the protocol model proposed by Gupta and Kumar, which is now the subject of a lot of analytical activity notably through conflict graph based problem formulations. We investigate the accuracy and appropriateness of the capture threshold based interference model, by comparing it with one based on the SINR (signal-to-interference-and-noise ratio) with additive interference calculation. We find that both in the case of random access networks, as well as in the case of scheduled networks (where node transmissions are scheduled to be completely conflict-free), a simplified interference model such as the capture threshold model, can produce significantly different results compared to an additive interference based model. Therefore, a lot of caution should be exercised before accepting or interpreting results based on simplified interference models.

The naturally occurring Amaryllidaceae alkaloid pancratistatin exhibits potent apoptotic activity against a large panel of cancer cells lines and has an insignificant effect on noncancerous cell lines, although with an elusive cellular target. Many current chemotherapeutics induce apoptosis via genotoxic mechanisms and thus have low selectivity. The observed selectivity of pancratistatin for cancer cells promoted us to consider the hypothesis that this alkaloid targets cancer cell mitochondria rather than DNA or its replicative machinery. In this study, we report that pancratistatin decreased mitochondrial membrane potential and induced apoptotic nuclear morphology in p53-mutant (HT-29) and wild-type p53 (HCT116) colorectal carcinoma cell lines, but not in noncancerous colon fibroblast (CCD-18Co) cells. Interestingly, pancratistatin was found to be ineffective against mtDNA-depleted (r 0 ) cancer cells. Moreover, pancratistatin induced cell death in a manner independent of Bax and caspase activation, and did not alter b-tubulin polymerization rate nor cause double-stranded DNA breaks. For the first time we report the efficacy of pancratistatin in vivo against human colorectal adenocarcinoma xenografts. Intratumor administration of pancratistatin (3 mg/kg) caused significant reduction in the growth of subcutaneous HT-29 tumors in Nu/Nu mice (n ¼ 6), with no apparent toxicity to the liver or kidneys as indicated by histopathologic analysis and terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling. Altogether, this work suggests that pancratistatin may be a novel mitochondria-targeting compound that selectively induces apoptosis in cancer cells and significantly reduces tumor growth.