The global demand for ubiquitous Internet access is expected to generate a 7-fold growth of the mobile data traffic from 2016 to 2021, which will account for 20% of the global data traffic by 2021. This increasing demand for wireless spectrum requires researchers to look for alternate communication architectures, technologies and protocols capable of addressing the expected high density and the requirements of mobile devices. From this perspective, with the increasing availability of mobile devices that natively support ad hoc communication protocols, we are presented with a unique opportunity to realize large scale ad hoc wireless networks.

Several studies have shown that using an ad hoc communication technology to support (or even substitute) a traditional infrastructure-based network, has the potential to improve the spectral efficiency, reduce the communication delay and increase the device battery life. Nevertheless, ad hoc communications also introduce different complications in the design of efficient networking protocols, most of which are still considered open research problems. As a result, suitable tools for the design, optimization and evaluation of mobile ad hoc networks are required to drive the development of the next generation communication systems.

While several attempts have been made by the research community to fill these needs, on one side 1) the network design and optimization rely on simplifications and, most of the time, unrealistic assumptions in order to overcome the enormous complexity introduced by the large state space of the system and its stochastic and distributed nature, while, on the other side, 2) the evaluation of the systems and protocols mainly rely on simulations. In addition, 3) it is not possible to define a general and global optimization criteria due to the complex interplay between the system variables. Thus, most of the contributions focus on designing and optimizing particular system operations under specific scenarios, and propose protocols that are not able to adapt to changes in network conditions or optimization criteria.

Main Contributions:

During my research career, I have tackled the problem of designing and optimizing the communications in a mobile ad hoc network from different perspectives. In particular, in [O1] I devised optimal and heuristic cooperative communication techniques based on virtual MIMO communications, while in [O2] I focused on spectrum leasing via cooperative routing techniques, and pure MIMO communications in [O3]. I studied the problem of dynamically and jointly optimizing the source coding and transmission strategies for time-varying channels and sources in [O4]. These works gave me an extensive knowledge of different signal processing and optimization techniques and, at the same time, they made me realize that there is a need for a general framework that is able to exploit the similarities between different optimization problems when designing networking protocols.

Similarly, practical implementation works like [O5] made clear that there is a need to share information between different layers of the protocol stack. The latter, combined with the work in [O6] and my active involvement as a maintainer for the open source project Network Simulator 3 (ns-3), posed the basis for developing a way to easily transition from simulation to real life experimentation.

Finally, I proposed and implemented a system architecture that combines a mobile application with a web application to gather device and network characteristics through ad hoc communications, and visualize this information on a map. In addition, this system allows the user to interact with the ad hoc network and change device and network characteristics on the fly.

Selected Publications:

