Pub Date : 2008-06-11DOI: 10.1109/SIES.2008.4577680
Farnaz Gharibian, K. Kent
Speed and security of data streams are two key factors in different areas such as data communication and multimedia. Compression algorithms are applied to data streams to increase their communication speed while encryption algorithms are used for assuring the security of the data transfer. AES and LZ77 are two well known algorithms for data encryption and compression respectively. In this paper we propose a model to implement both algorithms, decryption and decompression, in a field programmable gate array chip. Such a design must address the issues of optimal resource usage of the FPGA, and balance between the throughput of both algorithms. Handel-C is considered as the specification language for this design.
{"title":"An embedded decryption/decompression engine using Handel-C","authors":"Farnaz Gharibian, K. Kent","doi":"10.1109/SIES.2008.4577680","DOIUrl":"https://doi.org/10.1109/SIES.2008.4577680","url":null,"abstract":"Speed and security of data streams are two key factors in different areas such as data communication and multimedia. Compression algorithms are applied to data streams to increase their communication speed while encryption algorithms are used for assuring the security of the data transfer. AES and LZ77 are two well known algorithms for data encryption and compression respectively. In this paper we propose a model to implement both algorithms, decryption and decompression, in a field programmable gate array chip. Such a design must address the issues of optimal resource usage of the FPGA, and balance between the throughput of both algorithms. Handel-C is considered as the specification language for this design.","PeriodicalId":438401,"journal":{"name":"2008 International Symposium on Industrial Embedded Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123625690","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}
Pub Date : 2008-06-11DOI: 10.1109/SIES.2008.4577683
Hendrik Schweppe, A. Zimmermann, D. Grill
This paper introduces a method for selectively pre-processing and recording sensor data for engineering testing purposes in vehicles. In order to condense data, methodologies from the domain of sensor networks and stream processing are applied, which results in a reduction of the quantity of data, while maintaining information quality. A situation-dependent modification of recording parameters allows for a detailed profiling of vehicle-related errors. We developed a data-flow oriented model, in which data streams are connected by processing nodes. These nodes filter and aggregate the data and can be connected in nearly any order, which permits a successive composition of the aggregation and recording strategy. The integration with an event-condition-action model provides adaptability of the processing and recording, depending on the state of the vehicle. In a proof-of-concept system, which we implemented on top of the automotive diagnostic protocols KWP and UDS, the feasibility of the approach was shown. The target platform was an embedded on-board computer that is connected to the OBD-II interface of the vehicle. As the scope of recording can be adjusted flexibly, the recording system can not only be used for diagnostic purposes, but also serves objectives in development, quality assurance, and even marketing.
{"title":"Flexible in-vehicle stream processing with distributed automotive control units for engineering and diagnosis","authors":"Hendrik Schweppe, A. Zimmermann, D. Grill","doi":"10.1109/SIES.2008.4577683","DOIUrl":"https://doi.org/10.1109/SIES.2008.4577683","url":null,"abstract":"This paper introduces a method for selectively pre-processing and recording sensor data for engineering testing purposes in vehicles. In order to condense data, methodologies from the domain of sensor networks and stream processing are applied, which results in a reduction of the quantity of data, while maintaining information quality. A situation-dependent modification of recording parameters allows for a detailed profiling of vehicle-related errors. We developed a data-flow oriented model, in which data streams are connected by processing nodes. These nodes filter and aggregate the data and can be connected in nearly any order, which permits a successive composition of the aggregation and recording strategy. The integration with an event-condition-action model provides adaptability of the processing and recording, depending on the state of the vehicle. In a proof-of-concept system, which we implemented on top of the automotive diagnostic protocols KWP and UDS, the feasibility of the approach was shown. The target platform was an embedded on-board computer that is connected to the OBD-II interface of the vehicle. As the scope of recording can be adjusted flexibly, the recording system can not only be used for diagnostic purposes, but also serves objectives in development, quality assurance, and even marketing.","PeriodicalId":438401,"journal":{"name":"2008 International Symposium on Industrial Embedded Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126914869","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}
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