Energy-efficient computing for wildlife tracking

Abstract

Over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. The field of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices for both scientific and commercial purposes. This paper examines the research decisions and design tradeoffs that arise when applying wireless peer-to-peer networking techniques in a mobile sensor network designed to support wildlife tracking for biology research.The ZebraNet system includes custom tracking collars (nodes) carried by animals under study across a large, wild area; the collars operate as a peer-to-peer network to deliver logged data back to researchers. The collars include global positioning system (GPS), Flash memory, wireless transceivers, and a small CPU; essentially each node is a small, wireless computing device. Since there is no cellular service or broadcast communication covering the region where animals are studied, ad hoc, peer-to-peer routing is needed. Although numerous ad hoc protocols exist, additional challenges arise because the researchers themselves are mobile and thus there is no fixed base station towards which to aim data. Overall, our goal is to use the least energy, storage, and other resources necessary to maintain a reliable system with a very high 'data homing' success rate. We plan to deploy a 30-node ZebraNet system at the Mpala Research Centre in central Kenya. More broadly, we believe that the domain-centric protocols and energy tradeoffs presented here for ZebraNet will have general applicability in other wireless azld sensor applications.

Mobility management for IoT: a survey

“…• Mobile embedded sensor: In this type of sensor, their movement is controlled by external force, like wildlife tracking [96] or tracking cooperative nodes [97]. Another typical example for embedded sensors can be found in [98][99][100].…”

“…• Data mule: Predominantly, in this kind which is called a data mule [96], the sensor nodes do not work as mobile; they just collect the data and sent the collected data to the base station.…”

MANER: Managed Data Dissemination Scheme for LoRa IoT Enabled Wildlife Monitoring System (WMS)

“…Currently, several OMN based wildlife monitoring projects are proposed for sensor data gathering, e.g. ZebraNet [3,9], Rat Watch [10]. These works, implement opportunistic networks by leveraging a history based flooding, which are prone to low delivery ratio and high latency [7].…”

“…Moreover, the gathered data is transfered to a sink using intermediate nodes as fixed relays. However, traditional routing protocols will perform poorly in WMS scenarios where the network is sporadically connected due to animal mobility pattern [9]. Currently, several research works have shown an improved data collection based on opportunistic sensing with fixed network infrastructure support.…”

“…Currently, several research works have shown an improved data collection based on opportunistic sensing with fixed network infrastructure support. However, unless standard mobility model is considered, they often result in low delivery ratio and high latency [5,9,10]. Thus, an efficient data dissemination protocol is needed for a newly surfacing applications as in WMS IoT network architecture with random mobile nodes.…”