[O1] M. Rossi, C. Tapparello and S. Tomasin, On Optimal Cooperator Selection Policies for Multi-Hop Ad Hoc Networks, IEEE Transactions on Wireless Communications, Vol. 10, No. 2, February 2011, pp. 506-518. Code
Abstract: In this paper we consider wireless cooperative multihop networks, where nodes that have decoded the message at the previous hop cooperate in the transmission toward the next hop, realizing a distributed space-time coding scheme. Our objective is finding optimal cooperator selection policies for arbitrary topologies with links affected by path loss and multipath fading. To this end, we model the network behavior through a suitable Markov chain and we formulate the cooperator selection process as a stochastic shortest path problem (SSP). Further, we reduce the complexity of the SSP through a novel pruning technique that, starting from the original problem, obtains a reduced Markov chain which is finally embedded into a solver based on focused real time dynamic programming (FRTDP). Our algorithm can find cooperator selection policies for large state spaces and has a bounded (and small) additional cost with respect to that of optimal solutions. Finally, for selected network topologies, we show results which are relevant to the design of practical network protocols and discuss the impact of the set of nodes that are allowed to cooperate at each hop, the optimization criterion and the maximum number of cooperating nodes.
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[O2] C. Tapparello, D. Chiarotto, M. Rossi, O. Simeone and M. Zorzi, Spectrum Leasing via Cooperative Opportunistic Routing in Distributed Ad Hoc Networks: Optimal and Heuristic Policies, Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA. November 6-9, 2011. (Student Paper Contest Finalist)
Abstract: A spectrum leasing strategy is considered for the coexistence of a licensed multihop network and a set of unlicensed nodes. The primary network consists of a source, a destination and a set of additional primary nodes that can act as relays. In addition, the secondary nodes can be used as extra relays and hence potential next hops following the principle of opportunistic routing. Secondary cooperation is guaranteed via the “spectrum leasing via cooperation” mechanism, whereby a cooperating node is granted spectral resources subject to a Quality of Service (QoS) constraint.
The objective of this work is to find optimal as well as efficient heuristic routing policies based on the idea outlined above of spectrum leasing via cooperative opportunistic routing. The optimal policy is obtained by casting the problem in the framework of stochastic routing. The optimal performance is then numerically compared with two proposed heuristic routing schemes, which are shown to perform close to optimal solutions and as well being tunable in terms of end-to-end throughput vs primary energy consumption.
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[O3] H. Ayatollahi, C. Tapparello and W. Heinzelman, Transmitter-Receiver Energy Efficiency: A Trade-off in MIMO Wireless Sensor Networks, IEEE Wireless Communications and Networking Conference (WCNC), New Orleans, LA,USA. March 9-12, 2015.
Abstract: Power and energy consumption are the most important factors in extending the lifetime of Wireless Sensor Networks (WSN). Many energy efficiency techniques, that consider both the transmission and circuit power consumption have been proposed for the case of Single-Input Single-Output (SISO) WSNs. However, the power consumption of the receiver should also be considered in order to maximize the network lifetime. In this paper, we introduce a novel communication protocol for Multiple-Input Multiple-Output (MIMO) WSNs. In this protocol, the number of antennas to be used at both the transmitter and receiver are selected according to the energy consumption of the scheme, the remaining energy at the nodes, the distance between the nodes, and the target bit error rate. Starting from a policy that selects the optimal number of antennas, we then propose 3 low complexity heuristics with different information requirements. Numerical results show that our proposed communication protocols dramatically outperform the performance of a traditional fixed MIMO system in terms of energy consumption and system lifetime.
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[O4] C. Tapparello, O. Simeone and M. Rossi, Dynamic Compression-Transmission for Energy-Harvesting Multihop Networks with Correlated Sources, IEEE/ACM Transactions on Networking, Vol. 22, No. 6, December 2014, pp. 1729-1741. (Technical Report: arXiv:1203.3143)
Abstract: Energy-harvesting wireless sensor networking is an emerging technology with applications to various fields such as environmental and structural health monitoring. A distinguishing feature of wireless sensors is the need to perform both source coding tasks, such as measurement and compression, and transmission tasks. It is known that the overall energy consumption for source coding is generally comparable to that of transmission, and that a joint design of the two classes of tasks can lead to relevant performance gains. Moreover, the efficiency of source coding in a sensor network can be potentially improved via distributed techniques by leveraging the fact that signals measured by different nodes are correlated. In this paper, a data gathering protocol for multihop wireless sensor networks with energy harvesting capabilities is studied whereby the sources measured by the sensors are correlated. Both the energy consumptions of source coding and transmission are modeled, and distributed source coding is assumed. The problem of dynamically and jointly optimizing the source coding and transmission strategies is formulated for time- varying channels and sources. The problem consists in the minimization of a cost function of the distortions in the source reconstructions at the sink under queue stability constraints. By adopting perturbation-based Lyapunov techniques, a close-to-optimal online scheme is proposed that has an explicit and controllable trade-off between optimality gap and queue sizes. The role of side information available at the sink is also discussed under the assumption that acquiring the side information entails an energy cost.
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[O5] C. Funai, C. Tapparello, and W. Heinzelman, Enabling Multi-hop Ad Hoc Networks Through WiFi Direct Multi-group Networking, IEEE International Conference on Computing, Networking and Communications (ICNC), Silicon Valley, CA, USA. January 26-29, 2017. Technical Report: arXiv:1601.00028.
Abstract: With the increasing availability of mobile devices that natively support ad hoc communication protocols, we are presented with a unique opportunity to realize large scale ad hoc wireless networks. Recently, a novel ad hoc protocol named WiFi Direct has been proposed and standardized by the WiFi Alliance with the objective of facilitating the interconnection of nearby devices. However, WiFi Direct has been designed following a client-server hierarchical architecture, where a single device manages all the communications within a group of devices. In this paper, we propose and analyze different practical solutions for supporting the communications between multiple WiFi Direct groups using Android OS devices. By describing the WiFi Direct standard and the limitations of the current implementation of the Android WiFi Direct framework, we present possible solutions to interconnect different groups to create multi-hop ad hoc networks. Experimental results show that our proposed approaches are feasible with different overhead in terms of energy consumption and delay at the gateway node. Additionally, our experimental results demonstrate the superiority of techniques that exploit the device ability to maintain simultaneous physical connections to multiple groups.
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[O6] C. Tapparello, H. Ayatollahi and W. Heinzelman, Energy Harvesting Framework for Network Simulator 3 (ns-3), 2nd International Workshop on Energy Neutral Sensing Systems (ENSsys), Memphis, TN, USA. November 6, 2014.
Abstract: The problem of designing and simulating optimal communication protocols for energy harvesting wireless networks has recently received considerable attention, thus requiring an accurate modeling of the energy harvesting process and a consequent redesign of the simulation framework to include this. While the current ns-3 energy framework allows the definition of new energy sources that incorporate the contribution of an energy harvester, integrating an energy harvester component into an existing energy source is not straightforward using the existing energy framework. In this paper, we propose an extension of the ns-3.20 energy framework in order to explicitly introduce the concept of an energy harvester. Starting from the definition of a general energy harvester, we provide the implementation of two simple models for the energy harvester. In addition, we introduce the concept of an energy predictor, that gathers information from the energy source and harvester and uses this information to predict the amount of energy that will be available in the future. Finally, we extend the current energy framework to include a model for a supercapacitor energy source and a device energy model for the energy consumption of a sensor. Example simulation results show the benefit of our contributions to the ns-3 energy framework.
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The increasing availability of mobile devices, combined with the fact that nowadays people of all ages are always carrying or within range of at least one mobile device, has opened the possibility for new healthcare solutions. As recognized by the joint NSF and NIH Smart and Connected Health Program, these novel solutions have the potential to “transform the healthcare from reactive and hospital-centered to preventive, proactive, person-centered and focused on well-being rather than disease”. The need for such a transition is widely recognized by the medical community but requires large implementation efforts in order to develop suitable solutions that address the various requirements of different patients and medical conditions.

