Abstract

The memory and core requirements of a virtual machine depend on the performance requirements of the applications hosted on it. In this paper, we propose algorithms for dynamic memory and core scaling using a combination of machine learning and feedback control techniques. These algorithms work for sequential and parallel applications such as scientific computations where speedup is the primary performance metric. Then we use these algorithms to address the simultaneous memory and core allocation problem, which is more complex due to possible correlation between these resource requirements. All these algorithms can be applied in a black box fashion without instrumenting the source code of applications.

Abstract

Real-time multimedia applications which demand very low decoding delays are increasing day-by-day. To address this challenge, in error-resilient applications, many approximate computing architectures for delay critical units have been proposed. In this paper, we propose an architecture for an approximate multiplier, accuracy of which can be configured during the run-time. According to the requirement of the application, the multiplier can be configured to operate in an exact mode or in any of the approximate modes, reducing its decoding delay and the dynamic power consumed. The architecture for the proposed approximate multiplier has been synthesized and simulated using Cadence design tools. Using 16-bit multiplication, it has been demonstrated that, the pass-rate and the propagation delay of the proposed multiplier is comparable or better than most of the published inaccurate multipliers. The proposed approximate multiplier is successfully used in a JPEG conversion application and performances of different accuracy modes are compared.

Abstract

The telecare medicine information system (TMIS) helps the patients to gain the health monitoring facility at home and access medical services over the Internet of mobile networks. Recently, Amin and Biswas presented a smart card based user authentication and key agreement security protocol usable for TMIS system using the cryptographic one-way hash function and biohashing function, and claimed that their scheme is secure against all possible attacks. Though their scheme is efficient due to usage of one-way hash function, we show that their scheme has several security pitfalls and design flaws, such as (1) it fails to protect privileged-insider attack, (2) it fails to protect strong replay attack, (3) it fails to protect strong man-in-the-middle attack, (4) it has design flaw in user registration phase, (5) it has design flaw in login phase, (6) it has design flaw in password change phase, (7) it lacks of supporting biometric update phase, and (8) it has flaws in formal security analysis. In order to withstand these security pitfalls and design flaws, we aim to propose a secure and robust user authenticated key agreement scheme for the hierarchical multi-server environment suitable in TMIS using the cryptographic one-way hash function and fuzzy extractor. Through the rigorous security analysis including the formal security analysis using the widely-accepted Burrows-Abadi-Needham (BAN) logic, the formal security analysis under the random oracle model and the informal security analysis, we show that our scheme is secure against possible known attacks. Furthermore, we simulate our scheme using the most-widely accepted and used Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. The simulation results show that our scheme is also secure. Our scheme is more efficient in computation and communication as compared to Amin-Biswas’s scheme and other related schemes. In addition, our scheme supports extra functionality features as compared to other related schemes. As a result, our scheme is very appropriate for practical applications in TMIS.

Abstract

Recent advanced technology enables the telecare medicine information system (TMIS) for the patients to gain the health monitoring facility at home and also to access medical services over the Internet of mobile networks. Several remote user authentication schemes have been proposed in the literature for TMIS. However, most of them are either insecure against various known attacks or they are inefficient. Recently, Tan proposed an efficient user anonymity preserving three-factor authentication scheme for TMIS. In this paper, we show that though Tan’s scheme is efficient, it has several security drawbacks such as (1) it fails to provide proper authentication during the login phase, (2) it fails to provide correct updation of password and biometric of a user during the password and biometric update phase, and (3) it fails to protect against replay attack. In addition, Tan’s scheme lacks the formal security analysis and verification. Later, Arshad and Nikooghadam also pointed out some security flaws in Tan’s scheme and then presented an improvement on Tan’s s scheme. However, we show that Arshad and Nikooghadam’s scheme is still insecure against the privileged-insider attack through the stolen smart-card attack, and it also lacks the formal security analysis and verification. In order to withstand those security loopholes found in both Tan’s scheme, and Arshad and Nikooghadam’s scheme, we aim to propose an effective and more secure three-factor remote user authentication scheme for TMIS. Our scheme provides the user anonymity property. Through the rigorous informal and formal security analysis using random oracle models and the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool, we show that our scheme is secure against various known attacks, including the replay and man-in-the-middle attacks. Furthermore, our scheme is also efficient as compared to other related schemes.Recent advanced technology enables the telecare medicine information system (TMIS) for the patients to gain the health monitoring facility at home and also to access medical services over the Internet of mobile networks. Several remote user authentication schemes have been proposed in the literature for TMIS. However, most of them are either insecure against various known attacks or they are inefficient. Recently, Tan proposed an efficient user anonymity preserving three-factor authentication scheme for TMIS. In this paper, we show that though Tan’s scheme is efficient, it has several security drawbacks such as (1) it fails to provide proper authentication during the login phase, (2) it fails to provide correct updation of password and biometric of a user during the password and biometric update phase, and (3) it fails to protect against replay attack. In addition, Tan’s scheme lacks the formal security analysis and verification. Later, Arshad and Nikooghadam also pointed out some security flaws in Tan’s scheme and then presented an improvement on Tan’s s scheme. However, we show that Arshad and Nikooghadam’s scheme is still insecure against the privileged-insider attack through the stolen smart-card attack, and it also lacks the formal security analysis and verification. In order to withstand those security loopholes found in both Tan’s scheme, and Arshad and Nikooghadam’s scheme, we aim to propose an effective and more secure three-factor remote user authentication scheme for TMIS. Our scheme provides the user anonymity property. Through the rigorous informal and formal security analysis using random oracle models and the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool, we show that our scheme is secure against various known attacks, including the replay and man-in-the-middle attacks. Furthermore, our scheme is also efficient as compared to other related schemes.

