Hyukjoong Kim, Daedong Park, Uze Choi, Sungjin Shin, Minsoo Kim, Kyung-hoon Lee
{"title":"Multi-Device Framework with Spatial Clustering (industry track)","authors":"Hyukjoong Kim, Daedong Park, Uze Choi, Sungjin Shin, Minsoo Kim, Kyung-hoon Lee","doi":"10.1145/3366626.3368127","DOIUrl":"https://doi.org/10.1145/3366626.3368127","url":null,"abstract":"As the number of smart appliances increases, there is a possibility for novel user experiences that involve interaction with multiple devices, which we call multi-device experiences (MDE). In realizing MDE scenarios, one of the key features is the spatial context. However, there is no application framework that provides the spatial context and an easy-to-use application programming interface (API) for home appliances. In this paper, we present an application framework named Multi-Device Framework (MDF) that provides a programming interface, designed for exploiting the spatial context of multiple home appliances. We present the technical requirements and explain the implementation of three key components of the framework. To demonstrate the usability of our framework, we provide two exemplary applications developed using our API.","PeriodicalId":120474,"journal":{"name":"Proceedings of the 20th International Middleware Conference Industrial Track","volume":"108 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126088269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ahsan Ali, Riccardo Pinciroli, Feng Yan, E. Smirni
{"title":"It's not a Sprint, it's a Marathon: Stretching Multi-resource Burstable Performance in Public Clouds (industry track)","authors":"Ahsan Ali, Riccardo Pinciroli, Feng Yan, E. Smirni","doi":"10.1145/3366626.3368130","DOIUrl":"https://doi.org/10.1145/3366626.3368130","url":null,"abstract":"During the past few years, all leading cloud providers introduced burstable instances that can sprint their performance for a limited period to address sudden workload variations. Despite the availability of burstable instances, there is no clear understanding of how to minimize the waste of resources by regulating their burst capacity to the workload requirements. This is especially true when it comes to non-CPU-intensive applications. In this paper, we investigate how to limit network and I/O usage to optimize the efficiency of the bursting process. We also study which resource shall be controlled to benefit both cloud providers and end-users. We design MRburst (Multi-Resource burstable performance scheduler) to automatically limit multiple resources (i.e., network, I/O, and CPU) and make the application comply with a user-defined service level objective (SLO) while minimizing wasted resources. MRburst is evaluated on Amazon EC2 using two multi-resource applications: an FTP server and a Ceph system. Experimental results show that MRburst outperforms state-of-the-art approaches by allowing instances to speed up their performance for up to 2.4 times longer period while meeting SLO.","PeriodicalId":120474,"journal":{"name":"Proceedings of the 20th International Middleware Conference Industrial Track","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131962424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Profiling Dynamic Data Access Patterns with Controlled Overhead and Quality","authors":"Seongjae Park, Yunjae Lee, H. Yeom","doi":"10.1145/3366626.3368125","DOIUrl":"https://doi.org/10.1145/3366626.3368125","url":null,"abstract":"Modern workloads tend to have huge working sets and low locality. Despite this trend, the capacity of DRAM has not been increased enough to accommodate such huge working sets. Therefore, memory management mechanisms optimized for such modern workloads are widely required today. For such optimizations, knowing the data access pattern of given workloads is essential. However, manually extracting such patterns from huge and complex workloads is exhaustive. Worse yet, existing memory access analysis tools incur unacceptably high overheads for unnecessarily detailed analysis results. To mitigate this situation, we introduce a tool that is designed for data access pattern tracing. Two core mechanisms in this tool, a region-based sampling and an adaptive region adjustment, allow users to limit the tracing overhead in a bounded range regardless of the size and complexity of target workloads, while preserving the quality of results. Our empirical evaluations that conducted with 20 realistic workloads show the high quality, low overhead, and a potential use case of this tool.","PeriodicalId":120474,"journal":{"name":"Proceedings of the 20th International Middleware Conference Industrial Track","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125982775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Salehe, Zhiming Hu, S. H. Mortazavi, Iqbal Mohomed, Tim Capes
{"title":"VideoPipe","authors":"Mohammad Salehe, Zhiming Hu, S. H. Mortazavi, Iqbal Mohomed, Tim Capes","doi":"10.1145/3366626.3368131","DOIUrl":"https://doi.org/10.1145/3366626.3368131","url":null,"abstract":"Real-time video processing in the home, with the benefits of low latency and strong privacy guarantees, enables virtual reality (VR) applications, augmented reality (AR) applications and other next-gen interactive applications. However, processing video feeds with computationally expensive machine learning algorithms may be impractical on a single device due to resource limitations. Fortunately, there are ubiquitous underutilized heterogeneous edge devices in the home. In this paper, we propose VideoPipe, a system that bridges the gap and runs flexible video processing pipelines on multiple devices. Towards this end, with inspirations from Function-as-a-Service (FaaS) architecture, we have unified the runtime environments of the edge devices. We do this by introducing modules, which are the basic units of a video processing pipeline and can be executed on any device. With the uniform design of input and output interfaces, we can easily connect any of the edge devices to form a video processing pipeline. Moreover, as some devices support containers, we further design and implement stateless services for more computationally expensive tasks such as object detection, pose detection and image classification. As they are stateless, they can be shared across pipelines and can be scaled easily if necessary. To evaluate the performance of our system, we design and implement a fitness application on three devices connected through Wi-Fi. We also implement a gesture-based Internet of Things (IoT) control application. Experimental results show the the promises of VideoPipe for efficient video analytics on the edge.","PeriodicalId":120474,"journal":{"name":"Proceedings of the 20th International Middleware Conference Industrial Track","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123946392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Building Own Blockchain","authors":"Anil Mujagić, M. Gheorghe, Ermin Džinić","doi":"10.1145/3366626.3368126","DOIUrl":"https://doi.org/10.1145/3366626.3368126","url":null,"abstract":"Own