NEURON: Enabling Autonomicity in Wireless Sensor Networks

Zafeiropoulos, Anastasios; Gouvas, Panagiotis; Liakopoulos, Athanassios; Mentzas, Gregoris; Mitrou, Nikolas

doi:10.3390/s100505233

Cited by 7 publications

(2 citation statements)

References 38 publications

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“…In centralized systems, the whole range of sensors and devices is connected to a context server equipped with necessary computing and storage capacity making it simple to add and exchange context offering devices. Chatterjea et al and Jin and Li [15,16] propose that while being a single point of failure, the centralized approach is particularly not suited for CASs because the delay involved in context update might change the context itself at the source, whereas Zafeiropoulos et al [17] take the view that distributed systems offer to use localitybased context acquisition and processing. A comprehensive classification has also been performed byŽontar et al [18] on the basis of such kinds of architecture.…”

Section: Context Awareness and Context Aware Systemsmentioning

confidence: 99%

CRAM: A Conditioned Reflex Action Inspired Adaptive Model for Context Addition in Wireless Sensor Networks

et al. 2016

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In Wireless Sensor Networks (WSNs), Context Awareness is typically realized through Context Aware Systems (CASs). Although almost each CAS follows sense-decide-adapt cycle, the notion of context is hardwired into the applications; that is, when an event is triggered, the sense-decide-actuate cycle runs and performs required actuation. In situations, for instance, whenever the same event is triggered, the cycle produces the same actuation through mechanical use of the same resources, posing the same processing and time. In this paper, we propose CRAM, a context added system in which actuations once performed by the system help it to internally evolve by serving as new contexts. As the system is exposed to more situations overtime, its context repository is enriched through such retrospective contexts, gradually letting it perform internal actuation through improved introspective contexts. This internal actuation leads the system towards the evolution of intelligent processing by reducing the independent function of decision in sense-decide-actuate cycle and merging it with new context. Finally, the system reaches a juncture where recurrence of each event proves to be a stimulus for the system to respond impulsively, through priming memory of introspective contexts, to achieve an imitation of learned reflex action resulting into reduced time and energy expenditure.

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Section: Context Awareness and Context Aware Systemsmentioning

confidence: 99%

CRAM: A Conditioned Reflex Action Inspired Adaptive Model for Context Addition in Wireless Sensor Networks

et al. 2016

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“…This protocol moreover handles dynamic emergency circumstances and capacities commendably with the controlling crevice issue. An endeavor name NEURON projected by [29] has been created to reduce the diserse nature of operation and management, and hold up the spread of data inside future Wireless Sensor Networks. This is an energy capable game plan, clustering and routing segment in Wireless Sensor Networks that spotlights on the joining of programmed functionalities in the present strategies.…”

Section: Trial Arrangement and New-fangled Applicationsmentioning

confidence: 99%

The Up-to-Date Progression and Prospect Drift of Wireless Sensor Networks

Salamah¹

2015

IJAIS

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WSN's have transformed into a champion amongst the most interesting scopes of investigation in the past couple of years. It made out of different wireless sensor nodes which outline a sensor field and a sink. These tremendous amounts of nodes, having the abilities to sense their surroundings, perform limited retribution and confer remotely shape the wireless sensor networks. Late advances in remote and electronic headways have engaged a far reaching mixed bag of exercises of wireless sensor networks in military, movement observation, Traffic, focus taking after, environment watching, healthcare, and whatnot. There are various new challenges that have surfaced for the originators of wireless sensor networks with a particular finished objective to meet the requirements of distinctive applications like identified sums, size of nodes, and its self-sufficiency. Hence, updates in the present developments and better responses for these challenges are required. The future enhancements in sensor nodes must convey successful and economical contraptions, so that they may be brought into play as a piece of usage like submerged acoustic sensor systems, distinguishing based cyber-physical structures, time-critical applications, cognitive recognizing and management of spectrum, and security and assurance services.

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