000130854 001__ 130854 000130854 005__ 20240201151018.0 000130854 0247_ $$2doi$$a10.1155/2013/136745 000130854 0248_ $$2sideral$$a81683 000130854 037__ $$aART-2013-81683 000130854 041__ $$aeng 000130854 100__ $$0(orcid)0000-0002-6377-5319$$aAsensio, Á. 000130854 245__ $$aHardware architecture design for WSN runtime extension 000130854 260__ $$c2013 000130854 5060_ $$aAccess copy available to the general public$$fUnrestricted 000130854 5203_ $$aInternet of Things imposes demanding requirements on wireless sensor networks as key players in context awareness procurement. Temporal and spatial ubiquities are one of the essential features that meet technology boundaries in terms of energy management. Limited energy availability makes anywhere and anytime sensing a challenging task that forces sensor nodes to wisely use every bit of available power. One of the earliest and most determining decisions in the electronic design stage is the choice of the silicon building blocks that will conform hardware architecture. Designers have to choose between dual architectures (based on a low-power microcontroller controlling a radio module) and single architectures (based on a system on chip). This decision, together with finite state machine design and application firmware, is crucial to minimize power consumption while maintaining expected sensor node performance. This paper provides keys for energy analysis of wireless sensor node architecture according to the specific requirements of any application. It thoroughly analyzes pros and cons of dual and single architectures providing designers with the basis to select the most efficient for each application. It also provides helpful considerations for optimal sensing-system design, analyzing how different strategies for sensor measuring and data exchanging affect node energy consumption. 000130854 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000130854 590__ $$a0.923$$b2013 000130854 591__ $$aTELECOMMUNICATIONS$$b50 / 78 = 0.641$$c2013$$dQ3$$eT2 000130854 591__ $$aCOMPUTER SCIENCE, INFORMATION SYSTEMS$$b76 / 134 = 0.567$$c2013$$dQ3$$eT2 000130854 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000130854 700__ $$0(orcid)0000-0003-2286-9762$$aBlasco, R. 000130854 700__ $$0(orcid)0000-0002-7396-7840$$aMarco, Á.$$uUniversidad de Zaragoza 000130854 700__ $$0(orcid)0000-0001-5316-8171$$aCasas, R.$$uUniversidad de Zaragoza 000130854 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát. 000130854 7102_ $$15008$$2785$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Tecnología Electrónica 000130854 773__ $$g9, 4 (2013), [11 pp.]$$pInt. J. Distrib. Sens. Netw.$$tInternational Journal of Distributed Sensor Networks$$x1550-1329 000130854 8564_ $$s824751$$uhttps://zaguan.unizar.es/record/130854/files/texto_completo.pdf$$yVersión publicada 000130854 8564_ $$s2699619$$uhttps://zaguan.unizar.es/record/130854/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000130854 909CO $$ooai:zaguan.unizar.es:130854$$particulos$$pdriver 000130854 951__ $$a2024-02-01-14:34:26 000130854 980__ $$aARTICLE