The aim of the AfE is to bring a beyond state the art efficient communications network protocol with a set of powerful and innovative features, for low power wireless area networks (LPWAN).
AfE is the only meshed/ad-hoc communication network protocol that allows the continuous management of routing trees through optimal hop-constrained and energy resources of all the wireless sensor network (WSN), in order to continuously optimize and predict the performance and lifecycle of the whole network infrastructure, e.g. an automated metering infrastructure (AMI).
AfE allows the efficient integration in the same network infrastructure of communications battery-operated, energy-constrained, and mains power supplies operated devices/sensors, commonly in use in smart cities infrastructures, automated metering infrastructures (AMI), or professional buildings infrastructures!
AfE is a flexible multi-infrastructure and bidirectional communication network protocol, for use among smart cities infrastructures, automated metering infrastructures (AMI) or, professional buildings infrastructures.
AfE technology is Energy Aware, Reliable, and Easy to Deploy.
The AfE communication network protocol allows battery, energy constrained, or energy harvesting operated devices, the generation of efficient meshed/ad-hoc communication networks.
The AfE uses an innovative and efficient routing algorithm to compute continuously optimal spanning trees that maximize the energy capacity of the whole network infrastructure and minimize the number of hops of battery-operated or energy-constrained communications networks.
The AfE communication network protocol allows the easy connectivity of all the devices of the network infrastructure, dealing effectively with situations where other communication protocols normally can’t operate due deficient radiofrequency coverage and/or due to radio signal barriers.
The AfE communication network protocol has the self-healing connectivity ability by continuously exploring all available links among the network infrastructure devices to compute successively alternative spanning trees - "if exists an available link to a determined device, such device is connected in the network, no matter where it is".
The AfE communication network protocol allows the complete coverture of all the devices, even in harsh environment conditions, where current state of the art LPWAN protocols normally fail.
Network Easy deployment
The devices can be easily deployed with no hassle to the user, providing high scalability levels in the network infrastructure. Just is enough to place the device in the range of the current network infrastructure and the device is ready to go!
Devices Upgradable via OtA
If new features or revisions were developed, AfE devices firmware can be easily upgraded or updated over the air (OtA).
Flexibility / Multi-Infrastructure deployment
AfE has high number of devices integration capacity, enabling the possibility of an infrastructure network can have connected thousand of devices.
AfE has the possibility of interoperation among different utilities in smart cities infrastructures or automated metering infrastructures (AMI), from a same control center (CC), such for public water distribution networks, public electricity distribution networks, public streetlight, public interior lighting, green spaces irrigation, environmental and traffic sensors, etc.
AfE has the possibility of interoperation among different utilities in professional buildings infrastructures, from a same control center (CC), such for interior/exterior lighting, environmental sensors, intrusion or fire alarms, etc.
AfE can integrate in the same infrastructure battery-operated or energy-constrained devices with devices powered by mains power supply, where the communication network algorithm automatically compute the adequate spanning trees to obtain the optimal performance of the whole communication network.
AfE-EA's Problem Assessment
AfE-EA is the abbreviation of LPWAN-AfE-EA: Low Power Wireless Area Network – All for Everyone & Energy Aware Communication Network Protocol and was inspired in the ability of all the devices/sensors of an instance/ecosystem, e.g. a wireless sensor network (WSN) of an Utility Infrastructure, can communicate efficiently with each others.
In wireless sensor networks (WSN), the network infrastructure performance depends heavily on the efficiency of the communications network routing protocol.
The communication network routing protocol must deal efficiently with challenges such as energy constraints, low storage capacity, low bandwidth, low processing capability, device/sensor location sparsity, fault tolerance, among others.
All of these factors can affect the quality of service (QoS) of the automated metering infrastructure (AMI), or similar.
Having those challenges in mind, was developed the AfE-EA, a communication network routing protocol that allows for battery-operated or energy-constrained devices, even in the case of powering by energy harvesting, to form a proper meshed/ad-hoc communications network by implementing new disruptive features for efficient routing and managing of the energy consumption/availability of all devices/sensors of the infrastructure.
AfE-EA was developed to have the same common architecture of the power smart grids AMI infrastructures, composed of a control center (CC), data concentrators (DC) and groups of devices/sensors. The DC is responsible for gathering all the data from the devices/sensors and also managing all the communication network routing. The DC is the device responsible to compute the all the optimal communication network routings, from the DC to all the devices/sensors and vice-versa.
AfE-EA is based in an efficient time complexity algorithm to compute optimal hop-constrained maximum capacity spanning trees, to be used in bidirectional communication networks, even in the case of battery-operated or energy-constrained devices/sensors that can operate together mains power supplies operated devices/sensors.
The general principle followed was that the communication routing protocol should compute periodically or, when necessary, the optimal network spanning trees in order to use preferably as routers the devices/sensors with more available energy and with optimal hop-constraints and, this way, adjust the available energy of the whole network’s devices/sensors by performing a balanced consumption in all the devices/sensors, in order to maximize the period of operation of the whole infrastructure network.
The bottom line is that since AfE-EA computational complexity is fairly low, it is possible to compute optimal network hop-constrained spanning trees in real time, which is of major importance to cope with the needs of a self-healing/rearrangement routing. In case of battery-operated or energy-constrained devices, this functionality also allows the achieving of a network lifetime that is in line with the infrastructure's hardware lifetime.
As well known, in accordance with the current science state-of-the-art, the computation of even only hop-constrained minimum spanning trees (H-CMST) of dozens of devices/sensors is a math problem of class NP-Hard of high computational complexity, which cannot be performed efficiently in polynomial time by the current IT resources / computers available nowadays, even for the most sophisticated.
Therefore, one of the biggest outcomes is directly related with AfE-EA's computational efficiency that enables the possibility to use very small and low-cost processors, with low resources and battery-operated or energy-constrained, even in the case of be powered by energy harvesting.
AfE-EA also enables the possibility of having fully automated managing systems (AMS), namely in automated metering infrastructures (AMI), allowing the user to have very large networks without worrying about the communication network itself but only about processing the data that is continuously gathered.