Main Contributions:

In collaboration with Dr. Kelly Conn from St. John Fisher College (Rochester, NY), I developed a mobile application to help parents manage their child’s asthma. This application combines an educational part allowing the parents to learn more about their child’s condition, an easy access to local resources that can help relieve the difficulty of managing their child’s condition, and a reminder-based symptoms tracking component that can be used by the child’s doctor to control and adjust the child’s therapy. Moreover, in collaboration with Dr. Craig Mullen from the University of Rochester, I developed a mobile application to improve the compliance to prescribed medications in oncology patients. This application tests if a novel approach that simultaneously addresses patient understanding, provides a structured schedule of reminders and realtime data logging, and gives active case management based on real-time data, will significantly improve patient compliance with oral chemotherapy regimens. These applications and the proposed approaches are currently being validated via human subjects studies [H2].

While developing these mobile applications I realized that 1) medical practitioners recognize the importance of novel technology-based healthcare solutions, and 2) the application/infrastructure components most of the time overlap between different conditions/medical areas.

In this context, I have recently proposed and implemented ManageMyCondition [H1], a standard framework for the development of cloud-based medical condition management applications. Thanks to the experience acquired with the development of ManageMyCondition, I am currently working with Dr. Christie Petrenko (Mt. Hope Family Center, University of Rochester) to develop and investigate the efficacy of FMF Connect, a novel Cloud-based mHealth application, to directly provide caregivers raising children with fetal alcohol spectrum disorders (FASD) with evidence-based content and peer-moderated support to improve child and caregiver outcomes. FMF Connect is derived from the scientifically-validated Families Moving Forward (FMF) Program, and built on ManageMyCondition and other open source frameworks.

