In the last few years, due to the benefit of solving large-scale computational problems, researchers have been developed multicloud infrastructures. The trust-related issue in multiclouds includes more complicated content and new problems. A new trust management framework for multicloud environments is proposed in this article. The proposed framework used a combination of objective and subjective trust values to calculate the cloud service provider’s trust values. This new framework can identify and rectify fake feedbacks from other feedbacks. Another advantage of this framework is applying fuzzy rules to calculate trust values. Two main components of the proposed framework are simulated in this paper. The simulation results confirm the important role of applied components. Also, this paper proposed a framework compared with other frameworks (feedback-based model, SLA-based model, and multicloud model). Simulation results show the proposed framework increased trust values rather than other models. Also, compared with other models, our framework gives better mean trust values.
The interaction between cores and memory blocks, in multiprocessor chips and smart systems, has always been a concern as it affects network latency, memory capacity, and power consumption. A new 2.5-dimensional architecture has been introduced in which the communication between the processing elements and the memory blocks is provided through a layer called the interposer. If the core wants to connect to another, it uses the top layer, and if it wants to interact with the memory blocks, it uses the interposer layer. In a case that coherence traffic at the processing layer increases to the extent that congestion occurs, a part of this traffic may be transferred to the interposer network under a mechanism called load balancing. When coherence traffic is moved to the interposer layer, as an alternative way, this may interfere with memory traffic. This paper introduces a mechanism in which the aforementioned interference may be avoided by defining two different virtual channels and using multiple links which specifically determines which memory block is going to be accessed. Our method is based on the destination address to recognize which channel and link should be selected while using the interposer layer. The simulation results show that the proposed mechanism has improved by 32% and 14% latency compared to the traditional load-balancing and unbalanced mechanisms, respectively.
The routing process in vehicular ad hoc networks (VANETs) is a challenging task in urban areas which is due to the high mobility of vehicles, repetitive defects of the communication path, and the various barriers that may affect the reliability of data transmission and routing. Accordingly, the connectivity in vehicular communications has received the researchers’ attention, so different geographic routing protocols have been proposed in this respect. Unmanned aerial vehicles (UAVs) are useful for overcoming routing constraints. Cloud computing has also been defined as a new infrastructure for VANET which is made up of a significant number of computing nodes including stable data centers as well as a set of mobile computing devices embedded on vehicles. The aim of this research is to simulate a VANET in an urban area using cloud computing infrastructure and applying unmanned aerial vehicles (UAV) so that the negative influence of barriers in packet delivery and routing is avoided. To evaluate, the proposed method is compared with the basic protocol ClouDiV. Ns-2 simulation results show that the proposed method outperforms with different densities and variable times in terms of efficiency and performance.
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