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Device-Independent Quantum Secure Direct Communication (DI-QSDC) enhances quantum cryptography by enabling secure message transmission without relying on the trustworthiness of the devices involved. This approach mitigates risks associated with compromised or untrusted devices, common in traditional quantum communication. In this paper, we propose the first of its kind DI-QSDC protocol with user identity authentication. This ensures the authenticity of both the sender and receiver prior to message exchange. We then discuss the security of the proposed protocol against common attacks, demonstrating that no eavesdropper gains any information from either the quantum or the classical channel. Next, we implement the protocol on IBM's quantum hardware and evaluate its performance in a realistic noisy environment. Additionally, by simulating common attack models, we showcase that the protocol is secure against any eavesdropper in the channel. These findings highlight the protocol's robust security and practical feasibility for real-world secure quantum communication., Comment: Accepted in 37th IEEE International System-on-Chip Conference (SOCC) to be held in Dresden, Germany, September 16-19, 2024

In this article, we propose an energy-efficient data gathering scheme for wireless sensor network called Sleep-Route, which splits the sensor nodes into two sets - active and dormant (low-power sleep). Only the active set of sensor nodes participate in data collection. The sensing values of the dormant sensor nodes are predicted with the help of an active sensor node. Virtual Sensing Framework (VSF) provides the mechanism to predict the sensing values by exploiting the data correlation among the sensor nodes. If the number of active sensor nodes can be minimized, a lot of energy can be saved. The active nodes' selection must fulfill the following constraints - (i) the set of active nodes are sufficient to predict the sensing values of the dormant nodes, (ii) each active sensor nodes can report their data to the sink node (directly or through some other active node(s)). The goal is to select a minimal number of active sensor nodes so that energy savings can be maximized. The optimal set of active node selection raise a combinatorial optimization problem, which we refer as Sleep-Route problem. We show that Sleep-Route problem is NP-hard. Then, we formulate an integer linear program (ILP) to solve the problem optimally. To solve the problem in polynomial time, we also propose a heuristic algorithm that performs near optimally.

Wireless sensor networks (WSNs) have enabled continuous monitoring of an area of interest (body, room, region, etc.) while eliminating expensive wired infrastructure. Typically in such applications, wireless sensor nodes report the sensed values to a sink node, where the information is required for the end-user. WSNs also provide the flexibility to the end-user for choosing several parameters for the monitoring application. For example, placement of sensors, frequency of sensing and transmission of those sensed data. Over the years, the advancement in embedded technology has led to increased processing power and memory capacity of these battery powered devices. However, batteries can only supply limited energy, thus limiting the lifetime of the network. In order to prolong the lifetime of the deployment, various efforts have been made to improve the battery technologies and also reduce the energy consumption of the sensor node at various layers in the networking stack. Of all the operations in the network stack, wireless data transmission and reception have found to consume most of the energy. Hence many proposals found in the literature target reducing them through intelligent schemes like power control, reducing retransmissions, etc. In this article we propose a new framework called Virtual Sensing Framework (VSF), which aims to sufficiently satisfy application requirements while conserving energy at the sensor nodes., Comment: Accepted for publication in IEEE Twentieth National Conference on Communications (NCC-2014)

Accurate and fast packet delivery rate (PDR) estimation, used in evaluating wireless link quality, is a prerequisite to increase the performance of mobile, multi-hop and multi-rate wireless ad hoc networks. Unfortunately, contemporary PDR estimation methods, i.e. beacon-based packet counting in Estimated Transmission Time and Expected Transmission Count metrics, have unsatisfactory performance. Therefore, in this paper we propose a novel PDR estimation method based on SNR profiles. We classify all possible link quality estimation methods and compare them analytically against our design. Results show that it leads to a more efficient link quality estimation. Further investigations with the prototype implementation of our method in IEEE 802.11b/g testbeds reveal that the accuracy of PDR estimation in mobile scenarios can be improved up to 50% in comparison to generic packet-based PDR. Experiments with the same prototype on link and routing layers for different measurement scenarios show that it leads to a better rate adaptation and route selection in the form of end-to-end throughput increase compared to traditional packet counting methods.