End-user Services Research Articles

A general purpose contention manager for software transactions on the GPU

The Graphics Processing Unit (GPU) is now used extensively for general purpose GPU programming (GPGPU), allowing for greater exploitation of the multi-core model across many application domains. This is particularly true in cloud/edge/fog computing, where multiple GPU enabled servers support many different end user services. This move away from the naturally parallel domain of graphics can incur significant performance issues. Unlike the CPU, code that is hindered from execution due to blocking/waiting on the GPU can affect thousands of threads, rendering the advantages of a GPU irrelevant and reducing a highly parallel environment down to a serial one in the worst case. In this paper we present a solution that minimises blocking/waiting in GPGPU computing using a contention manager that offsets memory conflicts across threads through thread re-ordering. We consider conflicts of memory not only to avoid corruption (standard for transactional memory) but also in the semantic layer of application logic (e.g., enforcing ordering to ensure money drawn from bank account occurs after all deposits). We demonstrate how our approach is successful across a number of industry benchmarks and compare our approach to the only other related solution. We also demonstrate that our approach is scalable in terms of thread numbers (a key requirement on the GPU). We believe this is the first work of its kind demonstrating a generalised conflict and semantic contention manager suitable for the scale of parallel execution found on a GPU.

A gearbox model for processing large volumes of data by using pipeline systems encapsulated into virtual containers

Software pipelines enable organizations to chain applications for adding value to contents (e.g., confidentially, reliability, and integrity) before either sharing them with partners or sending them to the cloud. However, the pipeline components add overhead when processing large volumes of data, which can become critical in real-world scenarios. This paper presents a gearbox model for processing large volumes of data by using pipeline systems encapsulated into virtual containers. In this model, the gears represent applications, whereas gearboxes represent software pipelines. This model was implemented as a collaborative system that automatically performs Gear up (by using parallel patterns) and/or Gear down (by using in-memory storage) until all gears produce uniform data processing velocities. This model reduces delays and bottlenecks produced by the heterogeneous performance of applications included in software pipelines. The new container tool capsule has been designed to encapsulate both the collaborative system and the software pipelines into a virtual container and deploy it on IT infrastructures. We conducted case studies to evaluate the performance of capsule when processing medical images and PDF repositories. The incorporation of a capsule to a cloud storage service for pre-processing medical imagery was also studied. The experimental evaluation revealed the feasibility of applying the gearbox model to the deployment of software pipelines in real-world scenarios as it can significantly improve the end-user service experience when pre-processing large-scale data in comparison with state-of-the-art solutions such as Sacbe and Parsl.

Workload Allocation in IoT-Fog-Cloud Architecture Using a Multi-Objective Genetic Algorithm

With the rapid growth of Internet-of-Things (IoT) applications, data volumes have been considerably increased. The processing resources of IoT nodes cannot cope with such huge workloads. Processing parts of the workload in clouds could solve this problem, but the quality of services for end-users will be decreased. Given the latency reduction for end-users, the concept of processing in the fog devices, which are at the edge of the network has been evolved. Optimizing the energy consumption of fog devices in comparison with cloud devices is a significant challenge. On the other hand, providing the expected-quality of service in processing the requested workloads is highly dependent on the propagation delay between fog devices and clouds, which due to the nature of the distribution of clouds with the different workloads, is highly variable. To date, none of the proposed solutions has solved the problem of workload allocation given the criteria of minimizing the energy and delay of fog devices and clouds, simultaneously. This paper presents a processing model for the problem in which a trade-off between energy consumption and delay in processing workloads in fog is formulated. This multi-objective model of the problem is solved using NSGAII algorithm. The numerical results show that by using the proposed algorithm for workload allocation in a fog-cloud scenario, both of energy-consumption and delay can be improved. Also, by allocating 25% of the IoT workloads to fog devices, the energy consumption and delay are both minimized.

