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Network lifetime maximization has received continuous attention as green computing in wireless sensor networks. Recently, controlled mobility-based green computing has witnessed significant attention from academia and industrial research labs. It is due to the growing number of sensor-based services in mobility friendly nonhostile environments in our daily life. The intelligent mobility-aided repositioning of sensors is significantly challenging considering the critical constraints including irregular power depletion, static normal sensors, the correlation between sensor position, and coverage and connectivity. In this context, this paper proposes a network lifetime maximization framework based on balanced tree node switching. Specifically, a balanced tree-based network model for wireless sensor networks is designed focusing on energy consumption of sensor nodes in tree-based networks. The problem of lifetime maximization in tree-based network is identified considering energy loss rate, path load, and balancing factor. Two node-shifting algorithms are developed, namely, energy-based shifting and load-based shifting for balancing tree-based network in terms of energy. Analytical and simulation experimentbased comparative performance evaluation attests the benefit of the proposed framework as compared to the state-of-the-art techniques considering a number of energy-oriented metrics for wireless networks.Focusing on efficient and balanced energy consumption for uniform energy depletion among sensors, 2,4 various green computing techniques have been suggested. It includes duty cycle management, data aggregation, and controlled mobility-based lifetime maximization for green computing in WSNs. 5-9 One of the major constraints in duty cycle based techniques is the overhead involved in constructing broadcasting sets for assigning duty to the complete network. 10-14 It creates major network overhead and reduces actual data transmission capability of the network. Most of the data aggregation techniques are based on clustering approach, where networks are divided into manageable clusters to balance energy consumption in different areas of the networks. One of the major problem of the clusteringbased green computing is the frequent require of cluster head selection and updating. 11,[15][16][17][18][19] Recently, controlled mobility-based green computing in WSNs has witnessed considerable attention because of the growing significance of sensor technology in mobility-enabled nonhostile environment. In the mobility-based green computing, some designated mobile sensors intelligently change the network topology by repositioning their locations for balancing energy consumption among sensors. The intelligent repositioning is significantly challenging considering the 3 critical constraints of the network and sensor specifications. [20][21][22][23] The constraints include uneven power depletion, static nature of majority of normal sensors, and strong correlation between sensor position, and coverage and connectivity. In literature o...

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Recently, Internet of vehicles (IoV) has witnessed significant research and development attention in both academia and industries due to the potential towards addressing traffic incidences and supporting green mobility. With the growing vehicular network density, jamming signal centric security issues have become challenging task for IoV network designers and traffic applications developers. Global positioning system (GPS) and roadside unit (RSU) centric related literature on location-based security approaches lacks signal characteristics consideration for identifying vehicular network intruders or jammers. In this context, this paper proposes a machine learning oriented as Delimitated Anti Jamming protocol for vehicular traffic environments. It focuses on jamming vehicle's discriminated signal detection and filtration for revealing precise location of jamming effected vehicles. In particular, a vehicular jamming system model is presented focusing on localization of vehicles in delimitated jamming environments. A foster rationalizer is employed to examine the frequency changes caused in signal strength due to the jamming or external attacks. A machine learning open-sourced algorithm namely, CatBoost has been utilized focusing on decision tree relied algorithm to predict the locations of jamming vehicle. The performance of the proposed anti jammer scheme is comparatively evaluated with the state of the art techniques. The evaluation attests the resistive characteristics of the anti-jammer technique considering precision, recall, F1 score and delivery accuracy metrics. INDEX TERMS Internet of Vehicles, location verification, jamming signal, machine learning. I. INTRODUCTION Vehicular networks are emerging as a new promising field of wireless technology, where security is one of the major research theme [1]. A cooperative group of sensor-enabled vehicles operating in a dynamic road traffic network environment by interconnecting among on-road vehicles and, with neighboring Road Side Units (RSUs) are referred to as Vehicular Ad-hoc Networks (VANETs) [2]. The three sorts of data transmission to disseminate cooperative messages includes Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) The associate editor coordinating the review of this article and approving it for publication was Guan Gui. and Infrastructure-to-Vehicle (I2V) (see Fig. 1). The sensor enabled vehicles can communicate with each other in V2V data transmission either through direct wireless range or indirect multi-hop mode of communication [3]. V2I represents the communication among vehicles and the roadside infrastructures for avoiding vehicular incidences and enabling road safety. VANETs can support a promising intelligent transportation system technology for many real time traffic applications including safety message dissemination, dynamic route planning, content distribution, gaming, and Internet of connected vehicles, connected autonomous vehicles, electric vehicles and related smart applications [4]. This real time traffic information orient...

Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and speed.

Sensing coverage problem in wireless sensor networks is a measure of quality of service (QoS). Coverage refers to how well a sensing field is monitored or tracked by the sensors. Aim of the paper is to have a priori estimate for number of sensors to be deployed in a harsh environment to achieve desired coverage. We have proposed a new sensing channel model that considers combined impact of shadowing fading and multipath effects. A mathematical model for calculating coverage probability in the presence of multipath fading combined with shadowing is derived based on received signal strength (RSS). Further, the coverage probability derivations obtained using Rayleigh fading and lognormal shadowing fading are validated by node deployment using Poisson distribution. A comparative study between our proposed sensing channel model and different existing sensing models for the network coverage has also been presented. Our proposed sensing model is more suitable for realistic environment since it determines the optimum number of sensors required for desirable coverage in fading conditions.

Abstract-Vehicular localization has witnessed significant attention due to the growing number of location-based services in vehicular cyber physical systems (VCPS). In vehicular localization, GPS outage is a challenging issue considering the growing urbanization including high rise buildings, multi-level flyovers and bridges. GPS-free and GPS-assisted cooperative localization techniques have been suggested in literature for GPS outage. Due to the cost of infrastructure in GPS-free techniques, and the absence of location aware neighbors in cooperative techniques, efficient and scalable localization is a challenging task in VCPS. In this context, this paper proposes a geometry-based localization for GPS outage in VCPS (GeoLV). It is a GPSassisted localization which reduces location aware neighbor constraint of cooperative localization. GeoLV utilizes mathematical geometry to estimate vehicle location focusing on vehicular dynamics and road trajectory. The static and dynamic relocations are performed to reduce the impact of GPS outage on location-based services. A case study based comparative performance evaluation has been carried out to assess the efficiency and scalability of GeoLV. It is evident from the results that GeoLV handles both shorter and longer GPS outage problem better than the state-of-the-art techniques in VCPS. Index Terms-Vehicular cyber physical system, GPS outage, Vehicular communication, Vehicular localization

Health monitoring using biomedical sensors has witnessed significant attention in recent past due to the evolution of a new research area in sensor network known as Wireless Body Area Networks (WBANs). In WBANs, a number of implantable, wearable, and off-body biomedical sensors are utilized to monitor various vital signs of patient’s body for early detection, and medication of grave diseases. In literature, a number of Medium Access Control (MAC) protocols for WBANs have been suggested for addressing the unique challenges related to reliability, delay, collision and energy in the new research area. The design of MAC protocols is based on multiple access techniques. Understanding the basis of MAC protocol designs for identifying their design objectives in broader perspective, is a quite challenging task. In this context, this paper qualitatively reviews MAC protocols for WBANs. Firstly, 802.15.4 and 802.15.6 based MAC Superframe structures are investigated focusing on design objectives. Secondly, different multiple access techniques such as TDMA, CSMA/CA, Slotted Aloha and Hybrid are explored in terms of design goals. Thirdly, a two-layered taxonomy is presented for MAC protocols. First layer classification is based on multiple access techniques, whereas second layer classification is based on design objectives and characteristics of MAC protocols. Critical and qualitative analysis is carried out for each considered MAC protocol. Comparative study of different MAC protocols is also performed. Finally, some open research challenges in the area are identified with initial research directions.