Application-specific Data Research Articles

An Efficient Application Specific Memory Storage and ASIP Behavior Optimization in Embedded System

Low power embedded system requires effective memory design system which improves the system performance with the help of memory implementation techniques. Application specific data allocation design pattern implements the memory storage area and internal cell design techniques implements data transition speeds. Embedded cache design is implemented with simulator and scheduling approaches which can reduce the cache miss behavior and improve the cache hit quantities. Cache hit optimization, delay reduction and latency prediction techniques are effective for ASIP design. The design functionality is simply specifying the tradeoff among various design metrics like performance, power, size, cost and flexibility. ASIP behavior and memory storage area optimized for low power embedded system and implements cycle time with effective scheduling techniques which implements the system performance with low power consumption.

A Comparative Study and Analysis of Data Aggregation Techniques in WSN

Background: Wireless Sensor Network (WSN) often consists of large number sensor nodes which co-operatively send sensed data to base station. These networks are used in various applications scenarios such as habitat monitoring, disaster management, security and military, etc. As the sensor nodes are generally operated by battery driven, an efficient utilization of power is essential. Therefore, to enhance the life time of sensor network, power efficient methods has to be adapted to gather and aggregate data. It's mainly because majority of the sensor node energy is consumed during transmission than computation. Data aggregation is one of the widely recognized solutions to gather and reduce the redundant number of packets to be sent to base station by aggregating them. Literature survey shows that several application specific sensor network data gathering protocols exists in enhancing the network lifetime. Methods: This paper provides a comprehensive survey of different data aggregation algorithms in wireless sensor networks. The different algorithm are compared and contrasted based on the performance measures such as network type, mobility, Data (D) or Node (N) centric protocol, computation characteristics, data delivery model, communication pattern, query based support, energy usage and application type. To evaluate the performance of some of the algorithms surveyed in this work, simulation experiments on Matlab were conducted. Results: It was observed from the results that that the network topology has a high impact on the routing protocols to perform data aggregation. There exist few other protocols using contemporary methodologies such as Tree, Grid and Hybrid approaches which are also discussed in this paper. Application: The survey will help to identify the data aggregation algorithm suitable for a specific application.

QR code based blind digital image watermarking with attack detection code

A QR code based blind digital image watermarking technique with an attack detection feature is described here. The technique describes a key based framework to incorporate image, server port address or website address as watermark data; which increases the extended usability of the embedded data and the adaptability of the verification application. The watermarking problem is formulated as a signal communication problem with watermark data representation, embedding of watermark and attack detection as a source encoding, channel encoding and attenuation detection problems respectively. The mathematical aspects of the respective signal processing problems are extended to digital image watermarking with sufficient background support. The use of QR code ensures extended usability, while the application specific watermark data achieves adaptability of the verification application. The QR code is embedded into the attack resistant HH component of 1st level DWT domain of the cover image and to detect malicious interference by an attacker, a unique image registry code generated from the high frequency structural components of the stego-image is used. The key based approach and the attack resistant embedding domain makes this method robust against visually invariant attacks. The testing results show the compliance of the method with all the proposed aspects.

On the detection of custom memory allocators in C binaries

Many reverse engineering techniques for data structures rely on the knowledge of memory allocation routines. Typically, they interpose on the system's malloc and free functions, and track each chunk of memory thus allocated as a data structure. However, many performance-critical applications implement their own custom memory allocators. Examples include webservers, database management systems, and compilers like gcc and clang. As a result, current binary analysis techniques for tracking data structures fail on such binaries. We present MemBrush, a new tool to detect memory allocation and deallocation functions in stripped binaries with high accuracy. We evaluated the technique on a large number of real world applications that use custom memory allocators. We demonstrate that MemBrush can detect allocators/deallocators with a high accuracy which is 52 out of 59 for allocators, and 29 out of 31 for deallocators in SPECINT 2006. As we show, we can furnish existing reverse engineering tools with detailed information about the memory management API, and as a result perform an analysis of the actual application specific data structures designed by the programmer. Our system uses dynamic analysis and detects memory allocation and deallocation routines by searching for functions that comply with a set of generic characteristics of allocators and deallocators.

