Nanonetworks for Internet of Nano-Things (IoNT)

Nanonetworking utilizing electromagnetic and molecular communication paradigm is one of the most challenging domains of nanotechnology. Nanonetworking employs nanomachines that perform tasks such as sensing, actuation, processing, and computation in nanoscale for efficient biomedical applications. It promises new solutions for many healthcare applications, such as diagnostic devices, target (tumor) detection and tracking, as well as localized drug delivery. The biomedical approaches employ bioinspired nanosensors, often consisting of biological cells, molecular motors, bacteria or synthetic molecules, or genetically engineered cells termed as bio-nanosensors.

We study the impact of nanonetwork-based systems for different models towards healthcare applications in IoNT while ensuring high network-throughput and data delivery ratio, as well as low energy consumption and network delay. Additionally, we model and analyze the Dengue Virus transmission inside the body from the point of a mosquito bite to the targeted organs as a communication system, theoretically, in the light of molecular communication paradigm.

 

Asymmetric data delivery in Nanonetworks

In this work, we envisage an architecture of nanonetworks-based Coronary Heart Disease (CHD) monitoring, consisting of nano-macro interface (NM) and nanodevice-embedded Drug Eluting Stents (DESs), termed as nanoDESs. We study the problem of asymmetric data delivery in such nanonetworks-based systems and propose a simple distance-aware power allocation algorithm, named catch-the-pendulum, which optimizes the energy consumption of nanoDESs for communicating data from the underlying nanonetworks to radio frequency (RF) based macro-scale communication networks.

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In this paper, we study the problem of asymmetric data delivery in various types of network topologies. We propose a distributed topology control algorithm based on the solution of the well-known network flow problem for addressing asymmetric data delivery. The generated topology is dynamic in the sense that it changes according to the energy levels of the nanoDESs. The proposed algorithm helps establish the topology and balance the load on nanoDESs. The proposed approach changes the topology if there arises a need to balance the energy content of the nanoDESs.

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Collision in Bio-nanosensor Network

In this paper, we address the issue of catastrophic collision — a phenomenon which exhibits recurrent collisions of femtosecond long pulse symbols emanating from the nanodevices in a Wireless Bio-nanosensor Network (WB2N). The existing method of choosing the symbol rate does not completely avoid catastrophic collision. The severity of collision is further pronounced when molecular absorption noise gets compounded. In present work, we analyze the catastrophic collision and model the collision for WB2Ns to be successful e-health system.

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In this work, we propose the phenomenon of collision in multi-conjugation of multiple carrier bacteria at the side of receiver nanodevice. We show the effect of this conjugation-based collision on the maximum achievable throughput of the network, using a simple graph-theoretic approach, namely, Maximum Weight Bipartite Matching. The proposed Max Throughput algorithm runs in polynomial time. The effect of various spatial distribution of nanodevices on the maximum achievable throughput are extensively analyzed and evaluated.

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Energy Management in Nanonetworks

In this work, we envisage the architecture of Green Wireless Body Area Nanonetwork (GBAN) as a collection of nanodevices, in which each device is capable of communicating in both the molecular and wireless electromagnetic communication modes. The term green refers to the fact that the nanodevices in such a network can harvest energy from their surrounding environment. It is observed that the rate of energy harvesting is nonlinear and sporadic in nature. We specifically address the energy management problem in a ubiquitous healthcare monitoring scenario and formulate it as a cooperative Nash Bargaining game.

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Channel characterization in Virus Nanonetworks

Dengue, a mosquito-borne viral disease, poses a global threat owing to the unavailability of any specific therapeutics. Since prevention is only restricted to vector control, a clear understanding of Dengue Virus (DENV) transmission within an infected host is essential. The dynamics of DENV transmission addressed in light of molecular communication paradigm is promising in providing crucial information accounting for disease control that can lead to the development of novel approaches to clear the virus infection. An essential question is whether we can model the propagation behavior of DENV, and in particular its impact as it propagates through various sub-systems of the human body.

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