2,195 research outputs found
The energy problem in resource constrained wireless networks
No full textToday Wireless Sensor Networks are part of a wider scenario involving several wireless and wired communication technology: the Internet Of Things (IoT). The IoT envisions billions of tiny embedded devices, called Smart Objects, connected in a Internet-like structure. Even if the integration of WSNs into the IoT scenario is nowadays a reality, the main bottleneck of this technology is the energy consumption of sensor nodes, which quickly deplete the limited amount of energy of available in batteries. This drawback, referred to as the energy problem, was addressed in a number of research papers proposing various energy optimization approaches to extend sensor nodes lifetime. However, energy problem is still an open issue that prevents the full exploitation of WSN technology.
This thesis investigates the energy problem in WSNs and introduces original solutions trying to mitigate drawbacks related to this phenomenon. Starting from solutions proposed by the research community in WSNs, we deeply investigate critical and challenging factors concerning the energy problem and we came out with cutting-edge low-power hardware platforms, original software energy-aware protocols and novel energy-neutral hardware/software solutions overcoming the state-of-art.
Concerning low-power hardware, we introduce the MagoNode, a new WSN mote equipped with a radio frequency (RF) front-end which enhances radio performance. We show that in real applicative contexts, the advantages introduced by the RF front-end keep packet re-trasmissions and forwards low. Furthermore, we present the ultra low-power Wake-Up Radio (WUR) system we designed and the experimental activity to validate its performance. In particular, our Wake-up Radio Receiver (WRx) features a sensitivity of -50 dBm, has a current consumption of 579nA in idle-listening and features a maximum radio range of about 19 meters. What clearly resulted from the experimental activity is that performance of the WRx is strongly affected by noise. To mitigate the impact of noise on WUR communication we implemented a Forward Error Correction (FEC) mechanism based on Hamming code. We performed several test to determine the effectiveness of the proposed solution. The outcome show that our WUR system can be employed in environment where the Bit Error Rate (BER) induced by noise is up to 10^2, vice versa, when the BER induced by noise is in the order of 10 ́3 or below, it is not worth to use any Forward Error Correction (FEC) mechanism since it does not introduce any advantages compared to uncoded data.
In the context of energy-aware solutions, we present two protocols: REACTIVE and ALBA-WUR. REACTIVE is a low-power over-the-air programming (OAP) protocol we implemented to improve the energy efficiency and lower the image dissemination time of Deluge T2, a well-known OAP protocol implemented in TinyOS. To prove the effectiveness of REACTIVE we compared it to Deluge exploiting a testbed made of MagoNode motes. Results of our experiments show that the image dissemination time is 7 times smaller than Deluge, while the energy consumption drops 2.6 times. ALBA-WUR redesigns ALBA-R protocol, extending it to exploit advantages of WUR technology. We compared ALBA-R and ALBA-WUR in terms of current consumption and latency via simulations. Results show that ALBA-WUR
estimated network lifetime is decades longer than that achievable by ALBA-R. Furthermore, end-to-end packet latency features by ALBA-WUR is comparable to that of ALBA-R.
While the main goal of energy optimization approaches is motes lifetime maximization, in recent years a new research branch in WSN emerged: Energy Neutrality. In contrast to lifetime maximization approach, energy neutrality foresees the perennial operation of the network. This can be achieve only making motes use the harvested energy at an appropriate rate that guarantees an everlasting lifetime. In this thesis we stress that maximizing energy efficiency of a hardware platform dedicated to WSNs is the key to reach energy neutral operation (ENO), still providing reasonable data rates and delays. To support this conjecture, we designed a new hardware platform equipped with our wake-up radio (WUR) system able to support ENO, the MagoNode++. The MagoNode++ features a energy harvester to gather energy from solar and thermoelectric sources, a ultra low power battery and power management module and our WUR system to improve the energy efficiency of wireless communications. To prove the goodness in terms of current consumption of the MagoNode++ we ran a series of experiments aimed to assess its performance. Results show that the MagoNode++ consumes only 2.8 μA in Low Power Mode with its WRx module in listening mode.
While carrying on our research work on solutions trying to mitigate the energy problem, we also faced a challenging application context where the employment of WSNs is considered efficient and effective: structural health monitoring (SHM). SHM deals with the early detection of damages to civil and industrial structures and is emerging as a fundamental tool to improve the safety of these critical infrastructures. In this thesis we present two real world WSNs deployment dedicated to SHM. The first concerned the monitoring of the Rome B1 Underground construction site. The goal was to monitor the structural health of a tunnel connecting two stops. The second deployment concerned the monitoring of the structural health of buildings in earthquake-stricken areas. From the experience gained during these real world deployments, we designed the Modular Monitoring System (MMS). The MMS is a new low-power platform dedicated to SHM based on the MagoNode. We validated the effectiveness of the MMS low-power design performing energy measurements during data acquisition from actual transducers
Reins-MAC: Firefly Inspired Communication Scheduling for Reliable Low-Power Wireless
No full textPervasive sensing and actuation applications are increasingly being built using distributed devices connected with low-power wireless links. Most of these applications exploit anarchic protocols in which devices independently at- tempt to seize communication resources, supporting only best- effort applications as the communication they rely on cannot be guaranteed. For strict quality of service requirements, a few, non-anarchic, disciplined approaches exist in which nodes coordinate and resources are guaranteed to individual devices. Unfortunately, these solutions come at a considerable cost to form and conform to rigid communication schedules while considering the inherent volatility of the wireless environment.