Data Management Challenges in Cloud Environments

Recently the cloud computing paradigm has been receiving special excitement and attention in the new researches. Cloud computing has the potential to change a large part of the IT activity, making software even more interesting as a service and shaping the way IT hardware is proposed and purchased. Developers with novel ideas for new Internet services no longer require the large capital outlays in hardware to present their service or the human expense to do it. These cloud applications apply large data centers and powerful servers that host Web applications and Web services. This report presents an overview of what cloud computing means, its history along with the advantages and disadvantages. In this paper we describe the problems and opportunities of deploying data management issues on these emerging cloud computing platforms. We study that large scale data analysis jobs, decision support systems, and application specific data marts are more likely to take benefit of cloud computing platforms than operational, transactional database systems. 

Providing service assurance in mobile opportunistic networks

Concomitant to the growing popularity of Internet enabled mobile devices such as smartphones, tablets, PDAs, portable media players etc., however, are the concerns about availability of Internet access points for these devices. Network traffic originating from these devices has marked a multi-fold increase over the past few years. This increase in network traffic has in turn resulted in increased content availability and maintainability cost to the cellular service providers. Major challenges faced by mobile Internet users are limited hardware resources (3G or LTE) or exhaustion of carrier enforced data plans. Thus, users often either overpay for service availability such as (3G or LTE) or suffer incapability of accessing Internet services. In this paper, we argue that the ad-hoc network comprising of spatio-temporally co-existing users, identified as “Familiar Strangers” could be harnessed for viral dissemination of mobile application data. We present the architecture of a collaborative data sharing framework which comprises of two services, namely SmartParcel and CollabAssure. “SmartParcel” allows users to share mobile application data with their spatio-temporally co-existing peers. This service allows a user to receive application specific data from its neighboring nodes instead of cloud infrastructure. This reduces the network overhead generated by a large number of devices and thus, reducing content maintainability and dissemination costs at the server side. This system, however, suffers from the “tragedy of commons” problem, to overcome which we present the design of CollabAssure”. “CollabAssure” is an auction based, ad-hoc market model, assuring service by giving users incentives to “sublet” their surplus data plans to the users without Internet access. CollabAssure service allows users to participate in ad hoc auctions with their spatio-temporally co-existing neighbors as buyers or sellers of the data bandwidth. This in turn reduces under utilization overhead of the overpaying mobile data users. Users with limited or no data plans also benefit from CollabAssure service by receiving services from ad-hoc peers. We perform trace based simulations by varying data refresh rates, allowed server connections, probability of user participation and analyze the data availability at different times of the day. Our simulation results advocate a higher Internet data service is ensured by using our proposed data sharing framework.

English

As the scale of integration keeps growing, more and more sophisticated signal processing systems are being implemented on a VLSI chip. These signal processing applications not only demand great computation capacity but also consume considerable amounts of energy. While performance and area remain to be two major design goals, power consumption has become a critical concern in today’s VLSI system design. Multiplication is a fundamental operation in most arithmetic computing systems. Multipliers have large area, long latency and consume considerable power. Previous work on low-power multipliers focuses on low-level optimizations and has not considered well the arithmetic computation features and application-specific data characteristics. Binary multiplier is an integral part of the arithmetic logic unit (ALU) subsystem found in many processors. Booth's algorithm and others like Wallace-Tree suggest techniques for multiplying signed numbers that works equally well for both negative and positive multipliers. This synopsis proposes the design and implementation of Booth multiplier using VHDL . This compares the power consumption and delay of radix 2 and modified radix 4 Booth multipliers. The modified radix 4 Booth multiplier has reduced power consumption than the conventional radix 2 Booth Multiplier.

