The rise of the intelligent, local charging facilitation and environmentally friendly aspects of electric vehicles (EVs) has grabbed the attention of many end-users. However, there are still numerous challenges faced by researchers trying to put EVs into competition with internal combustion engine vehicles (ICEVs). The major challenge in EVs is quick recharging and the selection of an optimal charging station. In this paper, we present the most recent research on EV charging management systems and their role in smart cities. EV charging can be done either in parking mode or on-the-move mode. This review work is novel due to many factors, such as that it focuses on discussing centralized and distributed charging management techniques supported by a communication framework for the selection of an appropriate charging station (CS). Similarly, the selection of CS is evaluated on the basis of battery charging as well as battery swapping services. This review also covered plug-in charging technologies including residential, public and ultra-fast charging technologies and also discusses the major components and architecture of EVs involved in charging. In a comprehensive and detailed manner, the applications and challenges in different charging modes, CS selection, and future work have been discussed. This is the first attempt of its kind, we did not find a survey on the charging hierarchy of EVs, their architecture, or their applications in smart cities.
Delay/Disruption Tolerant Networks (DTNs) are a special category of IntermittentlyCon-nectedNetworks (ICNs). It has features such as long-delay, frequent-disruption, asymmetrical-data-rates, and high-bundle-error-rates. DTNs have been mainly developed for planet-to-planet networks, commonly known as Inter-Planetary-Networks (IPNs). However, DTNs have shown undimmed potency in challenged communication networks, such as DakNet, ZebraNet, KioskNet and WiderNet. Due to unique characteristics (Intermittent-connectivity and long-delay) DTNs face tough/huge/several challenges in various research areas i.e bundle-forwarding, key-distribution, privacy, bundle-fragmentation, and malicious/selfish nodes particularly. Malicious/selfish nodes launch various catastrophic attacks, this includes, fake packet attacks, selective packet drops attacks, and denial-of-service/flood attacks. These attacks inevitably consume limited resources (persistent-buffer and bandwidth) in DTNs. Fake-packet and selective-packet-drops attacks are top among the challenging attacks in ICNs. The focus of this article is on critical analyses of fake-packet and selective-packet-drops attacks. The panoramic view on misbehavior nodes mitigation algorithms are analyzed, and evaluated mathematically through several parameters for detection probability/accuracy. This article presents a novel algorithm to detects/mitigates fake-packet and selective-packet-drops attacks. Trace-driven simulation results show the proposed algorithm of this article accurately (enhanced detectionaccuracy, reduces false-positive/false-negative rates) detects malicious nodes which launch fake-packet and selective-packet-drops attacks, unlike previously proposed algorithms which detect only one attack (fakepacket or packet-drops at a time) or detect only malicious path (do not exactly detect malicious nodes which launch attacks).
The fast increase in adoption and development of Electric Vehicles (EVs) has invited a significant challenge to the existing charging management techniques and infrastructure. It is necessary to efficiently manage a large number of mobile EVs. As compared to fuel and gasoline type vehicles, the EV has a limited driving range and needs to recharge its battery frequently during long journeys. Hence, with plug-in charging services one major concern is the long duration of battery recharging. In this paper, we employ heterogeneous BS (Battery Switching) technology to provide an alternative charging option to minimize the charging duration of EV. Furthermore, enabling BS reservation in a centralized manner for mobile EVs, load balancing algorithm and optimal selection of Battery Switching Station (BSS) across the network are proposed. In addition, we suggest a scheduling technique for depleted batteries to recharge effectively in BSS to minimize power loss and queuing time at selected BSS. We have conducted a performance evaluation by comparing the proposed scheme with other benchmarks, in terms of average trip duration, total trip energy consumption, etc. Finally, it is proven that the battery stock is managed across the network efficiently through the proposed scheme.
The recent advancements in the web allow users to generate multimedia content. It may cause an immense multimedia information proliferation and demands innovative tools to discover multimedia content. The researchers have devised numerous state-of-the-art approaches; however, analysis to confirm the efficacy has little emphasis. This study investigates users' complex multimedia informationseeking behavior over state-of-the-art web search systems to unveil the user's information-seeking issues. Our research employs between-subjects study and post hoc analysis strategies to analyze participants' seeking characteristics. The study design adopted statistical hypothesis testing to consolidate previous user behavioral studies, confirm existing studies, and present recommended practices for future general-purpose web search engines. The participants were assigned Google and an advanced discovery search system using the same multimedia dataset to ensure the obtained results' credibility. The primary behavioral parameters include search efforts, multimedia content exploration, search user interface (SUI), information management and presentation, and user cognition. This study uncovers several inadequacies of the search engines in meeting users' complex discovery needs, including 29.6% less user engagement, 43% system and searching dissatisfaction, and 32% less knowledge acquisition with 63.9% increased clicking effort on traditional search engines. The results confirmed previous user studies and suggest novel research recommendations statistically significant in multimedia information exploration-related endeavors.
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