Current Issue : July - September Volume : 2019 Issue Number : 3 Articles : 5 Articles
Internet of Vehicle (IoV) is playing an increasingly important role in constructing an Intelligent Transport System (ITS) of safety,\nefficiency, and green. Safety applications such as emergency warning and collision avoidance require high reliability and timeliness\nfor data transmission. In order to address the problems of slow response and local broadcast storm commonly existing among\nwaiting-based relay schemes of emergency messages, a local topology information sensing technology-based broadcast (LISCast)\nprotocol is proposed in this paper, making use of the advantage of probability-based forwarding scheme in redundancy inhibition.\nAccording to the beacon broadcasted periodically between vehicles, LISCast collects information about number and distribution\nof neighbor, from which the characteristic information such as effective candidate number, maximum forwarding distance, and\nglobal traffic density are extracted. Through embedding the characteristic information into the head of broadcast packets by the\nmessage sender for assisting in making relay decision, the alternative receivers uniformly schedule forwarding priorities in a\ndistributed and adaptive way. LISCast works without the help of a roadside unit and generates a little more overhead. The\nsimulation results show that LISCast improves the ability to adapt to dynamic topology by optimizing the performance of delay,\nredundancy, and broadcast efficiency upon the condition of satisfying the high level of transmission reliability....
The convergence of automobiles and ICT (information and communication technology) has become a new paradigm for the\ndevelopment of next-generation vehicles. In particular, connected cars represent themost in-demand automobile-ICTconvergence\ntechnology. With the development of 5G technology, communication between vehicle and external device using autonomous\ndriving and Internet of things (IoT) technology has been remarkably developed. Control of vehicles using smart phones has\nbecome a routine feature, and over 200 Android apps are in use. However, Android apps are easy to tamper by repackaging\nand allowing hackers to attack vehicles with using this vulnerability, which can lead to life-critical accidents. In this study, we\nanalyze the vulnerabilities of connected car environments when connecting with IoT technologies and demonstrate the possibility\nof cyberattack by performing attack experiments using real cars and repackaging for commercial apps. Furthermore, we propose\na realistic security technology as a countermeasure to attain safety against cyberattacks. To evaluate the safety of the proposed\nmethod, a security module is developed and a performance evaluation is conducted on an actual vehicle....
The spectrum sharing approach (SSA) has emerged as a cost-efficient solution for the enhancement of spectrum utilization to meet the\nstringent requirements of 5G systems. However, the realization of SSA in 5G mmWave cellular networks from technical and regulatory\nperspectives could be challenging. Therefore, in this paper, an analytical framework involving a flexible hybrid mmWave SSA is presented\nto assess the effectiveness of SSA and investigate its influence on network functionality in terms of independence and fairness among\noperators. Two mmWave frequencies (28GHz and 73 GHz) are used with different spectrum bandwidths. Various access models have\nbeen presented for adoption by four independent mobile network operators that incorporate three types of spectrum allocation (exclusive,\nsemipooled, and fully pooled access). Furthermore, an adaptive multi-state mmWave cell selection scheme is proposed to associate typical\nusers with the tagged mmWave base stations that provide a great signal-to-interference plus noise ratio, thereby maintaining reliable\nconnections and enriching user experience. Numerical results show that the proposed strategy achieves considerable improvement in\nterms of fairness and independence among operators, which paves the way for further research activities that would provide better insight\nand encourage mobile network operators to rely on SSA....
In the IoT era, 5G will enable various IoT services such as broadband access everywhere, high user and devices mobility, and\nconnectivity of massive number of devices. Radio environment map (REM) can be applied to improve the utilization of radio\nresources for the access control of IoT devices by allocating them reasonable wireless spectrum resources. However, the primary\nproblem of constructing REM is how to collect the large scale of data. Mobile crowd sensing (MCS), leveraging the smart devices\ncarried by ordinary people to collect information, is an effective solution for collecting the radio environment information for\nbuilding the REM. In this paper, we build a REM collecting prototype system based on MCS to collect the data required by the\nradio environment information. However, limited by the budget of the platform, it is hard to recruit enough participants to join the\nsensing task to collect the radio environment information. This will make the radio environment information of the sensing area\nincomplete, which cannot describe the radio information accuracy. Considering that the Kriging algorithm has been widely used\nin geostatistics principle for spatial interpolation for Kriging giving the best unbiased estimate with minimized variance, we utilize\nthe Kriging interpolation algorithm to infer complete radio environment information from collected sample radio environment\ninformation data. The interpolation performance is analyzed based on the collected sample radio environment information data.\nWe demonstrate experiments to analyze the Kriging interpolation algorithm interpolation results and error and compared them\nwith the nearest neighbor (NN) and the inverse distance weighting (IDW) interpolation algorithms. Experiment results show that\nthe Kriging algorithm can be applied to infer radio environment information data based on the collected sample data and the\nKriging interpolation has the least interpolation error....
When the connection to Internet is not available during networking activities, an opportunistic approach exploits the encounters\nbetweenmobile human-carried devices for exchanging information.When users encounter each other, their handheld devices can\ncommunicate in a cooperative way, using the encounter opportunities for forwarding their messages, in a wireless manner. But,\nanalyzing real behaviors, most of the nodes exhibit selfish behaviors, mostly to preserve the limited resources (data buffers and\nresidual energy). That is the reason why node selfishness should be taken into account when describing networking activities: in\nthis paper, we first evaluate the effects of node selfishness in opportunistic networks.Then, we propose a routing mechanism for\nmanaging node selfishness in opportunistic communications, namely, SORSI (Social-based Opportunistic Routing with Selfishness\ndetection and Incentive mechanisms). SORSI exploits the social-based nature of node mobility and other social features of nodes\nto optimize message dissemination together with a selfishness detection mechanism, aiming at discouraging selfish behaviors and\nboosting data forwarding. Simulating several percentages of selfish nodes, our results on real-world mobility traces showthat SORSI\nis able to outperform the social-based schemes Bubble Rap and SPRINT-SELF, employing also selfishness management in terms\nof message delivery ratio, overhead cost, and end-to-end average latency. Moreover, SORSI achieves delivery ratios and average\nlatencies comparable to Epidemic Routing while having a significant lower overhead cost....
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