Analysis and design of software ecosystem architectures – Towards the 4S telemedicine ecosystem

ContextTelemedicine, the provision of health care at a distance, is arguably an effective way of increasing access to, reducing cost of, and improving quality of care. However, the deployment of telemedicine is faced with standards that are hard to use, application-specific data models, and application stove-pipes that inhibit the adoption of telemedical solutions. To which extent can a software ecosystem approach to telemedicine alleviate this? ObjectiveIn this article, we define the concept of software ecosystem architecture as the structure(s) of a software ecosystem comprising elements, relations among them, and properties of both. Our objective is to show how this concept can be used (i) in the analysis of existing software ecosystems and (ii) in the design of new software ecosystems. MethodWe performed a mixed-method study that consisted of a case study and an experiment. For (i), we performed a descriptive, revelatory case study of the Danish telemedicine ecosystem and for (ii), we experimentally designed, implemented, and evaluated the architecture of 4S. ResultsWe contribute in three areas. First, we define the software ecosystem architecture concept that captures organization, business, and software aspects of software ecosystems. Secondly, we apply this concept in our case study and demonstrate that it is a viable concept for software ecosystem analysis. Finally, based on our experiments, we discuss the practice of software engineering for software ecosystems drawn from experience in creating and evolving the 4S telemedicine ecosystem. ConclusionThe concept of software ecosystem architecture can be used analytically and constructively in respectively the analysis and design of software ecosystems.

Efficient Lung Air Volume Estimation Using Human Respiratory Image Sequences

This article presents experiences in the automation of a testing process. The main goal is the unified testing of not only one program, but a whole family of programs. The family is characterized by a common functionality and therefore similar GUI interfaces. The testing process integrates extraction of the application specific data from its executable and the usage of the capture and replay testing technique. The testing of various me mbers of application family is driven by a unified, common script. The approach is illustrated by a case study. As a family of applications under test a set of RSS aggregators was used. A unified test RSSscript was developed and verified in test experiments. The results of functional, performance and regression testing are presented. The benefits and limitations of the solution are discussed.

The Antibody Challenge

The Antibody Challenge

A Parameterizable NoC Router for FPGAs

The Network-on-Chip (NoC) approach fordesigning (System-on-Chip) SoCs is currently used forovercoming the scalability and efficiency problems of traditional on-chipinterconnection schemes, such as shared buses and point-to-point links. NoCdesign draws on concepts from computer networks to interconnect IntellectualProperty (IP) cores in a structured and scalable way, promoting design re-use.This paper presents the design and evaluation of a parameterizable NoC routerfor FPGAs. The importance of low area overhead for NoC components is pivotal inFPGAs, which have limited logic and routing resources. We obtain a low arearouter design by applying optimizations in switching fabric and dual purposebuffer/connection signals. We utilize a store and forward flow control withinput and output buffering. We proffer a component library to increase re-useand allow tailoring of parameters for application specific NoCs of varioussizes. The proposed router supports the mesh architecture which is well knownfor its scalability and simple XY routing algorithm. We presentIP-core-to-router mapping strategies for multi-local port routers that enableample opportunity to optimize the NoC for application specific data traffic. Aset of experiments were conducted to explore the design space of the proposedNoC router using different values of key router parameters: channel width (flitsize), arbitration scheme and IP-core-to-router mapping strategy. Area andlatency results from the experiments are presented and analyzed. These resultswill be useful to designers who want to implement NoC on FPGAs.

SIAVA: Secret Information Aggregation Design for Various Applications in Wireless Sensor Networks

In general information aggregation design that reduces a large amount of transmission is the most practical technique. In previous studies, homomorphic encryptions have been applied to conceal communication during aggregation such that enciphered data can be aggregated algebraically without decryption. Since aggregators collect data without decryption, adversaries are not able to forge aggregated results by compromising them. However, these schemes are not satisfy multi-application environments. Second, these schemes become insecure in case some sensor nodes are compromised. Third, these schemes do not provide secure counting; thus, they may suffer unauthorized aggregation attacks. Therefore, we propose a new concealed data aggregation scheme extended from Boneh et al.s homomorphic public encryption system. The proposed scheme has three contributions. First, it is designed for a multi-application environment. The base station extracts application-specific data from aggregated cipher texts. Next, it mitigates the impact of compromising attacks in single application environments. Finally, it degrades the damage from unauthorized aggregations. To prove the proposed schemes robustness and efficiency, we also conducted the comprehensive analyses and comparisons in the end.