Evaluation of a Codesign Method Used to Support the Inclusion of Children With Disability in Mainstream Schools

Codesign is increasingly used for health research and service improvement. Codesign combines generative and exploratory methods, enabling collaboration between service end users and researchers as equal partners. The aim of this study was to evaluate a codesign method used to design an online education package about inclusive education for children with disability in mainstream schools. The study design was a multiple methods evaluation informed by participatory and transformative research paradigms, incorporating design sciences and public service approaches. A governance committee supported the process. The codesigners ( n = 12) included teachers, teacher assistants, parents, and allied health professionals. Process and outcome evaluation data were used; data collected were from verbatim transcripts of codesign workshop discussions ( n = 11), documents, Self-Report Level of Participation Surveys, and individual interviews ( n = 11). Thematic and descriptive analysis methods were used to describe the codesign processes, experiences, and outcomes. The key processes were identifying the issues through storytelling, voicing frustrations, being vulnerable, sharing insider knowledge, challenging other people’s roles, and deliberation and decision-making. Codesigners’ experiences and outcomes identified strengths and challenges in the method. A conceptual model is presented demonstrating interrelationships between processes, subprocesses, and codesigners’ experiences and outcomes. Codesign involves multiple, interrelated processes that support deliberation and creative design. Skills and resources are required to effectively facilitate what can be a meaningful, creative, and social process.

QoS Guaranteed Resource Allocation for Live Virtual Machine Migration in Edge Clouds

Live Virtual Machine (VM) migration among geographically distributed edge clouds is an important strategy for providing low latency and reliable services for mobile end users. VM migration among edge clouds is more challenging than that in cloud computing, because the network bandwidth among edge clouds is more constrained than the cloud data center networks. In this paper, we study the bandwidth allocation among multiple concurrent live VM migrations in edge clouds. This problem is novel in that existing works aim to reduce the migration time for a single live VM migration among the edge clouds, and also ignores the QoS requirement for the service running on the VM in migration. However, our problem considers multiple VM migration tasks, and aims to maximize the average QoS while meeting the migration time constraint for each VM migration task. We formulate the problem as a Non-Linear Programming (NLP) problem which is also shown to be NP-Hard. We develop a new method to solve this problem. In our approach, we first transfer the problem into a Linear Programming (LP) problem by reducing the solution space. Taking the output from the LP solver as an initial solution, we then develop a heuristic to adjust it in order to find a better one to the original NLP problem. Finally, we design a set of evolutionary algorithms to select the optimal initial solution from the LP solver. Extensive simulations show that our proposed method can achieve good QoS and also has a fast convergence speed.

Deep Learning Enabled Data Offloading With Cyber Attack Detection Model in Mobile Edge Computing Systems

Mobile edge computing (MEC) becomes popular as it offers cloud services and functionalities to the edge devices, to enhance the quality of service (QoS) of end-users by offloading their computationally intensive tasks. At the same time, the rise in the number of internet of things (IoT) objectives poses considerable cybersecurity issues owing to the latest rise in the existence of attacks. Presently, the development of deep learning and hardware technologies offers a way to detect the present traffic condition, data offloading, and cyber-attacks in edge networks. The utilization of DL models finds helpful in several domains in which the MEC provides the decisive beneficiary of the approach for traffic prediction and attack detection since a large quantity of data generated by IoT devices enables deep models to learn better than shallow approaches. In this view, this paper presents a new DL based traffic prediction with a data offloading mechanism with cyber-attack detection (DLTPDO-CD) technique. The proposed model involves three major processes traffic prediction, data offloading, and attack detection. Initially, bidirectional long short term memory (BiLSTM) based traffic prediction to enable the proficient data offloading process. Then, the adaptive sampling cross entropy (ASCE) technique is executed to maximize the network throughput by making decisions related to offloading users to the WiFi system. Finally, a deep belief network (DBN) optimized by a barnacles mating optimizer (BMO) algorithm called BMO-DBN is applied as a detection tool for cyberattacks in MEC. Extensive simulation is carried out to ensure the proficient performance of the DLTPDO-CD model. The experimental outcome stated the superiority of the presented model over the compared methods under different dimensions.

