TraPy-MAC: Traffic Priority Aware Medium Access Control Protocol for Wireless Body Area Network

Recently, Wireless Body Area Network (WBAN) has witnessed significant attentions in research and product development due to the growing number of sensor-based applications in healthcare domain. Design of efficient and effective Medium Access Control (MAC) protocol is one of the fundamental research themes in WBAN. Static on-demand slot allocation to patient data is the main approach adopted in the design of MAC protocol in literature, without considering the type of patient data specifically the level of severity on patient data. This leads to the degradation of the performance of MAC protocols considering effectiveness and traffic adjustability in realistic medical environments. In this context, this paper proposes a Traffic Priority-Aware MAC (TraPy-MAC) protocol for WBAN. It classifies patient data into emergency and non-emergency categories based on the severity of patient data. The threshold value aided classification considers a number of parameters including type of sensor, body placement location, and data transmission time for allocating dedicated slots patient data. Emergency data are not required to carry out contention and slots are allocated by giving the due importance to threshold value of vital sign data. The contention for slots is made efficient in case of non-emergency data considering threshold value in slot allocation. Moreover, the slot allocation to emergency and non-emergency data are performed parallel resulting in performance gain in channel assignment. Two algorithms namely, Detection of Severity on Vital Sign data (DSVS), and ETS Slots allocation based on the Severity on Vital Sign (ETS-SVS) are developed for calculating threshold value and resolving the conflicts of channel assignment, respectively. Simulations are performed in ns2 and results are compared with the state-of-the-art MAC techniques. Analysis of results attests the benefit of TraPy-MAC in comparison with the state-of-the-art MAC in channel assignment in realistic medical environments

Toward Energy-Oriented Optimization for Green Communication in Sensor Enabled IoT Environments

[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.Kumar, S.; Kaiwartya, O.; Rathee, M.; Kumar, N.; Lloret, J. (2020). Toward Energy-Oriented Optimization for Green Communication in Sensor Enabled IoT Environments. IEEE Systems Journal. 14(4):4663-4673. https://doi.org/10.1109/JSYST.2020.29758234663467314

Multi-metric Geographic Routing for Vehicular Ad hoc Networks

Maintaining durable connectivity during data forwarding in Vehicular Ad hoc Networks has witnessed significant attention in the past few decades with the aim of supporting most modern applications of Intelligent Transportation Systems (ITS). Various techniques for next hop vehicle selection have been suggested in the literature. Most of these techniques are based on selection of next hop vehicles from fixed forwarding region with two or three metrics including speed, distance and direction, and avoid many other parameters of urban environments. In this context, this paper proposes a Multi-metric Geographic Routing (M-GEDIR) technique for next hop selection. It selects next hop vehicles from dynamic forwarding regions, and considers major parameters of urban environments including, received signal strength, future position of vehicles, and critical area vehicles at the border of transmission range, apart from speed, distance and direction. The performance of M-GEDIR is evaluated carrying out simulations on realistic vehicular traffic environments. In the comparative performance evaluation, analysis of results highlight the benefit of the proposed geographic routing as compared to the state-of-the-art routing protocols

Towards Anycasting-driven Reservation System for Electric Vehicle Battery Switch Service

Electro-Mobility has become an increasingly important research problem in urban city. Due to the limited electricity of battery, Electric Vehicle (EV) drivers may experience discomfort for long charging waiting time. Different from plug-in charging technology, we investigate the battery switch technology to improve EV drivers’ comfort (e.g., reduce the service waiting time from tens of minutes to a few minutes), by benefiting from switchable (fully-recharged) batteries cycled at Charging Stations (CSs). Since demand hotspot may still happen at CSs (e.g., running out of switchable batteries), incoming EVs may wait additional time to get their battery switched, and thus the EV driver’s comfort is degraded. Firstly, we propose a centralized reservation enabling service, considering EVs’ reservations (including arrival time, expected charging time of their batteries to be depleted) to optimally coordinate their battery switch plans. Secondly, a decentralized system is further proposed, by facilitating the Vehicle-to-Vehicle (V2V) anycasting to deliver EV’s reservations. This helps to address some of the privacy issues that can be materialized in centralized system and reduce communication cost (e.g., through cellular network for reservation making). Results under the Helsinki city scenario show a trade-off between comparable performance (e.g., service waiting time, number of switched batteries) and cellular network cost for EVs’ reservations delivery

An EV Charging Management System Concerning Drivers' Trip Duration and Mobility Uncertainty

With continually increased attention on Electric Vehicles (EVs) due to environment impact, public Charging Stations (CSs) for EVs will become common. However, due to the limited electricity of battery, EV drivers may experience discomfort for long charging waiting time during their journeys. This often happens when a large number of (on-the-move) EVs are planning to charge at the same CS, but it has been heavily overloaded. With this concern, in an EV charging management system, we focus on CS-selection decision making and propose a scheme to manage EVs' charging plans, to minimize drivers' trip duration through intermediate charging at CSs. The proposed scheme jointly considers EVs' anticipated charging reservations (including arrival time, expected charging time) and parking duration at CSs. Furthermore, by tackling mobility uncertainty that EVs may not reach their planned CSs on time (due to traffic jams on the road), a periodical reservation updating mechanism is designed to adjust their charging plans. Results under the Helsinki city scenario with realistic EV and CS characteristics show the advantage of our proposal, in terms of minimized drivers' trip duration, as well as charging performance at the EV and CS sides