Establishing Performance Evaluation Model with Queuing Theory in NoC

The transmission delay is an important index of the system performance of NoC (Network on Chip). Although the method of simulation-based can get accurate transmission delay, the simulation requires time consuming and a large number of test vectors. Especially in the study of some algorithms, such as mapping algorithms, buffer allocation algorithm, the simulation method is not applicable. To solve the above problems, the paper uses queuing theory to study the establishment of a NoC delay model. The model considers the limited buffer of routing unit and virtual channel technology for network transmission delay and proposes solving algorithm of the delay model based on reverse deduction method. The simulation shows that this model used to analyze the application-specific data transmission delay has smaller average error (reduced by 8%) and higher evaluation efficiency (increased by more than 30 times), which provide designers an efficient method of performance evaluation. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3395

CDAMA: Concealed Data Aggregation Scheme for Multiple Applications in Wireless Sensor Networks

For wireless sensor networks, data aggregation scheme that reduces a large amount of transmission is the most practical technique. In previous studies, homomorphic encryptions have been applied to conceal communication during aggregation such that enciphered data can be aggregated algebraically without decryption. Since aggregators collect data without decryption, adversaries are not able to forge aggregated results by compromising them. However, these schemes are not satisfy multi-application environments. Second, these schemes become insecure in case some sensor nodes are compromised. Third, these schemes do not provide secure counting; thus, they may suffer unauthorized aggregation attacks. Therefore, we propose a new concealed data aggregation scheme extended from Boneh et al.'s homomorphic public encryption system. The proposed scheme has three contributions. First, it is designed for a multi-application environment. The base station extracts application-specific data from aggregated ciphertexts. Next, it mitigates the impact of compromising attacks in single application environments. Finally, it degrades the damage from unauthorized aggregations. To prove the proposed scheme's robustness and efficiency, we also conducted the comprehensive analyses and comparisons in the end.

Combining the Arc Marine Framework with Geographic Metadata to Support Ocean Acoustic Modeling

AbstractA data model for use in a rapid environmental assessment system is constructed. The data model is used in an information layer that supports acoustic assessments of the ocean environment. Such an assessment requires use of both historic and real‐time oceanographic data. The foundation of the data model is Arc Marine, a framework specification for geospatial oceanographic databases that provides structures for containing the basic data types used in oceanographic research. Arc Marine also allows design extensions to account for application specific data structures as demonstrated through incorporation of aspects of the International Organization for Standardization (ISO) 19115 Geographic Information–Metadata standard. The ISO 19115 standard provides structures for recording the historic processing of the data sets. The data model is used to construct a database in the open source database management system (DBMS) PostgreSQL. The resulting system also incorporates the concept of user exits, the seamless extension of the DBMS through inclusion of application‐specific software.

ANALYSIS, VERIFICATION AND FPGA IMPLEMENTATION OF LOW POWER MULTIPLIER

As the scale of integration keeps growing, more and more sophisticated signal processing systems are being implemented on a VLSI chip. These signal processing applications not only demand great computation capacity but also consume considerable amounts of energy. While performance and area remain to be two major design goals, power consumption has become a critical concern in today’s VLSI system design. Multiplication is a fundamental operation in most arithmetic computing systems. Multipliers have large area, long latency and consume considerable power. Previous work on low-power multipliers focuses on low-level optimizations and has not considered well the arithmetic computation features and application-specific data characteristics. Binary multiplier is an integral part of the arithmetic logic unit (ALU) subsystem found in many processors. Booth's algorithm and others like Wallace-Tree suggest techniques for multiplying signed numbers that works equally well for both negative and positive multipliers. In this paper, we have used VHDL for describing and verifying a hardware design based on Booth's and some other efficient algorithms. Timing and correctness properties were verified. Instead of writing Test-Benches & Test-Cases we used WaveForm Analyzer which can give a better understanding of Signals & variables and also proved a good choice for simulation of design.

A stochastic approach for evaluating quality of service in wireless cellular networks

Recent increases in application and user data over cellular networks requires networks service providers to guarantee a well-defined quality of service for their customers. As such, network service providers must be able to evaluate and assess the quality of service in different types of applications over their networks. This paper presents a method for assessing quality of service in application-specific and user-centric data on cellular networks. To this end, it formulates the evaluation problem as a stochastic multi-attribute decision problem in which measurement parameters are used as probabilistic attributes of the problem collected in drive testing over three different cellular networks. Matrix relational analysis is applied on the decision matrix to solve the problem by reaching a final ranking of the networks based on the collected measured values of the problem parameters. A case study is used to show how this approach can be effective in evaluating quality of service in cellular networks.

