On the design of an energy-harvesting protocol stack for Body Area Nano-NETworks

Abstract

Body Area Nano-NETworks (BANNETs) consist of integrated nano-machines, diffused in the human body for collecting diagnostic information and tuning medical treatments. Endowed with communication capabilities, such nano-metric devices can interact with each other and the external micro/macro world, thus enabling advanced health-care services (e.g., therapeutic, monitoring, sensing, and telemedicine tasks). Due to limited computational and communication capabilities of nano-devices, as well as their scarce energy availability, the design of powerful BANNET systems represents a very challenging research activity for upcoming years. Starting from the most significant and recent findings of the research community, this work provides a further step ahead by proposing a hierarchical network architecture, which integrates a BANNET and a macro-scale health-care monitoring system and two different energy-harvesting protocol stacks that regulate the communication among nano-devices during the execution of advanced nano-medical applications. The effectiveness of devised solutions and the comparison with the common flooding-based communication technique have been evaluated through computer simulations. Results highlight pros and cons of considered approaches and pave the way for future activities in the Internet of Nano-Things and nano-medical research fields.

Introduction

In upcoming years, the innovation process triggered by nanotechnologies is expected to foster the development of integrated devices with size ranging from one to few hundred of nanometers, very well suited for ICT, biomedical, industrial, and military applications  [1]. This is sustaining the revolutionary transition from the Internet of Things (IoT)  [2] to the Internet of Nano-Things (IoNT)  [3].

Some recent studies on graphene-based nanoantennas demonstrated how nano-machines can communicate each other by using electromagnetic (EM) waves in the Terahertz band, with extremely higher bit rates at the nano-scale (i.e., around some terabit/s), but with limited transmission ranges that cannot exceed few tens of millimeters  [4], [5]. Accordingly, Wireless NanoSensor Networks (WNSNs), which are networks composed by a (potentially high) number of nano-machines able to communicate each other through the wireless channel, became the first concrete actualization of the IoNT concept  [1], [2], [3], [4], [5], [6], [7], [8], [9], [10].

In particular, the use of IoNT systems in the health-care domain discloses new horizons and never seen applications  [8], [11], [12], [13], [14], [15]. In this context, Body Area Nano-NETworks (BANNETs) represent a specific WNSN system, operating in the human body  [8]: biomedical nano-devices equipped with communication capabilities, can be implanted, ingested, or worn by humans for collecting diagnostic information (e.g., the presence of sodium, glucose, and/or other ions in blood, cholesterol, as well as cancer biomarkers and other infectious agents) and tuning medical treatments (e.g., administration of insulin and other drugs through under-skin actuators)  [16].

While few scientific works already started the study of some aspects related to BANNETs (see for example [11], [12], [13], [14], [15]), three important issues have not been addressed with the required depth, that are:

• How to design a lightweight protocol suite able to fit the singular requirements of nano-machines?

• According to  [3], nano-machines cannot execute complex tasks and, as a consequence, all the solutions already conceived for the IoT domain, cannot be directly applied to BANNETs. In line with this assumption, some contributions have already proposed valuable solutions for Media Access Control (MAC)[17], [18] and routing  [19] layers. However, they mainly focus on WNSNs and do not take care of requirements and constraints that typically characterize BANNETs. Simple MAC and routing protocols enabling health-care services are presented in  [12], [13], but their formulation needs to be improved for also covering additional issues described in the sequel.

• How to deal with limited energy resources available at the nano-scale?

• Without loss of generality, it should be assumed that nano machines should count for minimal power capabilities and the adoption of suitable energy harvesting mechanisms is required for ensuring a continuous availability of nano-devices in a BANNET. With the aim of increasing, as more as possible, the lifetime of nano-networks, the entire protocol stack should be designed by jointly considering energy harvesting and energy consumption processes  [20]. In this regard, some significant contributions have been presented in  [21], [22], [23]. Also in this case, such works focus on WNSN and their adaptability to BANNET environments still remains an open issue.

• How to enable the interaction between nano-environments and the rest of the world?

• A BANNET could be integrated within a complex health monitoring system  [8], where different monitoring devices, that communicate among them and with a remote health-care server through Low-power and Lossy Network (LLN) technologies  [24], [2], may also coexist. In this scenario, it is important to evaluate the interaction between devices belonging to both nano and macro domains. Even if a hierarchical architecture has been already defined in  [3], it is still not clear how to properly regulate the interaction between macro and nano devices and to define the rate of requests coming from the macro world that ensures the right reactivity of nano-devices (subjected to computational, technological, and energy constraints) that satisfies health-care application requirements.

To provide initial answers to the aforementioned issues, this work proposes a twofold contribution. First of all, a lightweight network architecture that integrates a BANNET within a more complete health-care monitoring system is proposed. In line with the scheme presented in [3], it is able to deliver requests coming from monitoring devices to nano-machines and forward corresponding answers in the opposite direction. Then, two different energy-harvesting aware protocol stacks (composed by both MAC and routing algorithms) have been conceived. The former scheme implements an optimal routing protocol, that selects the most suitable nano-machine which the request coming from the external world are forwarded to. Such a decision is done in order to maximize the overall amount of energy that will be available into the network when a new request arrives. To this end, starting from the energy model developed in  [20], the routing protocol has been defined by means of an optimization problem. The latter, instead, just delivers the request to the node with the higher energy level (greedy approach). In both cases, a handshake mechanism has been implemented at the MAC layer for identifying devices available in the neighborhood and being aware about their energy level.

The effectiveness of conceived proposals have been evaluated through computer simulations by using the emerging NANO-SIM tool  [25], which models electromagnetic based nano-communications within the NS-3 simulation framework. In particular, it has been evaluated the impact of the density of nano-machines forming the BANNET and of the average rate of requests coming from the macro world have on packet loss ratio, energy and device availability, and physical transmission throughput. To provide a further insight, a comparison with respect to the simple flooding approach (according to which any request is broadcasted into the network without executing any kind of initial handshake and the answer is generated by all the available devices) is reported too.

Results show that better system performances can be achieved when energy-harvesting aware techniques are used. When compared with the flooding approach, such strategies guarantee an increase in the average amount of energy available in each nano-machine (about more 60%), a decrease of the percentage of packet losses (up to 10%), a gain on the percentage of active nodes (ranging from 6% to 50%), and the reduction of the physical transmission rate (up to 20%). Moreover, they demonstrate that the proposed greedy strategy, despite its lowest computational complexity, guarantees results very close to those reached with the optimal strategy, thus becoming the best candidate for BANNETs. In authors’ humble opinion this study (with particular reference to the analysis of the packet loss ratio, measured under different network conditions) could be useful to find the most suitable combination of both network size and request rate that better satisfies requirements of real nano-medical applications.

The rest of this paper is organized as follows. Section  2 presents a background on both IoT and IoNT paradigms, by focusing the attention on both biomedical applications and energy-harvesting techniques available at the nano-scale. Section  3 discusses both the conceived health-care monitoring system and the designed energy-harvesting aware protocol suites. The performance evaluation of proposed solutions is investigated in Section  4. Finally, Section  5 draws the conclusions and discusses future activities.