Performance Analysis of IP based WSNs in real time systems

Wireless sensor networks (WSNs) are the key enablers of the internet of things (IoT) paradigm. Traditionally, sensor network research has been to be unlike the internet, motivated by power and device constraints. The IETF 6LoWPAN draft standard changes this, defining how IPv6 packets can be efficiently transmitted over IEEE 802.15.4 radio links. Due to this 6LoWPAN technology, low power, low cost micro- controllers can be connected to the internet forming what is known as the wireless embedded internet. Another IETF recommendation, CoAP allows these devices to communicate interactively over the internet. The integration of such tiny, ubiquitous electronic devices to the internet enables interesting real-time applications. This thesis work attempts to evaluate the performance of a stack consisting of CoAP and 6LoWPAN over the IEEE 802.15.4 radio link using the Contiki OS and Cooja simulator, along with the CoAP framework Californium (Cf). Ultimately, the implementation of this stack on real hardware is carried out using a raspberry pi as a border router with T-mote sky sensors as slip radios and CoAP servers relaying temperature and humidity data. The reliability of the stack was also demonstrated during scalability analysis conducted on the physical deployment. The interoperability is ensured by connecting the WSN to the global internet using different hardware platforms supported by Contiki and without the use of specialized gateways commonly found in non IP based networks. This work therefore developed and demonstrated a heterogeneous wireless sensor network stack, which is IP based and conducted performance analysis of the stack, both in terms of simulations and real hardware.

Interface Implementation for GPRS/PCU Software Testing with Emulators

Jatkuvasti lisääntyvä matkapuhelinten käyttäjien määrä, internetin kehittyminen yleiseksi tiedon ja viihteen lähteeksi on luonut tarpeen palvelulle liikkuvan työaseman liittämiseksi tietokoneverkkoihin. GPRS on uusi teknologia, joka tarjoaa olemassa olevia matka- puhelinverkkoja (esim. NMT ja GSM) nopeamman, tehokkaamman ja taloudellisemman liitynnän pakettidataverkkoihin, kuten internettiin ja intranetteihin. Tämän työn tavoitteena oli toteuttaa GPRS:n paketinohjausyksikön (Packet Control Unit, PCU) testauksessa tarvittavat viestintäajurit työasemaympristöön. Aidot matkapuhelinverkot ovat liian kalliita, eikä niistä saa tarvittavasti lokitulostuksia, jotta niitä voisi käyttää GPRS:n testauksessa ohjelmiston kehityksen alkuvaihessa. Tämän takia PCU-ohjelmiston testaus suoritetaan joustavammassa ja helpommin hallittavassa ympäristössä, joka ei aseta kovia reaaliaikavaatimuksia. Uusi toimintaympäristö ja yhteysmedia vaativat PCU:n ja muiden GPRS-verkon yksiköiden välisistä yhteyksistä huolehtivien ohjelman osien, viestintäajurien uuden toteutuksen. Tämän työn tuloksena syntyivät tarvittavien viestintäajurien työasemaversiot. Työssä tarkastellaan eri tiedonsiirtotapoja ja -protokollia testattavan ohjelmiston vaateiden, toteutetun ajurin ja testauksen kannalta. Työssä esitellään kunkin ajurin toteuttama rajapinta ja toteutuksen aste, eli mitkä toiminnot on toteutettu ja mitä on jätetty pois. Ajureiden rakenne ja toiminta selvitetään siltä osin, kuin se on oleellista ohjelman toiminnan kannalta.

Analyzing change in medication use - statistical approaches

The objective of this study was to gain an understanding of the effects of population heterogeneity, missing data, and causal relationships on parameter estimates from statistical models when analyzing change in medication use. From a public health perspective, two timely topics were addressed: the use and effects of statins in populations in primary prevention of cardiovascular disease and polypharmacy in older population. Growth mixture models were applied to characterize the accumulation of cardiovascular and diabetes medications among apparently healthy population of statin initiators. The causal effect of statin adherence on the incidence of acute cardiovascular events was estimated using marginal structural models in comparison with discrete-time hazards models. The impact of missing data on the growth estimates of evolution of polypharmacy was examined comparing statistical models under different assumptions for missing data mechanism. The data came from Finnish administrative registers and from the population-based Geriatric Multidisciplinary Strategy for the Good Care of the Elderly study conducted in Kuopio, Finland, during 2004–07. Five distinct patterns of accumulating medications emerged among the population of apparently healthy statin initiators during two years after statin initiation. Proper accounting for time-varying dependencies between adherence to statins and confounders using marginal structural models produced comparable estimation results with those from a discrete-time hazards model. Missing data mechanism was shown to be a key component when estimating the evolution of polypharmacy among older persons. In conclusion, population heterogeneity, missing data and causal relationships are important aspects in longitudinal studies that associate with the study question and should be critically assessed when performing statistical analyses. Analyses should be supplemented with sensitivity analyses towards model assumptions.