Ethopian Database Management system as a Cloud Service: Limitations and advantages

An Ethiopian Cloud database management system is a distributed database that delivers computing as a service instead of a product. It is the sharing of resources, software, and information between multiple devices over a network which is mostly the internet. It is expected that this number will grow significantly in the future. As a result, there is a growing interest in outsourcing database management tasks to third parties that can provide these tasks for much lower cost due to the economy of scale just like putting it into the cloud. In this paper, we discuss the recent trend in database management system and the possibilities of making it as one of the services offered in the cloud. We also Recently the cloud computing paradigm has been receiving significant excitement and attention in the media and blogosphere. To some, cloud computing seems to be little more than a marketing umbrella, encompassing topics such as distributed computing, grid computing, utility computing, and software as- a-service, that have already received significant research focus and commercial implementation. Nonetheless, there exist an increasing number of large companies that are offering cloud computing infrastructure products and services that do not entirely resemble the visions of these individual component topics. In this article we discuss the limitations and opportunities of deploying data management issues on these emerging cloud computing platforms. We speculate that large scale data analysis tasks, decision support systems, and application specific data marts are more likely to take advantage of cloud computing platforms than operational, transactional database systems (at least initially). We then discuss some currently available open source and commercial database options that can be used to perform such analysis tasks, and conclude that none of these options, as presently architected, match the requisite features. We thus express the need for a new DBMS, designed specifically for Ethiopian cloud computing environments.

Digital methods for process development in manufacturing and their relevance to value driven design

This paper examines the applicability of a digital manufacturing framework to the implementation of a Value Driven Design (VDD) approach for the development of a stiffened composite panel. It presents a means by which environmental considerations can be integrated with conventional product and process design drivers within a customized, digital environment. A composite forming process is used as an exemplar for the work which creates a collaborative environment for the integration of more traditional design drivers with parameters related to manufacturability as well as more sustainable processes and products. The environmental stakeholder is introduced to the VDD process through a customized product/process/resource (PPR) environment where application specific power consumption and material waste data has been measured and characterised in the process design interface. This allows the manufacturing planner to consider power consumption as a concurrent design driver and the inclusion of energy as a parameter in a VDD approach to the development of efficiently manufactured, sustainable transport systems.

A novel framework for energy-efficient data gathering with random coverage in wireless sensor networks

In wireless sensor networks, different applications feature different requirements in terms of such performance metrics as sensing coverage and data reporting latency. In most applications, it is usually sufficient to provide a Desired Sensing Coverage (DSC) lower than full coverage at any instance with the guarantee that the whole area will eventually be covered within a specified delay bound. Due to the fact that these applications are also expected to run for longer periods of time and at the same time battery recharging and replacement are costly, energy consumption in wireless sensor networks should be minimized while achieving the application goals. In this article, we propose a novel framework for application-specific data gathering which exploits a trade-off between coverage and latency, thereby minimizing energy consumption and extending the network lifetime. The proposed energy-efficient, constant-time, randomized scheme, called Coverage-Adaptive raNdom SEnsor sElection (CANSEE), selects a subset of k sensors to report at each round so as to fulfill the application-specific requirement of desired sensing coverage and bounded latency, instead of always guaranteeing full coverage and minimum latency. We present a probabilistic model to estimate: (i) the connectivity of those selected k sensors and the number of additional sensors needed to guarantee connectivity; (ii) a lower bound on k in each round; and (iii) the probability of almost surely having k data reporters using the Chernoff bound. The immediate event detection capability achieved by the proposed CANSEE scheme is also analyzed to compare the performance of our framework with other data gathering schemes that allow 100% coverage. Simulation results demonstrate that our framework leads to a significant conservation of energy (and thus extended network lifetime) with a small trade-off between coverage and data reporting latency, yet providing the required data reporting capability.