Selected Publications:

[H1] C. Tapparello, W. Heinzelman, K. Conn and C. A. Mullen, Developing Medical Condition Management Applications using ManageMyCondition, IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Washington D.C., USA. June 27-29, 2016.
Abstract: Given the increasing availability and accessibility of mobile devices, there is enormous potential to transform how healthcare is administered through the creation of highly customized smartphone-based applications for effective medical condition management. Such platforms can offer improvements for both patients and healthcare systems. However, a critical barrier to achieving these tantalizing benefits in healthcare management is the current paradigm of medical software design. Development and deployment of enterprise-wide applications is generally slow and expensive. Furthermore, each application is developed independently, even if several functionalities overlap between different applications. In this demonstration, we present our experience in the development of three mobile applications for medical condition management, namely ManageMyAsthma, ManageMyMedications and ManageMyPatients, which led to the creation of ManageMyCondition, a standard framework for the development of medical condition management applications.
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[H2] C. Tapparello, W. Heinzelman, K. Conn and C. A. Mullen, ManageMyCondition: A Standard Framework for the Development of Cloud-based Medical Condition Management Applications, IEEE International Workshop on Cloud Connected Health (CCH), Washington D.C., USA. June 27-29, 2016.
Abstract: Given the increasing availability and accessibility of mobile devices, there is enormous potential to transform how healthcare is administered through the creation of highly customized smartphone-based applications for effective medical condition management. Such platforms can offer improvements for both patients and healthcare systems. For patients, advantages include improved health management as well as satisfaction, enabling them to better understand their medical condition and improve their compliance with medication regimes. For healthcare systems, advantages include more effective patient management and increased pay-for-performance reimbursements, enabling real time tracking of critical patient specific data to provide comprehensive, effective medical condition management. However, a critical barrier to achieving these tantalizing benefits in healthcare management is the current paradigm of medical software design. Development and deployment of enterprise-wide applications is generally slow and expensive. Furthermore, each application is developed independently, even if several functionalities overlap between different applications. In this paper, we present ManageMyCondition, a framework for the rapid creation and standardization of medical condition management applications. The framework defines different building blocks for the creation of cloud-based mobile applications, defines a common format for data acquisition and presentation, and is easily customizable and extendable to meet the needs of different medical conditions. Finally, we present three mobile applications for medical condition management developed using the ManageMyCondition framework.
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The increasing availability of mobile devices makes it possible to explore novel computing infrastructures. In particular, ad hoc mobile cloud computing has been proposed as a way to offload the computation from a mobile device to a remote cloud through a combination of ad hoc and Internet communications. Moreover, given the large availability and intrinsic energy efficiency of mobile devices, different solutions also explored the possibility of using mobile devices as the devices that are performing the computation. Solutions for offloading the computation from the cloud to the mobile devices as well as between mobile devices have been proposed. However, there is no general framework for evaluating and optimizing the offload of the computation, while security considerations and the effect on the user experience are still considered open research problems.

Main Contributions:

In [C1], I investigated different techniques for allowing the computation offload from the cloud to the mobile ad hoc networks, while in [C2] I explored the tradeoff of distributing the computation in multi-hop ad hoc networks. Moreover, I am currently working on a general architecture where a mobile device is able to independently decide to offload the computation either to the cloud or to the local ad hoc network. This architecture allows to derive energy-delay tradeoff based on the device computational capabilities, the amount of information to be exchanged between the devices, and the device available network interfaces.

These works prove the potential of mobile devices as computing devices [C3], showing that different tradeoffs can be achieved when offloading the computation to a local network vs. the cloud, and motivate further research in this area.

Finally, I recently started to explore the benefits of combining the concepts described above to enable distributed computing in ad hoc multi-robot networks. In particular, I am currently working on learning models to predict ad hoc network performance between nodes in a multi-robot team. These models will enable robots to predicatively compensate for potential disruptions in links that originate from the environmental complexity and dynamics, and can be used to improve the probabilistic planning of distributed computing and feed-forward control of network and link layers for ad hoc networks.

Selected Publications:

[C1] C. Funai, C. Tapparello, H. Ba, B. Karaoglu and W. Heinzelman, Extending Volunteer Computing through Mobile Ad Hoc Networking, IEEE GLOBECOM, Austin, TX, USA. December 8-12, 2014.
Abstract: Volunteer computing provides a practical and low cost solution to the increasing computational demands of many applications. Recent advancements in mobile device processing capabilities, combined with the energy efficiency of the mobile devices, make their inclusion in a distributed computing architecture particularly appealing. However, the intrinsic requirement of Internet connectivity to participate in volunteer computing limits the direct adoption of mobile devices due to service availability or related costs to connect to the Internet. In this paper, we propose and implement a novel computational architecture that extends the ability of mobile devices to participate in volunteer computing through ad hoc networking. By introducing decentralized task distribution points, mobile devices are invited to join the computation via device to device communication, removing the requirement for an Internet connection. Using a prototype implementation running on Android devices, we investigate the impact of a promising ad hoc communication technology, namely WiFi Direct, and two task distribution algorithms with different computation and communication overheads, under various scenarios. Experimental results show that our proposed approach is feasible with only minor additional energy consumption at the decentralized task distribution points.
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[C2] C. Funai, C. Tapparello, and W. Heinzelman, Mobile to Mobile Computational Offloading in Multi-hop Cooperative Networks, IEEE GLOBECOM, Washington, DC, USA. December 4-8, 2016.
Abstract: As the number of mobile devices that natively support ad hoc communication protocols increase, large ad hoc networks can be created not only to facilitate communication among the mobile devices, but also to assist devices that are executing computationally intensive applications. Prior work has developed computation offloading systems for mobile devices, but this work has focused exclusively on offloading to single hop neighbors, due in part to the practical challenges of setting up multi-hop networks using existing ad hoc communication protocols. However, limiting the offloading of computation to one-hop neighbors inherently restricts the number of devices that can participate in the distributed computation. In this paper, we propose and evaluate the performance of computational offloading within a multi-hop cooperative network, where mobile devices are able to share the computational load with all other nodes in the network. Additionally, we present an iterative task assignment algorithm that can optimize the assignment of computational tasks to devices in such a multi-hop cooperative network, taking into account the communication overhead of the multi-hop network. Experimental results, obtained from an implementation on Android devices, are integrated with an analytical model that enables the evaluation of system performance under a variety of conditions. These experimental and analytic results demonstrate the benefit of enabling computation offloading to all devices in a multi-hop cooperative network.
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[C3] C. Tapparello, C. Funai, S. Hijazi, A. Aquino, B. Karaoglu, H. Ba, J. Shi, and W. Heinzelman, Volunteer Computing on Mobile Devices: State of the Art and Future Research Directions, Appears in Enabling Real-Time Mobile Cloud Computing through Emerging Technologies, IGI Global, 2015.
Abstract: Different forms of parallel computing have been proposed to address the high computational requirements of many applications, following the principle that large computational problems can often be divided into smaller ones. Building on advances in parallel and distributed computing, volunteer computing has been shown to be an efficient way to exploit the computational resources of devices that are available around the world and that are under utilized for most of their time. The idea of including mobile devices, such as smartphones and tablets, in existing distributed volunteer computing systems has recently been investigated. In this chapter, we present the current state of the art in the mobile volunteer computing research field, where personal mobile devices are the elements that perform the computation. Starting from the motivations and challenges behind the adoption of personal mobile devices as computational resources, we then provide a literature review of the different architectures that have been proposed to support parallel and distributed computing and how these architectures have been adapted to use mobile devices for distributed computing. Finally, we present some open issues that need to be investigated in order to extend user participation and improve the overall system performance for mobile volunteer computing.
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Wireless sensor networks (WSN) have been shown to automate different operations that normally require continuous user involvement. In particular, different researchers have recognized their potential in environmental and disaster monitoring. While several solutions have been proposed over the years, there is still no general architecture to address the needs for an efficient design of WSN-based monitoring systems. Moreover, there are several open issues that need to be addressed to further advance automatic environmental and disaster monitoring using WSNs.

Main Contributions:

I have recently completed two literature survey papers that investigate the current state of the art in the design of these types of systems. The first work focused on WSN-based solutions for water quality monitoring, while the second one focuses on WSNs that take advantage of energy harvesting technologies and protocols for environmental monitoring applications. These literature reviews show that, while several research efforts have been dedicated to the design of these systems, they are quite fragmented and there are still several open issues that are limiting their widespread adoption. As a result, most of these scenarios either rely on human intervention, or they rely on very expensive dedicated equipment and sensors.

In addition, I have recently worked on the design and implementation of a WSN-based system for the remote monitoring of wild elephants. Within this system, wireless sensor nodes are attached to the elephants and communicate with each other using an epidemic routing-based protocol in order to reach fixed monitoring stations. Moreover, since tagging (using GPS collars) elephants to obtain location information is difficult and costly, in collaboration with Dr. Wijesundara (Sri Lanka Institute of Information Technology, Malabe, Sri Lanka), I proposed a kinetic energy harvester that uses magnetic levitation and ferro fluid bearings to generate energy from an elephant movements. Some initial testing of the use of these sensors on domesticated elephant is currently ongoing as part of JumboNet, a collaborative effort between University of Rochester and Sri Lanka Institute of Information Technology (Malabe, Sri Lanka) to explore solutions to Human-Elephant Conflicts using wireless communication technologies.