Electric Vehicle Charging Recommendation and Enabling ICT Technologies: Recent Advances and Future Directions

The introduction of Electric Vehicles (EV) will have a significant impact on the sustainable economic development of urban city. However, compared with traditional gasoline-powered vehicles, EVs currently have limited range, which necessitates regular recharging. Considering the limited charging infrastructure currently available in most countries, infrastructure investments and Renewable Energy Sources (RES) are critical. Thus, service quality provisioning is necessary for realizing EV market. Unlike numerous previous works which investigate "charging scheduling" (referred to when/whether to charge) for EVs already been parked at home/Charging Stations (CSs), a few works focus on “charging recommendation” (refer to where/which CS to charge) for on-the-move EVs. The latter use case cannot be overlooked as it is the most important feature of EVs, especially for driving experience during journeys. On-the-move EVs will travel towards appropriate CSs for charging based on smart decision on where to charge, so as to experience a shorter waiting time for charging. The effort towards sustainable engagement of EVs has not attracted enough attention from both industrial and academia communities. Even if there have been many charging service providers available, the utilization of charging infrastructures is still in need of significant enhancement. Such a situation certainly requires the popularity of EVs towards the sustainable, green and economic market. Enabling the sustainability requires a joint contribution from each domain, e.g., how to guarantee accurate information involved in decision making, how to optimally guide EV drivers towards charging place with the least waiting time, how to schedule charging services for EVs being parked within grid capacity. Achieving this goal is of importance towards a positioning of efficient, scalable and smart ICT framework, makes it feasible to learn the whole picture of grid: - Necessary information needs to be disseminated between stakeholders CSs and EVs, e.g., expected queuing time at individual CSs. In this context, how accurate CSs condition information plays an important role on the optimality of charging recommendation. - Also, it is very time-consuming for the centralized Global Controller (GC) to achieve optimization, by seamlessly collecting data from all EVs and CSs, The complexity and computation load of this centralized solution, increases exponentially with the number of EVs. This paper summaries the recent interdisciplinary research works on EV charging recommendation along with novel ICT frameworks, with an original taxonomy on how Intelligent Transportation Systems (ITS) technologies support the EV charging use case. Future directions are also highlighted to promote the future research

BEST-Blockchain-Enabled Secure and Trusted Public Emergency Services for Smart Cities Environment

[EN] In the last few years, the Internet of things (IoT) has recently gained attention in developing various smart city applications such as smart healthcare, smart supply chain, smart home, smart grid, etc. The existing literature focuses on the smart healthcare system as a public emergency service (PES) to provide timely treatment to the patient. However, little attention is given to a distributed smart fire brigade system as a PES to protect human life and properties from severe fire damage. The traditional PES are developed on a centralised system, which requires high computation and does not ensure timely service fulfilment. Furthermore, these traditional PESs suffer from a lack of trust, transparency, data integrity, and a single point of failure issue. In this context, this paper proposes a Blockchain-Enabled Secure and Trusted (BEST) framework for PES in the smart city environment. The BEST framework focuses on providing a fire brigade service as a PES to the smart home based on IoT device information to protect it from serious fire damage. Further, we used two edge computing servers, an IoT controller and a service controller. The IoT and service controller are used for local storage and to enhance the data processing speed of PES requests and PES fulfilments, respectively. The IoT controller manages an access control list to keep track of registered IoT gateways and their IoT devices, avoiding misguiding the PES department. The service controller utilised the queue model to handle the PES requests based on the minimum service queue length. Further, various smart contracts are designed on the Hyperledger Fabric platform to automatically call a PES either in the presence or absence of the smart-home owner under uncertain environmental conditions. The performance evaluation of the proposed BEST framework indicates the benefits of utilising the distributed environment and the smart contract logic. The various simulation results are evaluated in terms of service queue length, utilisation, actual arrival time, expected arrival time, number of PES departments, number of PES providers, and end-to-end delay. These simulation results show the effectiveness and feasibility of the BEST framework.This research is Funded by the B11 unit of assessment, Centre for Computing and Informatics Research Centre, Department of Computer Science, Nottingham Trent University, UK. This work is supported by the SC&SS, Jawaharlal Nehru University, New Delhi, India.Bhawana; Kumar, S.; Rathore, RS.; Mahmud, M.; Kaiwartya, O.; Lloret, J. (2022). BEST-Blockchain-Enabled Secure and Trusted Public Emergency Services for Smart Cities Environment. Sensors. 22(15). https://doi.org/10.3390/s22155733221

Northwestern University in Chicago(FROM ABROAD)

<p>Comparative analysis of impact of percentage of malicious nodes on interruption detection under dynamic condition.</p

Physical Layer Security in Vehicular Communication Networks in the Presence of Interference

This paper studies the physical layer security of a vehicular communication network in the presence of interference constraints by analysing its secrecy capacity. The system considers a legitimate receiver node and an eavesdropper node, within a shared network, both under the effect of interference from other users. The double-Rayleigh fading channel is used to capture the effects of the wireless communication channel for the vehicular network. We present the standard logarithmic expression for the system capacity in an alternate form, to facilitate analysis in terms of the joint moment generating functions (MGF) of the random variables representing the channel fading and interference. Closed-form expressions for the MGFs are obtained and Monte-Carlo simulations are provided throughout to validate the results. The results show that performance of the system in terms of the secrecy capacity is affected by the number of interferers and their distances. The results further demonstrate the effect of the uncertainty in eavesdropper location on the analysis