Efficient resource management in Multimedia Internet of Things

Abstract Multimedia Internet of Things (MIoT) refers to IP-enabled Wireless Multimedia Sensor Networks (WMSN) which are used to retrieve, not only scalar data, but also video and audio streams, and still images from the physical environment. Despite the prominent growth in demand of MIoT, several technical challenges still arise when dealing with practical deployments of WMSN. Most technical challenges in MIoT-and IoT in general-are, one way or another, related to the constrained nature of devices. This thesis provides novel contributions towards optimizing the most precious resource of wireless multimedia sensor nodeꟷthe energy. First, the dissertation proposes sleepyCAM power management model, which uses hierarchy in sensor-node architecture to minimize the idle power consumption of a camera node. Second, a prototype is developed to realize the energy saving potential of sleepyCAM in an event driven live video streaming application. Third, a heterogeneous multi-tier WMSN is developed to improve idle power consumption of camera nodes in large scale deployment. It applies hierarchy in sensor-network design, where low-power sensor nodes wake up more energy-consuming multimedia sensor nodes only when needed. A simple power consumption model is also formulated and applied to estimate the battery-life of MIoT devices. Finally, this thesis offers solutions to enhance manageability and service orchestration of WMSN software using container based virtualization, and study their energy implications. The measurement results show that both hierarchy in sensor-node and multi-tier network architecture significantly reduce the idle power consumption of WMSNs. Moreover, the empirical results also indicate that containers add fixed overhead during the boot-up and shutdown phase of the cameras, but nevertheless, have negligible impact during the video streaming session.Tiivistelmä Multimediakyvykkäällä esineiden internetillä (Multimedia IoT, MIoT) viitataan IP-pohjaisiin langattomiin sensoriverkkoihin, jotka kykenevät perinteisen skalaarisen sensoridatan lisäksi tallentamaan ympäristöstään myös video- ja ääni- ja kuvadataa. Vaikka multimediakyvykkään esineiden internetin tarve kasvaa jatkuvasti useilla alueilla, teknologian kannattavan hyödyntämisen tiellä on vielä useita haasteita. Suurin osa näistä haasteista liittyy tavalla tai toisella esineiden internetin laitteiden rajoitettuun laitteisto- ja energiakapasiteettiin. Tämä väitöskirja esittelee uusia tapoja multimediakyvykkään esineiden internetin energiatehokkuuden parantamiseen, sillä esineiden internetin laitteiden käytettävissä oleva energiakapasiteetti on tyypillisesti erittäin rajallinen. Työn ensimmäisessä vaiheessa kehitettiin hierarkkinen sensorilaitearkkitehtuuri, sleepyCAM, joka tähtää kameralaitteen valmiustilan energiankulutuksen minimointiin herättämällä laitteen enemmän energiaa kuluttavat multimediasensoritoiminnot vain tarvittaessa. Työn seuraavassa vaiheessa sleepyCAM-mallista kehitettiin prototyyppi, jolla tutkittiin mallin energiansäästöpotentiaalia todellisen maailman videovalvontasovelluksessa. Kolmannessa vaiheessa kehitettiin hierarkkinen sensoriverkkoarkkitehtuuri, jossa matalamman energiatason sensorilaitteet herättävät enemmän energiaa kuluttavia multimediasensorilaitteita vain tarvittaessa, mikä parantaa valmiustilan energiatehokkuutta laajemmissa multimediasensoriverkoissa. Työssä kehitettiin myös yksinkertainen energiankulutusmalli multimediakyvykkäiden esineiden internetin laitteiden akunkeston arviointiin. Lopuksi väitöskirjassa tutkittiin multimediasensoriverkon palveluiden hallittavuuden parantamista konttipohjaisella orkestroidulla virtualisoinnilla sekä tutkittiin ratkaisun vaikutuksia energiankulutukseen. Prototyypeillä tehdyt todellisen maailman mittaukset osoittavat, että sekä sleepyCAM että hierarkkinen verkkoarkkitehtuuri vähentävät huomattavasti multimediasensorijärjestelmän kokonaisenergiankulutusta. Tulokset osoittavat myös, että virtualisoinnin käyttö lisää energiankulutusta videosensorilaitteen käynnistyksen ja sammutuksen yhteydessä, mutta videonsiirron aikana konttipohjaisen virtualisoinnin vaikutus energiankulutukseen on olematon

