Current Issue : April - June Volume : 2018 Issue Number : 2 Articles : 5 Articles
Many artificial intelligence applications often require a huge amount of computing\nresources. As a result, cloud computing adoption rates are increasing in the artificial intelligence\nfield. To support the demand for artificial intelligence applications and guarantee the service level\nagreement, cloud computing should provide not only computing resources but also fundamental\nmechanisms for efficient computing. In this regard, a snapshot protocol has been used to create a\nconsistent snapshot of the global state in cloud computing environments. However, the existing\nsnapshot protocols are not optimized in the context of artificial intelligence applications, where\nlarge-scale iterative computation is the norm. In this paper, we present a distributed snapshot protocol\nfor efficient artificial intelligence computation in cloud computing environments. The proposed\nsnapshot protocol is based on a distributed algorithm to run interconnected multiple nodes in a\nscalable fashion. Our snapshot protocol is able to deal with artificial intelligence applications, in which\na large number of computing nodes are running. We reveal that our distributed snapshot protocol\nguarantees the correctness, safety, and liveness conditions....
Because wireless sensor networks (WSNs) are complex and difficult to deploy and manage, appropriate structures are required to\nmake these networks more flexible. In this paper, a reconfigurable testbed is presented, which supports dynamic protocol switching\nby creating a novel architecture and experiments with several different protocols. The separation of the control and data planes\nin this testbed means that routing configuration and data transmission are independent. A programmable flow table provides the\ntestbed with the ability to switch protocols dynamically.We experiment on various aspects of the testbed to analyze its functionality\nand performance. The results demonstrate that sensors in the testbed are easy to manage and can support multiple protocols. We\nthen raise some important issues that should be investigated in future work concerning the testbed....
Typical radio frequency (RF) digital beamformers can be highly complex. In addition to a suitable antenna array, they require\nnumerous receiver chains, demodulators, data converter arrays, and digital signal processors. To recover and reconstruct the\nreceived signal, synchronization is required since the analog-to-digital converters (ADCs), digital-to-analog converters (DACs),\nfield programmable gate arrays (FPGAs), and local oscillators are all clocked at different frequencies. In this article, we present a\nclock synchronization topology for a multichannel on-site coding receiver (OSCR) using the FPGA as a master clock to drive all\nRF blocks.This approach reduces synchronization errors by a factor of 8, when compared to conventional digital beamformer....
In view of the real-time and distributed features of Internet of Things (IoT) safety system in water conservancy engineering,\nthis study proposed a new safety system architecture for water conservancy engineering based on cloud/fog computing and\nput forward a method of data reliability detection for the false alarm caused by false abnormal data from the bottom sensors.\nDesigned for the South-North Water Transfer Project (SNWTP), the architecture integrated project safety, water quality safety,\nand human safety. Using IoT devices, fog computing layer was constructed between cloud server and safety detection devices in\nwater conservancy projects. Technologies such as real-time sensing, intelligent processing, and information interconnection were\ndeveloped. Therefore, accurate forecasting, accurate positioning, and efficientmanagement were implemented as required by safety\nprevention of the SNWTP, and safety protection of water conservancy projects was effectively improved, and intelligential water\nconservancy engineering was developed....
Outsourcing computation with verifiability is amerging notion in cloud computing, which enables lightweight clients to outsource\ncostly computation tasks to the cloud and efficiently check the correctness of the result in the end. This advanced notion is more\nimportant in marine mobile computing since the oceangoing vessels are usually constrained with less storage and computation\nresources. In such a scenario, vessels always firstly outsource data set and perform a function computing over them or at first\noutsource computing functions and input data set into them. However, vessels may choose which delegation computation type to\noutsource, which generally depends on the actual circumstances. Hence, we propose a scalable verifiable outsourcing computation\nprotocol (SV-OC) inmarine cloud computing at first and extract a single-mode versionof it (SM-SV-OC),where both protocols\nallow anyone who holds verification tokens to efficiently verify the computed result returned fromcloud. In this way, the introduced\nââ?¬Å?scalableââ?¬Â property lets vessels adjust the protocol to cope with different delegation situations in practice. We additionally prove\nbothSV-OC andSM-SV-OC achieving selective soundness in the random oracle model and evaluate their performance in the\nend....
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