Selected Publications:

[W1] K. S. Adu-Manu, C. Tapparello, W. Heinzelman, F. A. Katsriku and J.-D. Abdulai, Water Quality Monitoring Using WSNs: Current Trends and Future Research Directions. ACM Transactions on Sensor Networks, Vol. 13 Issue 1, January 2017, Article No. 4.
Abstract: Water is essential for human survival. While approximately 71% of the world is covered in water, only 2.5% of this is fresh water; hence fresh water is a valuable resource that must be carefully monitored and maintained. In developing countries, 80% of people are without access to potable water. Cholera is still reported in over 50 countries. In Africa, 75% of the drinking water comes from underground sources that makes water monitoring an issue of key concern, as water monitoring can be used to track water quality changes over time, to identify existing or emerging problems and to design effective intervention programs to remedy water pollution. It is important to have detailed knowledge of potable water quality to enable proper treatment and also prevent contamination. In this paper, we review methods for WQM from traditional manual methods to more technologically advanced methods employing Wireless Sensor Networks (WSNs) for in-situ WQM. In particular, we highlight recent developments in the sensor devices, data acquisition procedures, communication and network architectures, and power management schemes to maintain a long-lived operational WQM system. Finally, we discuss open issues that need to be addressed to further advance automatic WQM using WSNs.
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[W2] K. S. Adu-Manu, N. Adam, C. Tapparello, H. Ayatollahi and W. Heinzelman, Energy-Harvesting Wireless Sensor Networks (EH-WSNs): A Review, ACM Transactions on Sensor Networks, Vol. 14 Issue 2, July 2018, Article No. 10.
Abstract: Wireless Sensor Networks (WSNs) are crucial in supporting continuous environmental monitoring, where sensor nodes are deployed and must remain operational to collect and transfer data from the environment to a base-station. However, sensor nodes have limited energy in their primary power storage unit, and this energy may be quickly drained if the sensor node remains operational over long periods of time. Therefore, the idea of harvesting ambient energy from the immediate surroundings of the deployed sensors, to recharge the batteries and to directly power the sensor nodes, has recently been proposed. The deployment of energy harvesting in environmental field systems eliminates the dependency of sensor nodes on battery power, drastically reducing the maintenance costs required to replace batteries. In this paper, we review the state of the art in energy harvesting WSNs for environmental monitoring applications including Animal Tracking, Air Quality Monitoring, Water Quality Monitoring, and Disaster Monitoring to improve the ecosystem and human life. In addition to presenting the technologies for harvesting energy from ambient sources and the protocols that can take advantage of the harvested energy, we present challenges that must be addressed to further advance energy harvesting-based WSNs, along with some future work directions to address these challenges.
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[W3] M. N. Wijesundara, C. Tapparello, A. Gamage, Y. Gokulan, L. Gittelson, T. Howard and W. Heinzelman, Design of a Kinetic Energy Harvester for Elephant Mounted Wireless Sensor Nodes of JumboNet, IEEE GLOBECOM, Washington, DC, USA. December 4-8, 2016.
Abstract: In areas where the habitats of elephants and humans are rapidly encroaching on each other, real-time monitoring of the elephants' locations has the potential to drastically improve the co-existence of elephants and humans, resulting in reduced deaths in both groups. However, as tagging (using GPS collars) elephants to obtain such location information is difficult and costly, it is important to ensure very long lifetimes of the tags, which can only be achieved using energy harvesting. In this paper, we present a kinetic energy harvester that uses magnetic levitation and ferro fluid bearings to generate energy from an elephant's movements. In order to determine the feasibility of using this kinetic energy harvester for powering the tags on elephants, we obtained real acceleration data collected from an Asian elephant over a 10 day period, and this data was then used to tune the system to maximize the harvested energy. Using experimentally validated analytical and simulation models, and the actual elephant acceleration data, we find that our prototype can generate 88.91J of energy per day. This energy is not only sufficient to power the tags to acquire and transmit locations 24 times a day to a distance of 114km (line of sight), but provides a surplus of at least 35.40J, which can be used to increase the frequency of position updates or to support alternative communication options such as GPRS. Therefore, this shows the viability of long-term tracking of elephants.
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