Amalinda Gamage

Publications | Talks | Teaching | Service

Hello, I'm Amalinda from Sri Lanka 🇱🇰. ආයුබෝවන්! (āyubōwan!)— a warm wish for a long and prosperous life in Sinhalese.

I'm a Research Fellow with NTU, SG. I earned my Ph.D. degree in Computer Science from the same university advised by Professor Mo Li and my Bachelor's degree in Electronic Engineering with first-class honors from SHU, UK. Prior to joining NTU, I was a lecturer at both SLIIT and UNIVOTEC in Sri Lanka. I am also an elected member of The Institution of Engineers Singapore (IES), a signatory of The Washington Accord.

Central to my research is spectral optimization, specifically in the implementation of physical layer techniques that enhance the coexistence & fairness of LPWANs. My current work is focused on bringing improvements to LoRa— a low-power LOng RAnge communication protocol for the Internet of Things.

My previous work LMAC, enabling CSMA for LoRaWAN, has led to an industry standard of the LoRa Alliance and is commercially deployed worldwide by the singapore-made IoT startup BITS.

[Summary. ] LMAC was proposed to the LoRa Alliance to reduce collisions among LoRaWAN devices. The CSMA Task Force integrates a version of LMAC to TR-013 which enables CSMA for LoRaWAN.
Thank you Semtech and LoRa Alliance for this successfull collaboration!

[Summary. ] This work extends LMAC through an industry-academia collaboration between Semtech and NTU. The extension explores various aspects including the limitations of utilizing RSS-LBT, enhancing weak transmissions through LMAC, gradual adoption and coexistence with ALOHA, regulatory implications, and finally, compliance.

[Summary. ] This work looks into collision avoidance across large-scale LoRa networks. CSMA is a technique used by many wireless protocols to avoid collisions. However, LoRa modulation is unique. A single LoRa channel can accommodate multiple frames simultaneously. LoRa frames also have the ability to traverse underneath the noise floor. Therefore, we need a CSMA protocol that doesn't debilitate LoRa's key advantages. LMAC is a simple protocol that does just that reliably with an extremely small energy overhead.

Project Website | MobiCom 5min pitch

[ABSTRACT] Long Range (LoRa) is a Low-power Wide-area Network technology designed for the Internet of Things. In recent years, it has gained significant momentum among industrial and research communities. Patented by Semtech, LoRa makes use of chirp spread spectrum modulation to deliver data with promises of long battery life, far-reaching communication distances, and a high node density at the cost of data rate. In this article, we conduct a series of experiments to verify the claims made by Semtech on LoRa technology. Our results show that LoRa is capable of communicating over 10km under line-of-sight environments. However, under non-line-of-sight environments, LoRa’s performance is severely affected by obstructions such as buildings and vegetations. Moreover, the promise of prolonged battery life requires extreme tuning of parameters. Last, a LoRa gateway supports up to 6,000 nodes with PRR requirement of >70%. This study also explores the relationship between LoRa transmission parameters and proposes an algorithm to determine optimal settings in terms of coverage and power consumption under non-line-of-sight environments. It further investigates the impact of LoRa Wide-area Networks on energy consumption and network capacity along with implementation of a LoRa medium access mechanism and possible gains brought forth by implementing such a mechanism.

[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.