Abstract. Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a dense, distributed, wireless network of multi-modal resource-poor sensors combined into loosely coherent sensor arrays that perform in situ detection, estimation, compression, and exfiltration. We ground our study in the context of a security scenario called "A Line in the Sand" and accordingly define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking, and middleware services. We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of our work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effects of network unreliability on application performance. Our work includes multiple experimental deployments of over 90 sensors nodes at MacDill Air Force Base in Tampa, Florida, as well as other field experiments of comparable scale. Based on these experiences, we identify a set of key lessons and articulate a few of the challenges facing extreme scaling to tens or hundreds of thousands of sensor nodes.
The role of adenosine A1 receptors (A1R) in reflex-evoked short-circuit current ( I sc) indicative of chloride secretion was studied in the guinea pig colon. The A1R antagonist 8-cyclopentyltheophylline (CPT) enhanced reflex-evoked I sc. Adenosine deaminase and the nucleoside transport inhibitor S-(4-nitrobenzyl)-6-thioinosine enhanced and reduced reflex-induced I sc, respectively. The A1R agonist 2-chloro- N 6-cyclopentyladenosine (CCPA) inhibited reflex-evoked I sc at nanomolar concentrations, and its action was antagonized by CPT. In the presence of either N-acetyl-5-hydroxytryptophyl-5-hydroxytryptophan amide to block the 5-hydroxytryptamine (5-HT)-mediated pathway or piroxicam to block the prostaglandin-mediated pathway, CCPA reduced the residual reflex-evoked I sc. CCPA reduced the response to a 5-HT pulse without affecting the tetrodotoxin-insensitive I sc responses to carbachol or forskolin. Immunoreactivity for A1R was detected in the membrane (10% of neurons) and cytoplasm (90% of neurons) of neural protein gene product 9.5-immunoreactive (or S-100-negative) submucosal neurons, in glia, and in the muscularis mucosa. A1R immunoreactivity in a majority of neurons remained elevated in the cytoplasm despite preincubation with adenosine deaminase or CPT. A1R immunoreactivity colocalized in synaptophysin-immunoreactive presynaptic varicose nerve terminals. The results indicate that endogenous adenosine binding to high-affinity A1R on submucosal neurons acts as a physiological brake to suppress reflex-evoked I scindicative of chloride secretion.
Abstract-In the context of IEEE 802.11b network testbeds, we examine the differences between unicast and broadcast link properties, and we show the inherent difficulties in precisely estimating unicast link properties via those of broadcast beacons even if we make the length and transmission rate of beacons be the same as those of data packets. To circumvent the difficulties in link estimation, we propose to estimate unicast link properties directly via data traffic itself without using periodic beacons. To this end, we design a data-driven routing protocol Learn on the Fly (LOF). LOF estimates link quality based on data traffic, and it chooses routes by way of a locally measurable metric ELD, the expected MAC latency per unit-distance to the destination. Using a realistic sensor network traffic trace and an 802.11b testbed of 195 Stargates, we experimentally compare the performance of LOF with that of existing protocols, represented by the geography-unaware ETX and the geography-based PRD. We find that LOF reduces end-to-end MAC latency by a factor of 3 and enhances energy efficiency by a factor up to 2.37, which demonstrate the feasibility as well as potential benefits of datadriven link estimation and routing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.