This work proposes REINS-MAC, a fully distributed solution that adapts to changes in the wireless environment and forms a flexible communication schedule able to support quality of service requirements. Inspired by pulse-coupled oscillators, the mathematical formulation of firefly flash synchronization, our approach forms and reserves communication slots of variable size in an online and adaptive manner. REINS-MAC tailors communication resources to network conditions that vary in time and space as well as to the explicit communication needs of devices by enabling distributed, dynamic changes to established schedules. Ultimately, REINS-MAC allows higher level abstractions to rein in the protocol anarchy, laying the foundation for reliable wireless applications
PINCH: Self-Organized Context Neighborhoods for Smart Environments
No full textToday’s “smart” domains are driven by lightweight battery operated devices carried by people and embedded in environments. Many applications rely on con- tinuous neighbor discovery, i.e., the ability to detect other nearby devices. Application uses for neighbor discovery are widely varying, but they all rely on a protocol in which devices exchange periodic beacons containing device identi- fiers. Many applications also ultimately involve assessing and adapting to context information sensed about the physical world and the device’s situation in that world (e.g., its location or speed, the ambient temperature or sound, etc.). In this paper, we define Proactive Implicit Neighborhood Context Heuristics (PINCH), which leverages unused payload in periodic neighbor discovery beacons to opportunistically distribute context information in a local area. PINCH’s self- organizing algorithms use limited local views of the state of a one-hop network neighborhood to determine the most useful type of context information for a device to sense and share. In this paper, we develop the algorithms, integrate an implementation of PINCH with a smart city simulator, and benchmark the tradeoffs of self-organized local context sharing with 2.4GHz neighbor discovery beacons
Dr. Amy Howard – Faculty Author Interview
No full textAmy Howard, executive director of the Bonner Center for Civic Engagement and associated faculty in American studies, discusses her new book, More Than Shelter: Activism and Community in San Francisco Public Housing, published recently by the University of Minnesota Press. Her research and book looks closely at three public housing projects in San Francisco and brings to light the dramatic measures tenants have taken to create communities that mattered to them
A two-prong approach to energy-efficient WSNs: Wake-up receivers plus dedicated, model-based sensing
No full textEnergy neutral operation of WSNs can be achieved by exploiting the idleness of the workload to bring the average power consumption of each node below the harvesting power available. This paper proposes a combination of state-of-the-art low-power design techniques to minimize the local and global impact of the two main activities of each node: sampling and communication. Dynamic power management is adopted to exploit low-power modes during idle periods, while asynchronous wake-up and prediction-based data collection are used to opportunistically activate hardware components and network nodes only when they are strictly required. Furthermore, the concept of “model-based sensing” is introduced to push prediction-based data collection techniques as close as possible to the sensing elements. The results achieved on representative real-world WSN case studies show that the combined benefits of the design techniques adopted is more than linear, providing an overall power reduction of more than three orders of magnitude
On-Demand LoRa: Asynchronous TDMA for Energy Efficient and Low Latency Communication in IoT
No full textEnergy efficiency is crucial in the design of battery-powered end devices, such as smart sensors for the Internet of Things applications. Wireless communication between these distributed smart devices consumes significant energy, and even more when data need to reach several kilometers in distance. Low-power and long-range communication technologies such as LoRaWAN are becoming popular in IoT applications. However, LoRaWAN has drawbacks in terms of (i) data latency; (ii) limited control over the end devices by the gateway; and (iii) high rate of packet collisions in a dense network. To overcome these drawbacks, we present an energy-efficient network architecture and a high-efficiency on-demand time-division multiple access (TDMA) communication protocol for IoT improving both the energy efficiency and the latency of standard LoRa networks. We combine the capabilities of short-range wake-up radios to achieve ultra-low power states and asynchronous communication together with the long-range connectivity of LoRa. The proposed approach still works with the standard LoRa protocol, but improves performance with an on-demand TDMA. Thanks to the proposed network and protocol, we achieve a packet delivery ratio of 100% by eliminating the possibility of packet collisions. The network also achieves a round-trip latency on the order of milliseconds with sensing devices dissipating less than 46 mJ when active and 1.83 μ W during periods of inactivity and can last up to three years on a 1200-mAh lithium polymer battery
Lasso: A device-to-device group monitoring service for smart cities
No full textMany smart city applications involve groups of individuals that wish to
remain together as they move throughout the city. For example, a group of
tourists may be monitored by a tour operator to keep the group together and
on schedule. Alternatively, a group of elementary school children in transit
to school should be closely supervised by an adult to ensure the children
stay safe. This paper presents \lasso, a smartphone-based service that
exploits wireless devices carried by each group member to provide
infrastructure-free group formation and monitoring. We show how smartphones
equipped with Bluetooth Low Energy (BLE) can be used as personal beacons in
a device-to-device group monitoring protocol to allow each user to join a
group and see a distributed view of group membership in real
time. While \lasso is general purpose in nature, we demonstrate
it and evaluate its performance through a prototype application used by a
tourist guide to monitor tour participants
MVSink: Incrementally Building In-Network Aggregation Trees
No full textIn-network data aggregation is widely recognized as an acceptable means to reduce the amount of transmitted data without adversely affecting the quality of the results. To date, most aggregation protocols assume that data from localized regions is correlated, thus they tend to identify aggregation points within these regions. Our work, instead, targets systems where the data sources are largely independent, and over time, the sink requests different combinations of data sources. The combinations are essentially aggregation functions. This problem is significantly different from the localized one because the functions are initially known only by the sink, and the data sources to be combined may be located in any part of the network, not necessarily near one another. This paper describes MVSink, a protocol that lowers the network cost by incrementally pushing the aggregation function as close to the sources as possible, aggregating early the raw data. Our results show between 20% and 30% savings over a simplistic approach in large networks, and demonstrate that a data request needs to be active only for a reasonably short period of time to overcome the cost of identifying the aggregation tree
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