Platform choices and design demands for IoT platforms: cost, power, and performance tradeoffs

Abstract

The rise of the Internet of Things has led to an explosion of new sensor computing platforms. The complexity and application domains of IoT devices range from simple self-monitoring devices in vending machines to complex interactive devices with artificial intelligence in smart vehicles and drones. As IoT developers wish to meet more aggressive platform objectives and protect market share through feature differentiation, they must choose between low-cost, and lowperformance CPU-based commercial-off-the-shelf (COTS) systems, and high-performance custom platforms with hardware accelerators such as GPU and FPGA. Both COTS and custom platform designs introduce a variety of design challenges-the extreme pressures on time-to-market, design cost, and development risk are also driving a voracious demand for new CAD technologies to enable rapid, low cost design of effective IoT platforms with smaller design teams and lower risk. In this article, we present a generic IoT device design flow and discuss platform choices available for IoT devices to efficiently tradeoff cost, power, performance and volume constraints: CPUbased systems, and custom platforms that contain hardware accelerators such as FPGA and embedded GPUs. We demonstrate this design process through a driving application in computer vision. We also present current critical design automation needs for IoT development and demonstrate how our prior work in CAD for FPGAs and SoCs begin to address these needs.

Performance evaluation of IOT systems – basic issues

“…A design flow is presented that trades off cost, power, performance, and volume of transactions handled. The designing of computer vison related to application has been presented using the design flow [10]. Many network topologies are in use for constructing IOT based networks.…”

A Compression Algorithm Design and Simulation for Processing Large Volumes of Data from Wireless Sensor Networks

“…Similarly, paper [12] presents a way to design/customize a reconfigurable hardware to the target application domain and make the SoC custom-fabricated. While [13] presents the generic IoT device design flow and various platform choices for IoT devices to efficiently tradeoff cost, power, performance and volume constraints.…”

Performance Analysis of Multihop Relaying Caching for Internet of Things under Nakagami Channels

“…Three deployment patterns of the industrial IoT are theoretically discussed by the authors from [7] for the cognitive access in IoT. The cost and the performance tradeoff are demonstrated in [8][9][10] for selecting the platform in IoT, where the CUP, GPU, and FPGA are taken into the consideration for the computer vision. In [11], the smart manufacturing with real-time traceability is studied in [11] which is enabled by IoT, where the authors propose a production performance analysis and exception diagnosis model.…”

“…Compared to traditional networks, MCRSs have a lot of advantages such as the connectivity improvement and the capacity enhancement. In multihop wireless communications, many relay stations assist the source terminal to transmit signal to 2 Wireless Communications and Mobile Computing the destination terminal, which reduces the transmit power and improves the wireless link reliability especially for the scenario of the long-distance between the source and the destination [6][7][8][9][10][11][12][13]. The amplify-and-forward relaying protocol is studied in [13] for the multihop and multibranch wireless cooperative systems with nonregenerative fixed gain at the relay station.…”