Performance evaluation of IOT systems – basic issues

Sowmya, K. V.; Sastry, J. K. R.

doi:10.14419/ijet.v7i2.7.10279

Cited by 14 publications

(4 citation statements)

References 22 publications

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“…At positive edge of Clk Q1=D and at negative edge of the Clk Q 2 =D. This paper obviously clarifies the effectiveness of 14T, 12T and 16T flip-flops at higher order bits (5,10,15,20,32, 64-bits) in terms of area delay and power dissipation.…”

Section: Introductionsupporting

confidence: 53%

“…AI (Artificial intelligence) and ML (Machine Learning) have their unique way in interacting with the things surrounding us. Our voice is the Speech processed and given as input voice command for few devices [6][7][8][9].Few electronic gadgets takes humans face as input to interact in a more intuitive manner [9][10][11][12][13]. As more and more devices with extending machine intelligence are connected over "Internet-of-Things" (IoT), "edge-computing" i.e.…”

Section: Introductionmentioning

confidence: 99%

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High Speed High Capacity Memories for Secured Internet of Things based systems

2020

IJATCSE

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The Internet of Things (IoT) is a network connecting objects ranging from remote sensors to smart devices and tablets. To support high speed and high caacity networking speed the database management system (DBMS). To meet the requirements of DBMS of IoT smart micro devices are in high demand to store and access the data. Dual Edge Triggering (DET) flip-flops stand out to be a unique solution overcoming the trade-offs between speed and power. This paper presents a 64-bit register to control the flow of data to enhance the communication between devices connected over IoT. Though the concept of DET is subsisting, the design of area power and delay flipflops efficient is still under design process. In this paper two new D-type flip-flops with Dual Edge Triggering are proposed. One among the two consists of 14 Transistors (14T) and the other consists of 12 Transistors (12T). The two designs are compared with existing 16 Transistor (16T) DET Flip-Flop. 14T DETFF (Dual Edge Triggered Flip-Flop) is found to be efficient in terms of area power and delay parameters. 12T DETFF shows really amazing and efficient results than 14T. Results are derived by simulating the circuits at 45nm technology at 1.2V supply voltage. It is observed that propagation delay of 14T is reduced by 45.39% when compared with 16T, for 12T it is reduced by 60.52% with respect to 16T. For 14T decrease in area is observed to be 18.42%, and 12T 36.16% of area is reduced when compared with 16T. Examinations of Dynamic Power scattering is finished with various capacitive loads, at various frequencies for multi bit registers extended up to 64-bits.

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Section: Introductionsupporting

confidence: 53%

Section: Introductionmentioning

confidence: 99%

High Speed High Capacity Memories for Secured Internet of Things based systems

2020

IJATCSE

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“…Docker containers performances were also studied by MORABITO [18] by using bench-mark tools, when running on a single board computer device such as Raspberry Pi 2. Also, main network performance issues in an IoT system are presented by Sowmya et al [8].…”

Section: Related Workmentioning

confidence: 99%

Towards Self-Optimization of Publish/Subscribe IoT Systems using Continuous Performance Monitoring

Mohammed,

Nabila

2024

Networks, Blockchain and Internet of Things

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Today, more and more embedded devices are being connected through a network, generally Internet, offering users different services. This concept refers to Internet of Things (IoT), bringing information and control capabilities in many fields like medicine, smart homes, home security, etc. Main drawbacks of IoTenvironment are its dependency on Internet connectivity and need continuous devices power. These dependencies may affect system performances, namely request processing response times. In this context,we propose in this paper a continuous performance monitoring methodology, applied on IoT systems based on Publish/subscribe communication model. Our approach assesses performances using Stochastic Petri net modeling, and self-optimizes whenever poor performances are detected. Our approach relies on a Stochastic Petri nets modelling and analysis to assess performances. We target improving performances, in particular response times, by online modification of influencing factors.

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“…Sowmya, K.V., and Sastry, J.K.R. [6] have presented several issues that should be considered to improve IoT networks' performance.…”

Section: Literature Surveymentioning

confidence: 99%

Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

Sowmya,

Sastry

2022

Scientia Iranica

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Multiple networking layers existing in the IoT network involve heterogeneity that must be addressed to facilitate proper communication such that the performance of an IoT network does not suffer. The performance of the IoT networks depends on networking topologies used in different layers, clustering algorithms, protocols used for handling heterogeneity, communication speeds, and data packet sizes. In this Research, the performance of IoT networks is improved by adding device clustering via a multi-Stage network and using an efficient SOJK clustering algorithm in the device layer, which minimizes power depletion and increases the quantity of data and data packets; transmitted at zero power. A mechanism to handle heterogeneity due to Wi-Fi, CDMA, and USB communication protocols is also presented while optimizing the communication speeds and data transmission size. It has also been shown that the use of 170Mbps cellular speed and the data size of 468 bytes give the optimum response time of an IoT network. The time taken to transport information from the device to the storage layer is reduced by 57% compared to the time taken to transport the data using the prototype network.

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Performance evaluation of IOT systems – basic issues

Cited by 14 publications

References 22 publications

High Speed High Capacity Memories for Secured Internet of Things based systems

High Speed High Capacity Memories for Secured Internet of Things based systems

Towards Self-Optimization of Publish/Subscribe IoT Systems using Continuous Performance Monitoring

Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

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