Time-interleaved pipelined ADC design for computational intelligence and cloud computing application

This paper presents a four-channel time-interleaved 3GSps 12-bit pipelined analog-to-digital converter (ADC). The combination of master clock sampling and delay-adjusting is adopted to remove the time skew due to channel mismatches. An early comparison scheme is used to minimize the non-overlapping time, where a custom-designed latch is developed to replace the typical non-overlapping clock generator. By using the dither capacitor to generate an equivalent direct current input, a zero-input-based calibration is developed to correct the capacitor mismatch and inter-stage gain error. Fabricated in a 40 nm CMOS process, the ADC achieves a signal-to-noise-and-distortion ratio (SNDR) of 57.8 dB and a spurious free dynamic range (SFDR) of 72 dB with a 23 MHz input tone. It can achieve an SNDR above 52.3 dB and an SFDR above 61.5 dB across the entire first Nyquist zone. The differential and integral nonlinearities are −0.93/+0.73 least significant bit (LSB) and −2.8/+4.3 LSB, respectively. The ADC consumes 450 mW powered at 1.8V, occupies an active area of 3 mm × 1.3 mm. The calculated Walden figure of merit reaches 0.44 pJ/step.

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Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues

Journal of Information Security and Applications ◽

10.1016/j.jisa.2020.102582 ◽

2020 ◽

Vol 55 ◽

pp. 102582 ◽

Cited By ~ 2

Author(s):

Shahab Shamshirband ◽

Mahdis Fathi ◽

Anthony T. Chronopoulos ◽

Antonio Montieri ◽

Fabio Palumbo ◽

...

Keyword(s):

Cloud Computing ◽

Intrusion Detection ◽

Computational Intelligence ◽

Mobile Cloud Computing ◽

Mobile Cloud ◽

Research Issues ◽

Detection Techniques ◽

Open Research ◽

Computing Environments

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An Ant-Colony-Based Meta-Heuristic Approach for Load Balancing in Cloud Computing

Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing ◽

10.4018/978-1-7998-5339-8.ch041 ◽

2021 ◽

pp. 873-903

Author(s):

Santanu Dam ◽

Gopa Mandal ◽

Kousik Dasgupta ◽

Parmartha Dutta

Keyword(s):

Cloud Computing ◽

Load Balancing ◽

Computational Intelligence ◽

Optimal Solution ◽

Ant Colony ◽

Multi Agent Systems ◽

Distributed Environment ◽

Intelligent Behavior ◽

Computational Intelligence Technique ◽

Multi Agent

This book chapter proposes use of Ant Colony Optimization (ACO), a novel computational intelligence technique for balancing loads of virtual machine in cloud computing. Computational intelligence(CI), includes study of designing bio-inspired artificial agents for finding out probable optimal solution. So the central goal of CI can be said as, basic understanding of the principal, which helps to mimic intelligent behavior from the nature for artifact systems. Basic strands of ACO is to design an intelligent multi-agent systems imputed by the collective behavior of ants. From the perspective of operation research, it's a meta-heuristic. Cloud computing is a one of the emerging technology. It's enables applications to run on virtualized resources over the distributed environment. Despite these still some problems need to be take care, which includes load balancing. The proposed algorithm tries to balance loads and optimize the response time by distributing dynamic workload in to the entire system evenly.

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