Local heuristic for the refinement of multi-path routing in wireless mesh networks

We consider wireless mesh networks and the problem of routing end-to-end traffic over multiple paths for the same origin-destination pair with minimal interference. We introduce a heuristic for path determination with two distinguishing characteristics. First, it works by refining an extant set of paths, determined previously by a single- or multi-path routing algorithm. Second, it is totally local, in the sense that it can be run by each of the origins on information that is available no farther than the node's immediate neighborhood. We have conducted extensive computational experiments with the new heuristic, using AODV and OLSR, as well as their multi-path variants, as underlying routing methods. For two different CSMA settings (as implemented by 802.11) and one TDMA setting running a path-oriented link scheduling algorithm, we have demonstrated that the new heuristic is capable of improving the average throughput network-wide. When working from the paths generated by the multi-path routing algorithms, the heuristic is also capable to provide a more evenly distributed traffic pattern

How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution

Clearing the Rf Smog: Making 802.11 Robust to Cross-Technology Interference

Recent studies show that high-power cross-technology interference is becoming a major problem in today’s 802.11 networks. Devices like baby monitors and cordless phones can cause a wireless LAN to lose connectivity. The existing approach for dealing with such high-power interferers makes the 802.11 network switch to a different channel; yet the ISM band is becoming increasingly crowded with diverse technologies, and hence many 802.11 access points may not find an interference-free channel. This paper presents TIMO, a MIMO design that enables 802.11n to communicate in the presence of high-power cross-technology interference. Unlike existing MIMO designs, however, which require all concurrent transmissions to belong to the same technology, TIMO can exploit MIMO capabilities to decode in the presence of a signal from a different technology, hence enabling diverse technologies to share the same frequency band. We implement a prototype of TIMO in GNURadio-USRP2 and show that it enables 802.11n to communicate in the presence of interference from baby monitors, cordless phones, and microwave ovens, transforming scenarios with a complete loss of connectivity to operational networks.National Science Foundation (U.S.) (NSF grant CNS-0831660)National Science Foundation (U.S.) (NSF grant CNS- 0721857)United States. Defense Advanced Research Projects Agency (DARPA ITMANET