Transform recipes for efficient cloud photo enhancement

Cloud image processing is often proposed as a solution to the limited computing power and battery life of mobile devices: it allows complex algorithms to run on powerful servers with virtually unlimited energy supply. Unfortunately, this overlooks the time and energy cost of uploading the input and downloading the output images. When transfer overhead is accounted for, processing images on a remote server becomes less attractive and many applications do not benefit from cloud offloading. We aim to change this in the case of image enhancements that preserve the overall content of an image. Our key insight is that, in this case, the server can compute and transmit a description of the transformation from input to output, which we call a transform recipe. At equivalent quality, our recipes are much more compact than JPEG images: this reduces the client's download. Furthermore, recipes can be computed from highly compressed inputs which significantly reduces the data uploaded to the server. The client reconstructs a high-fidelity approximation of the output by applying the recipe to its local high-quality input. We demonstrate our results on 168 images and 10 image processing applications, showing that our recipes form a compact representation for a diverse set of image filters. With an equivalent transmission budget, they provide higher-quality results than JPEG-compressed input/output images, with a gain of the order of 10 dB in many cases. We demonstrate the utility of recipes on a mobile phone by profiling the energy consumption and latency for both local and cloud computation: a transform recipe-based pipeline runs 2--4x faster and uses 2--7x less energy than local or naive cloud computation.Qatar Computing Research InstituteUnited States. Defense Advanced Research Projects Agency (Agreement FA8750-14-2-0009)Stanford University. Stanford Pervasive Parallelism LaboratoryAdobe System

Performance comparison of power saving strategies for mobile Web access

One of the critical issues in mobile Web access is the usage of limited energy resources of mobile computers. Unfortunately, the legacy TCP/IP architecture is very inefficient. This work proposes and analyzes power-saving strategies for mobile Web access. Specifically, in this paper we develop an energy-consumption model for Web transactions and, based on it, we propose and compare four different energy saving strategies: ideal, Indirect-TCP (I-TCP), local and global. The ideal strategy is unfeasible but it is used as a reference bound as it guarantees the lowest energy consumption. The other strategies have been implemented and compared in a real test-bed. The performance comparison is carried out by measuring two main performance figures: the energy spent for downloading a Web page, and the associated transfer-time. Experimental results show that relevant energy saving is achievable and that, among the feasible strategies, the global one gives the best performance: with this strategy we can save (on average) up to 88% of the energy. Furthermore, our results indicate that this power saving is obtained without a significant increase in the transfer-time perceived by the users (on average, 0.2s). Finally, by comparing the feasible strategies, we observe that the global one is much closer to the ideal case than the other strategies. In detail, the global strategy is about twice more efficient than the local one, and eight times more efficient than the I-TCP strategy

Local Networks to Compete in the Global Era. The Italian SMEs Experience

This study is concerned with the factors that influence the cooperation among cluster-based firms. Theorists have consistently demonstrated the role and importance of economic externalities, such as knowledge spillovers, within industrial clusters. Less attention has been paid to the investigation of social based externalities, though it has been suggested that these may also accrue from geographical agglomeration. This study explores the development of cooperation between firms operating in a single industry sector and in close proximity. The results suggest that social networking has a greater influence than geographic proximity in facilitating inter-firm co-operation. A semi-structured questionnaire has been developed and the answers were analysed with a stepwise regression model.Networks, Inter-Firm Cooperation, SMEs

Genomic co-processor for long read assembly

Genomics data is transforming medicine and our understanding of life in fundamental ways; however, it is far outpacing Moore's Law. Third-generation sequencing technologies produce 100X longer reads than second generation technologies and reveal a much broader mutation spectrum of disease and evolution. However, these technologies incur prohibitively high computational costs. In order to enable the vast potential of exponentially growing genomics data, domain specific acceleration provides one of the few remaining approaches to continue to scale compute performance and efficiency, since general-purpose architectures are struggling to handle the huge amount of data needed for genome alignment. The aim of this project is to implement a genomic-coprocessor targeting HPC FPGAs starting from the Darwin FPGA co-processor. In this scenario, the final objective is the simulation and implementation of the algorithms described by Darwin using Alveo boards, exploiting High Bandwidth Memory (HBM) to increase its performance

Proof of User Similarity: the Spatial Measurer of Blockchain

Although proof of work (PoW) consensus dominates the current blockchain-based systems mostly, it has always been criticized for the uneconomic brute-force calculation. As alternatives, energy-conservation and energy-recycling mechanisms heaved in sight. In this paper, we propose proof of user similarity (PoUS), a distinct energy-recycling consensus mechanism, harnessing the valuable computing power to calculate the similarities of users, and enact the calculation results into the packing rule. However, the expensive calculation required in PoUS challenges miners in participating, and may induce plagiarism and lying risks. To resolve these issues, PoUS embraces the best-effort schema by allowing miners to compute partially. Besides, a voting mechanism based on the two-parties computation and Bayesian truth serum is proposed to guarantee privacy-preserved voting and truthful reports. Noticeably, PoUS distinguishes itself in recycling the computing power back to blockchain since it turns the resource wastage to facilitate refined cohort analysis of users, serving as the spatial measurer and enabling a searchable blockchain. We build a prototype of PoUS and compare its performance with PoW. The results show that PoUS outperforms PoW in achieving an average TPS improvement of 24.01% and an average confirmation latency reduction of 43.64%. Besides, PoUS functions well in mirroring the spatial information of users, with negligible computation time and communication cost.Comment: 12 pages,10 figure

Power-management policies for mobile computing

Abbiamo studiato architetture di rete per il power-saving in ambito di wireless LAN infrastrutturate. Abbiamo proposto protocolli power-saving di livello middleware, indipendenti dalla tecnologia wireless impiegata. Tali protocolli sono stati valutati approfonditamente, risultando molto efficienti. Abbiamo poi valutato in maniera estensiva il meccanismo di power-saving dello standard 802.11. Ne abbiamo evidenziato i limiti, ed abbiamo definito un framework cross-layer di power-management. Tale framewok integra i protocolli middleware studiati inizialmente e lo standard 802.11. L'incremento delle prestazioni ottenute rispetto allo standard 802.11 arriva al 90% in termini di power saving

Toward a process theory of entrepreneurship: revisiting opportunity identification and entrepreneurial actions

This dissertation studies the early development of new ventures and small business and the entrepreneurship process from initial ideas to viable ventures. I unpack the micro-foundations of entrepreneurial actions and new ventures’ investor communications through quality signals to finance their growth path. This dissertation includes two qualitative papers and one quantitative study. The qualitative papers employ an inductive multiple-case approach and include seven medical equipment manufacturers (new ventures) in a nascent market context (the mobile health industry) across six U.S. states and a secondary data analysis to understand the emergence of opportunities and the early development of new ventures. The quantitative research chapter includes 770 IPOs in the manufacturing industries in the U.S. and investigates the legitimation strategies of young ventures to gain resources from targeted resource-holders.Open Acces