sleepyCAM:power management mechanism for wireless video-surveillance cameras

Abstract In this paper, we propose an energy efficient motion detection and power management mechanism, called sleepyCAM, for wireless camera sensor nodes that do not otherwise support low-power modes. In the proposed solution, a low-power sensor node accompanied with a Pyroelectric Infrared (PIR) sensor and a relay is used to detect motion and manage the power usage of a high-power and high-resolution camera sensor node. To validate our work, we used two baseline benchmarks for comparison that are commonly used as motion detection mechanisms on wireless surveillance cameras: (a) hardware based motion detection using a PIR sensor and (b) software based motion detection using video frame comparison. The main contributions of this paper are the prototype implementation of the sleepyCAM, the surveillance application and the comparison of power consumption between the proposed and the baseline methods. The measurement results indicate that the power consumption of a surveillance camera node can be reduced significantly with the proposed mechanism

Energy consumption analysis of high quality multi-tier wireless multimedia sensor network

Abstract Video surveillance is one of the promising applications of the Internet of Things paradigm. We see heterogeneous deployment of sensor platforms in a multi-tier network architecture as a key enabler for energy optimization of battery powered high-quality video surveillance applications. In this paper, we propose a heterogeneous wireless multimedia sensor network (WMSN) prototype composed of constrained low-power scalar sensor nodes and single board computers (SBCs). Whereas constrained nodes are used for preliminary motion detection, more capable SBCs are used as camera nodes. The camera nodes stream full HD (1080 pixels) video to a remote laptop during occurrence of an event (when motion is detected). We also present a simple power model and simulation results of battery life of the motes for variable event interval and event duration

Energy efficient event driven video streaming surveillance using sleepyCAM

Abstract Wireless Multimedia Sensor Networks (WMSN) are one of the emerging paradigms of the Internet of Things (IoT) that are used to retrieve content including scalar data, video and audio streams and still images from the physical environment. In contrast to scalar sensor (such as temperature and humidity sensor) nodes, multimedia sensor nodes capture high volumes of data and perform far more complex tasks that can be highly power consuming. In this paper, we present the design of energy efficient high resolution camera sensor node, that is capable of capturing a full HD video at 30fps, using off-the-shelf hardware for an event driven video streaming surveillance application. In order to achieve long battery life, we use an energy efficient motion detection and power management mechanism, called sleepyCAM, which uses a lowpower scalar sensor node to detect motion and wake-up a high resolution camera node when needed. We used Libellium Waspmote platform and raspberry pi (RPi) to implement the functionality of the low-power sensor node and the HD camera node, respectively. We validate our work using a baseline setup on a standby RPi that uses scalar sensor for motion detection. The results demonstrate that with the used hardware platform, the power consumption can be reduced by more than 99%

Energy consumption analysis of edge orchestrated virtualized wireless multimedia sensor networks

Abstract Virtualization enabled by container-based technologies is a recently emerging concept in the integration of Internet of Things (IoT) and cloud computing. Due of their lightweight nature, container-based virtualization tools improve manageability of cloud-based IoT solutions by making it possible to update application software on the fly. Although different studies have demonstrated the feasibility of efficiently running container-based virtualization on low-power IoT nodes, the implication of doing so on battery-powered nodes has been overlooked. In this paper, we investigate how much energy overhead is generated by Docker-based virtualization on battery powered camera sensor nodes. In our scenario, camera nodes are most of the time in “power off”state to save energy. They are switched on for streaming video only when activity is detected by motion sensor nodes. By means of empirical measurement and subsequent analysis, we found that starting and closing of containers in the Docker platform adds-up roughly 13 percent power consumption overhead during the boot-up and shutdown of the camera nodes. Furthermore, the fixed overhead occurring from boot-up and shutdown procedures become negligible with longer video stream sessions