Abstract

SURROGATE CITY FINDER - WEATHER DATA TOOLVishal Garg, T.V.S Nikhil, Hema Rallapalli,Aviruch Bhatia, Jegibabu Subhash, Chetan Kasireddy International Institute of Information Technology, Hyderabad, India. ABSTRACTWeather data is the one of the important inputs for the building energy simulation and is available for almost all major cities of the world. However, there are still some cities, for which weather data is not readily available in the format suitable for energy simulation. To address this problem, we have developed a web-based tool called Surrogate City Finder (SCF). For a given location, for which there is no weather file available, the tool shortlists the best-matched weather files based on parameters such as the latitude, altitude, and temperature range of the given location. The SCF tool has been tested by analysing the annual energy consumption of 16-reference building models simulated for eight locations from different international climate zones and their surrogate cities. In most cases, the deviation in annual energy consumption was within two percent.

Abstract

To make roofs energy efficient, typically two types of techniques are followed: surface treatments (coolroofs, radiant barriers) and thermal property modifications (roof insulation). The interplay between thesetwo techniques has been studied using energy simulations. A single storey, daytime operational, officebuilding of 200 m2area has been simulated forfive climatic zones in India. A total of 88 different roofcombinations have been studied for each climatic zone. An economic analysis using Internal Rate ofReturn has been performed to identify a suitable roof insulation thickness for a roof with high albedo,and radiant barrier combination. The incremental benefits in energy savings reduces by adding insulationafter a limit. For a roof with albedo of 0.6 and radiant barrier emittance of 0.2, the optimized roofR-valueis 0.49 m2K/W in hot and dry and composite climates, 0.31 m2K/W in warm and humid and temperateclimates, and 1.02 m2K/W for cold climates

Abstract

The systems for weather observation and forecast are being operated to deal with adverse weather in general to mankind. Weather-based decision support systems (DSSs) are being build to improve the efficiency of the production systems in the domains of health, agriculture, livestock, transport, business, planing, governance and so on.The weather-based DSS provides appropriate suggestions based on the weather condition of the given period for the selected domain. In the literature, the notion of reuse is being employed in improving the efficiency of DSSs. In this paper, we have proposed a framework to identify similar weather conditions, which could help in improving the performance of weather-based DSSs with better reuse. In the proposed framework, the range of weather variable is divided into categories based on its influence on that domain. We form a weather condition for a period which is the combination of category values of weather variables. By comparing the daily/weekly weather conditions of a given year to weather conditions of subsequent years, the proposed framework identifies the extent of reuse.We have conducted the experiment by applying the proposed framework on 30 years of weather data of Rajendranagar, Hyderabad and using the categories employed by India Meteorological Department in Meteorology domain. The results show that there is a significant degree of similarity among daily and weekly weather conditions over the years. The results provide an opportunity to improve the efficiency of weather-based DSSs by improving the degree of reuse of the developed suggestions/knowledge for the corresponding weather conditions.

Abstract

Extraction of water bodies from satellite imagery has been widely explored in the recent past. Several approaches have been developed to delineate water bodies from different satellite imagery varying in spatial, spectral, and temporal characteristics. The current study puts forward an automatic approach to extract the water body from a Landsat satellite imagery using a perceptron model. Perceptron involves classification based on a linear predictor function that merges few characteristic properties of the object commonly known as feature vectors. The feature vectors, combined with the weights, sum up to provide an input to the output function which is a binary hard limit function. The feature vector in this study is a set of characteristic properties shown by a pixelof the water body. Low reflectance of water in SWIR band, comparison of reflectance in different bands, and a modified normalized difference water index are used as descriptors. The normalized difference water index is modified to enhance its reach over shallowregions. For this study a threshold value of 2 has been proved as best among the three possible threshold values. The proposed method accurately and quickly discriminated water from other land cover features.

Abstract

The traditional pixel-based classification totally relies on spectral information and neglects the spatial information. These methods when applied on very high-resolution imagery get confused because of the increased variability implicit within the data and thus leads to lower classification accuracies.The object-based image analysis (OBIA) is advantageous to deal with objects that are composed of homogeneous pixels.This paper aims at automatically extracting buildings from very high-resolution satellite imagery using Object Based Image Analysis(OBIA).The algorithm uses an active contour model called chan-vese segmentation to create objects from the image. Objects representing vegetation or trees are removed by subtracting NDVI mask from the segmented output. The detected objects are further filtered based on regional properties like minimum area, width of object etc. The results are promising with 74-77%of the buildings getting detected as objects

Abstract

We have addressed the problem of visualization of vector building data on top of a terrain. It tries to make it more realistic by automated draping of building textures from geo-tagged images which are captured from a cell phone camera with a built-in GPS. We use the properties of the images to tag them to the corresponding 2D polygon footprint by using the camera pose, and the cameras position to automate our process. The elevation data captured from NASAs SRTM project, GTOPO, etc can be used to render 3D terrains using existing GPU based Level of detail(LOD) algorithms[1] [2][3]. The vector data of buildings along with their height at-tributes can be obtained from various Lidar based algorithmsor from DEM data[4] [5]. A scene graph is used as the data structure which is used to render these vector based graphics models