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Postquantum cryptography for elevating security against attacks by quantum computers in the Internet of Everything (IoE) is still in its infancy. Most postquantum based cryptosystems have longer keys and signature sizes and require more computations that span several orders of magnitude in energy consumption and computation time, hence the sizes of the keys and signature are considered as another aspect of security by green design. To address these issues, the security solutions should migrate to the advanced and potent methods for protection against quantum attacks and offer energy efficient and faster cryptocomputations. In this context, a novel security framework Lightweight Postquantum ID-based Signature (LPQS) for secure communication in the IoE environment is presented. The proposed LPQS framework incorporates a supersingular isogeny curve to present a digital signature with small key sizes which is quantum-resistant. To reduce the size of the keys, compressed curves are used and the validation of the signature depends on the commutative property of the curves. The unforgeability of LPQS under an adaptively chosen message attack is proved. Security analysis and the experimental validation of LPQS are performed under a realistic software simulation environment to assess its lightweight performance considering embedded nodes. It is evident that the size of keys and the signature of LPQS is smaller than that of existing signature-based postquantum security techniques for IoE. It is robust in the postquantum environment and efficient in terms of energy and computations.

[EN] The IEEE 802.15.4 standard is one of the most widely used link layer technology for building Internet of Things (IoT). It specifies several physical layer options and MAC layer for meeting low-power and low-rate requirements of devices deployed in a network of IoT. The standard also specifies a synchronization scheme for devices connected in a star topology, operating in beacon-enabled (BE) mode using periodic beacons. The BE mode facilitates synchronization among devices for data transmission and is suitable for large networks to establish low duty-cycles. Absence of a such a scheme for a cluster-tree network has confined its application only to nonbeacon mode. The challenge here is to schedule beacon frame transmissions of multiple devices in a nonoverlapping manner to avoid beacon collisions. This paper tackles the problem of synchronization by proposing localized beacon synchronization (LBS) scheme, a distributed technique for beacon scheduling in cluster-tree network topologies. LBS uses 2-hop information and association order to compute beacon transmission offsets that better utilize the available time slots, incur fewer transmissions, and is highly scalable. Further, we analytically show that the schedulability of the proposed scheme is higher compared to other related schemes. In addition, we also address the important issue of resynchronization that has been ignored in all of the prior works. The proposed resynchronization mechanisms consider the interdependencies between synchronization and duty-cycling schemes and are shown to significantly lower the synchronization overhead when synchronization among devices is lost. This work was supported by the Science and Engineering Research Board, Department of Science and Technology, Govt. of India, under Grant ECR/2016/001651.

[EN] One of the major bottlenecks toward realizing IoT systems is the energy constraint of sensors. Prolonging network lifetime is a fundamental issue for implementing IoT systems. The energy optimization problem, being NP-hard in nature for scalable networks, has been addressed in the literature using traditional metaheuristic techniques. Quantum inspired metaheuristics have shown better performance than their traditional counterparts in solving such optimization problems in different domains. Toward this end, this article proposes a quantum inspired green communication framework for Energy Balancing in sensor enabled IoT systems (Q-EBIoT). First, an energy optimization model for sensor enabled IoT environments is presented, where energy consumption is derived as cost of the energy-oriented paths. Second, a quantum computing oriented solution is developed for the optimization problem focusing on energy centric solution representation, measurement, and rotation angle. The proposed solution is implemented to evaluate the comparative performance with the state-of-the-art techniques. The evaluation demonstrates the benefit of the proposed framework in terms of various energy-related metrics for sensor enabled IoT environments.

Energy efficiency is a significant characteristic of battery-run devices such as sensors, RFID and mobile phones. In the present scenario, this is the most prominent requirement that must be served while introducing a communication protocol for an IoT environment. IoT network success and performance enhancement depend heavily on optimization of energy consumption that enhance the lifetime of IoT nodes and the network. In this context, this paper presents a comprehensive review on energy efficiency techniques used in IoT environments. The techniques proposed by researchers have been categorized based on five different layers of the energy architecture of IoT. These five layers are named as sensing, local processing and storage, network/communication, cloud processing and storage, and application. Specifically, the significance of energy efficiency in IoT environments is highlighted. A taxonomy is presented for the classification of related literature on energy efficient techniques in IoT environments. Following the taxonomy, a critical review of literature is performed focusing on major functional models, strengths and weaknesses. Open research challenges related to energy efficiency in IoT are identified as future research directions in the area. The survey should benefit IoT industry practitioners and researchers, in terms of augmenting the understanding of energy efficiency and its IoT-related trends and issues.

In this paper, we propose a non-localization routing protocol for underwater wireless sensor networks (UWSNs), namely, the triangle metric based multi-layered routing protocol (TM2RP). The main idea of the proposed TM2RP is to utilize supernodes along with depth information and residual energy to balance the energy consumption between sensors. Moreover, TM2RP is the first multi-layered and multi-metric pressure routing protocol that considers link quality with residual energy to improve the selection of next forwarding nodes with more reliable and energy-efficient links. The aqua-sim package based on the ns-2 simulator was used to evaluate the performance of the proposed TM2RP. The obtained results were compared to other similar methods such as depth based routing (DBR) and multi-layered routing protocol (MRP). Simulation results showed that the proposed protocol (TM2RP) obtained better outcomes in terms of energy consumption, network lifetime, packet delivery ratio, and end-to-end delay.

Augmented Reality is a key technology that will facilitate a major paradigm shift in the way users interact with data and has only just recently been recognized as a viable solution for solving many critical needs [...]

AbstractCellular networks based on new generation standards are the major enabler for Internet of things (IoT) communication. Narrowband-IoT and Long Term Evolution for Machines are the newest wide area network-based cellular technologies for IoT applications. The deployment of unmanned aerial vehicles (UAVs) has gained the popularity in cellular networks by using temporary ubiquitous coverage in the areas where the infrastructure-based networks are either not available or have vanished due to some disasters. The major challenge in such networks is the efficient UAVs deployment that covers maximum users and area with the minimum number of UAVs. The performance and sustainability of UAVs is largely dependent upon the available residual energy especially in mission planning. Although energy harvesting techniques and efficient storage units are available, but these have their own constraints and the limited onboard energy still severely hinders the practical realization of UAVs. This paper employs neglected parameters of UAVs energy consumption in order to get actual status of available energy and proposed a solution that more accurately estimates the UAVs operational airtime. The proposed model is evaluated in test bed and simulation environment where the results show the consideration of such explicit usage parameters achieves significant improvement in airtime estimation.