Funneling-MAC: A localized, sink-oriented MAC for boosting fidelity in sensor networks

Sensor networks exhibit a unique funneling effect which is a product of the distinctive many-to-one, hop-by-hop traffic pattern found in sensor networks, and results in a significant increase in transit traffic intensity, collision, congestion, packet loss, and energy drain as events move closer toward the sink. While network (e.g., congestion control) and application techniques (e.g., aggregation) can help counter this problem they cannot fully alleviate it. We take a different but complementary approach to solving this problem than found in the literature and present the design, implementation, and evaluation of a localized, sink-oriented, funneling-MAC capable of mitigating the funneling effect and boosting application fidelity in sensor networks. The funneling-MAC is based on a CSMA/CA being implemented network-wide, with a localized TDMA algorithm overlaid in the funneling region (i.e., within a small number of hops from the sink). In this sense, the funneling-MAC represents a hybrid MAC approach but does not have the scalability problems associated with the network-wide deployment of TDMA. The funneling-MAC is 'sink-oriented' because the burden of managing the TDMA scheduling of sensor events in the funneling region falls on the sink node, and not on resource limited sensor nodes; and it is 'localized' because TDMA only operates locally in the funneling region close to the sink and not across the complete sensor field. We show through experimental results from a 45 mica-2 testbed that the funneling-MAC mitigates the funneling effect, improves throughput, loss, and energy efficiency, and importantly, significantly outperforms other representative protocols such as B-MAC, and more recent hybrid TDMA/CSMA MAC protocols such as Z-MAC. Copyright 2006 ACM

Cleaning Transferred Graphene for Optimization of Device Performance

Much has been made of the potential electrical properties of graphene, but still in many cases, unintentional doping leads to these not being fully realised. In the processing of graphene, the step which leads to most of this doping is the transfer from the growth substrate leaving unwanted chemical residue on the graphene surface. A comparison of the most commonly used techniques used to remove this residue is presented showing that most effective cleaning can be obtained using ionic solutions rather than the more commonly used organic solvents. The physical and electrical properties of graphene treated using these solutions are assessed by a combination of Atomic Force Microscopy (AFM), Raman Spectroscopy, Kelvin-Probe Force Microscopy (KPFM) and contact resistance/charge neutrality point (CNP) measurements, and it is shown how to remove residue effectively and reduce contact resistance without adversely affecting the graphene