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Full-Text Articles in Physical Sciences and Mathematics
Verification Assisted Gas Reduction For Smart Contracts, Bo Gao, Siyuan Shen, Ling Shi, Jiaying Li, Jun Sun, Lei Bu
Verification Assisted Gas Reduction For Smart Contracts, Bo Gao, Siyuan Shen, Ling Shi, Jiaying Li, Jun Sun, Lei Bu
Research Collection School Of Computing and Information Systems
Smart contracts are computerized transaction protocols built on top of blockchain networks. Users are charged with fees, a.k.a. gas in Ethereum, when they create, deploy or execute smart contracts. Since smart contracts may contain vulnerabilities which may result in huge financial loss, developers and smart contract compilers often insert codes for security checks. The trouble is that those codes consume gas every time they are executed. Many of the inserted codes are however redundant. In this work, we present sOptimize, a tool that optimizes smart contract gas consumption automatically without compromising functionality or security. sOptimize works on smart contract bytecode, …
Adadeep: A Usage-Driven, Automated Deep Model Compression Framework For Enabling Ubiquitous Intelligent Mobiles, Sicong Liu, Junzhao Du, Kaiming Nan, Zimu Zhou, Hui Liu, Zhangyang Wang, Yingyan Lin
Adadeep: A Usage-Driven, Automated Deep Model Compression Framework For Enabling Ubiquitous Intelligent Mobiles, Sicong Liu, Junzhao Du, Kaiming Nan, Zimu Zhou, Hui Liu, Zhangyang Wang, Yingyan Lin
Research Collection School Of Computing and Information Systems
Recent breakthroughs in deep neural networks (DNNs) have fueled a tremendously growing demand for bringing DNN-powered intelligence into mobile platforms. While the potential of deploying DNNs on resource-constrained platforms has been demonstrated by DNN compression techniques, the current practice suffers from two limitations: 1) merely stand-alone compression schemes are investigated even though each compression technique only suit for certain types of DNN layers; and 2) mostly compression techniques are optimized for DNNs’ inference accuracy, without explicitly considering other application-driven system performance (e.g., latency and energy cost) and the varying resource availability across platforms (e.g., storage and processing capability). To this …
Utility-Based Adaptation In Mission-Oriented Wireless Sensor Networks, Sharanya Eswaran, Archan Misra, Thomas La Porta
Utility-Based Adaptation In Mission-Oriented Wireless Sensor Networks, Sharanya Eswaran, Archan Misra, Thomas La Porta
Research Collection School Of Computing and Information Systems
This paper extends the distributed network utility maximization (NUM) framework to consider the case of resource sharing by multiple competing missions in a military-centric wireless sensor network (WSN) environment. Prior work on NUM-based optimization has considered unicast flows with sender-based utilities in either wireline or wireless networks. We extend the NUM framework to consider three key new features observed in mission-centric WSN environments: i) the definition of an individual mission's utility as a joint function of data from multiple sensor sources ii) the consumption of each senders (sensor) data by multiple receivers (missions) and iii) the multicast-tree based dissemination of …
An Efficient And Robust Computational Framework For Studying Lifetime And Information Capacity In Sensor Networks, Enrique J. Duarte-Melo, Mingyan Liu, Archan Misra
An Efficient And Robust Computational Framework For Studying Lifetime And Information Capacity In Sensor Networks, Enrique J. Duarte-Melo, Mingyan Liu, Archan Misra
Research Collection School Of Computing and Information Systems
In this paper we investigate the expected lifetime and information capacity, defined as the maximum amount of data (bits) transferred before the first sensor node death due to energy depletion, of a data-gathering wireless sensor network. We develop a fluid-flow based computational framework that extends the existing approach, which requires precise knowledge of the layout/deployment of the network, i.e., exact sensor positions. Our method, on the other hand, views a specific network deployment as a particular instance (sample path) from an underlying distribution of sensor node layouts and sensor data rates. To compute the expected information capacity under this distribution-based …
A Modeling Framework For Computing Lifetime And Information Capacity In Wireless Sensor Networks, Enrique Duarte-Melo, Mingyan Liu, Archan Misra
A Modeling Framework For Computing Lifetime And Information Capacity In Wireless Sensor Networks, Enrique Duarte-Melo, Mingyan Liu, Archan Misra
Research Collection School Of Computing and Information Systems
In this paper we investigate the expected lifetime and information capacity, defined as the maximum amount of data (bits) transferred before the first sensor node death due to energy depletion, of a data-gathering wireless sensor network. We develop a fluidflow based computational framework that extends the existing approach, which requires precise knowledge of the layout/deployment of the network, i.e., exact sensor positions. Our method, on the other hand, views a specific network deployment as a particular instance (sample path) from an underlying distribution of sensor node layouts and sensor data rates.