is a decentralized fundraising, digital trading and security token issuance platform that runs on a native, custom-built dual-blockchain infrastructure. This paper describes the implementation and our experiences with the public, permissionless part of Own dual blockchain. We describe Own public blockchain consensus, which is based on the Tendermint BFT consensus algorithm, and which we modified towards simplicity and robustness, and open-source implemented from scratch in F#. We further detail how Own Delegated Proof of Stake (DPoS) mechanism works and the staking cryptoeconomics around its native utility token (CHX). Finally, we report on Own public blockchain performance both in experimental (testnet) deployments and extracting performance numbers from history of the live blockchain network (mainnet), which consisted of 83 active validators in August 2019.","PeriodicalId":120474,"journal":{"name":"Proceedings of the 20th International Middleware Conference Industrial Track","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122506842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emad Heydari Beni, B. Lagaisse, W. Joosen, A. Aly, Michael Brackx
{"title":"DataBlinder","authors":"Emad Heydari Beni, B. Lagaisse, W. Joosen, A. Aly, Michael Brackx","doi":"10.1145/3366626.3368132","DOIUrl":"https://doi.org/10.1145/3366626.3368132","url":null,"abstract":"Business application owners want to outsource data storage, including sensitive data, to the public cloud for economical reasons. This is often challenging since these businesses are and remain responsible for regulatory compliance and data protection, even though cloud providers may do their best to offer (data) protection. Meanwhile, data protection techniques evolve and get better because of continuous research and improvement of advanced encryption. Numerous cryptographic tactics have been proposed, e.g., searchable symmetric encryption (SSE) and homomorphic encryption (HE), that support search and aggregation functions on encrypted data. Each of these tactics has a trade-off between security, performance and functionality, but there is no one-size-fits-all solution. For the application developer, the underpinning concepts of these tactics are complex to comprehend, complex to integrate in a distributed application, and prone to implementation mistakes. In this paper we present DataBlinder, a distributed data access middleware that provides crypto agility by means of configurable fine-grained data protection at the application level. DataBlinder supports adaptive runtime selection of data protection tactics, and offers a plugin architecture for such tactics based on a key abstraction model for protection level, performance and supported query functionality. We have developed this middleware in close collaboration with businesses that face these challenges and offer cloud-based applications in e-finance, and e-health, by implementing and integrating state-of-the-art cryptographic schemes to DataBlinder. This paper illustrates the case of medical data protection with FHIR-compliant [30] medical data.","PeriodicalId":120474,"journal":{"name":"Proceedings of the 20th International Middleware Conference Industrial Track","volume":"50 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123189457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Designing for Privacy and Confidentiality on Distributed Ledgers for Enterprise (Industry Track)","authors":"Allison Irvin, Isabell Kiral","doi":"10.1145/3366626.3368128","DOIUrl":"https://doi.org/10.1145/3366626.3368128","url":null,"abstract":"Distributed ledger technology offers numerous desirable attributes to applications in the enterprise context. However, with distributed data and decentralized computation on a shared platform, privacy and confidentiality challenges arise. Any design for an enterprise system needs to carefully cater for use case specific privacy and confidentiality needs. With the goal to facilitate the design of enterprise solutions, this paper aims to provide a guide to navigate and aid in decisions around common requirements and mechanisms that prevent the leakage of private and confidential information. To further contextualize key concepts, the design guide is then applied to three enterprise DLT protocols: Hyperledger Fabric, Corda, and Quorum.","PeriodicalId":120474,"journal":{"name":"Proceedings of the 20th International Middleware Conference Industrial Track","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121720225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Abebe, Dushyant Behl, Chander Govindarajan, Yining Hu, Dileban Karunamoorthy, P. Novotný, Vinayaka Pandit, V. Ramakrishna, C. Vecchiola
{"title":"Enabling Enterprise Blockchain Interoperability with Trusted Data Transfer (Industry Track)","authors":"E. Abebe, Dushyant Behl, Chander Govindarajan, Yining Hu, Dileban Karunamoorthy, P. Novotný, Vinayaka Pandit, V. Ramakrishna, C. Vecchiola","doi":"10.1145/3366626.3368129","DOIUrl":"https://doi.org/10.1145/3366626.3368129","url":null,"abstract":"The adoption of permissioned blockchain networks in enterprise settings has seen an increase in growth over the past few years. While encouraging, this is leading to the emergence of new data, asset and process silos limiting the potential value these networks bring to the broader ecosystem. Mechanisms for enabling network interoperability help preserve the benefits of independent sovereign networks, while allowing for the transfer or sharing of data, assets and processes across network boundaries. However, a naive approach to interoperability based on traditional point-to-point integration is insufficient for preserving the underlying trust decentralized networks provide. In this paper, we lay the foundation for an approach to interoperability based on a communication protocol that derives trust from the underlying network consensus protocol. We present an architecture and a set of building blocks that can be adapted for use in a range of network implementations and demonstrate a proof-of-concept for trusted data-sharing between two independent trade finance and supply-chain networks, each running on Hyperledger Fabric. We show how existing blockchain deployments can be adapted for interoperation and discuss the security and extensibility of our architecture and mechanisms.","PeriodicalId":120474,"journal":{"name":"Proceedings of the 20th International Middleware Conference Industrial Track","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124990688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the 20th International Middleware Conference Industrial Track","authors":"Lucy Cherkasova, R. Rastogi","doi":"10.1145/3366626","DOIUrl":"https://doi.org/10.1145/3366626","url":null,"abstract":"","PeriodicalId":120474,"journal":{"name":"Proceedings of the 20th International Middleware Conference Industrial Track","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133192500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}