Automatic classification for preventing duplication of online multimedia data in secure cloud infrastructure

Cloud computing provides various types of software and hardware services collectively working together at different computational environment to the end user through internet. Cloud computing is an emerging technology that provides variety of applications to the end user and cloud services can be accessed from anywhere in the world in secured way whenever required. Nowadays free online hosting websites produce a large amount of multimedia data. It may include images, audios, 2D videos, 3D videos. Some people will use videos and audios in the distributed environment against the copyrights from the original content creators. This will create a large amount of revenue loss for the original content creator. The protection of theses multimedia content is a challenging task. Cloud computing has some security issues like authentication, privacy and data security. Our proposed system will provide highly scalable storage infrastructure in cloud environment. It also protects the multimedia content by creating a depth signature and classifying them with duplicated contents using SVM classifier. This proposed system will avoid the security issues in multimedia content and it will increase the revenue for original content creator. The proposed system can work in both public and private cloud infrastructure.

Управління ланцюгами поставок: шляхи вдосконалення

Living in a global world, we cannot limit supply chain to only one, two, or even three countries. Hence, supply chain manager’s key function now is to continuously reduce the time of goods flow and minimize the number of chain links making the chain more efficient and cost effective. The article outlines key components of the concept of supply chain management. We regard the management concept itself as planning, management and supply chain development on every stage of creation of goods and services: from raw materials supply to an end user service maintenance. We should streamline supply chain management to exclude all barriers, which different stakeholders may face during the flow. SCM-concept helps control the work of existing processing lines in the supply chain management system, create optimal planning what and when we should deliver, taking into account possible limits of capacity and access to raw materials. Currently, the motor vehicles do the major domestic transportation. Motor transport development is one of the most important aspects of effective economy development. In cross border transportation the share of freight transportation is growing compared to other means of transport. However, domestic motor transport and fuel quality have considerable mismatch of environment properties that lag far behind global requirements. Transport companies inside supply chain have moved beyond conventional services, at the same time they have higher market consolidation, integration, and collaboration with different agents that give new demands to transportation in logistics. The article identifies basic methods of supply chain management. We analyzed impact of modern technologies on logistics and supply chain management: 3D printing, radio frequency identification, unmanned aerial vehicles, connected and autonomous vehicles, and augmented reality. Modern technologies provide small and medium enterprises opportunities to use innovative tools to obtain data-driven analytics, visualization, and processing of cargo. In order to make supply chain management efficient, we should use new technologies, modern devices, and tangible assets of high quality.

Design Choices for Central Bank Digital Currency: Policy and Technical Considerations

Central banks around the world are exploring and in some cases even piloting Central Bank Digital Currencies (CBDCs). CBDCs promise to realize a broad range of new capabilities, including direct government disbursements to citizens, frictionless consumer payment and money-transfer systems, and a range of new financial instruments and monetary policy levers. CBDCs also give rise, however, to a host of challenging technical goals and design questions that are qualitatively and quantitatively different from those in existing government and consumer payment systems. A well-functioning CBDC will require an extremely resilient, secure, and performant new infrastructure, with the ability to onboard, authenticate, and support users on massive scale. It will necessitate an architecture simple enough to support modular design and rigorous security analysis, but flexible enough to accommodate current and future functional requirements and use cases. A CBDC will also in some way need to address an innate tension between privacy and transparency, protecting user data from abuse while selectively permitting data mining for end-user services, policymakers, and law enforcement investigations and interventions.In this paper, we enumerate the fundamental technical design challenges facing CBDC designers, with a particular focus on performance, privacy, and security. Through a survey of relevant academic and industry research and deployed systems, we discuss the state of the art in technologies that can address the challenges involved in successful CBDC deployment. We also present a vision of the rich range of functionalities and use cases that a well-designed CBDC platform could ultimately offer users. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Design Choices for Central Bank Digital Currency: Policy and Technical Considerations

Central banks around the world are exploring and in some cases even piloting Central Bank Digital Currencies (CBDCs). CBDCs promise to realize a broad range of new capabilities, including direct government disbursements to citizens, frictionless consumer payment and money-transfer systems, and a range of new financial instruments and monetary policy levers. CBDCs also give rise, however, to a host of challenging technical goals and design questions that are qualitatively and quantitatively different from those in existing government and consumer payment systems. A well-functioning CBDC will require an extremely resilient, secure, and performant new infrastructure, with the ability to onboard, authenticate, and support users on a massive scale. It will necessitate an architecture simple enough to support modular design and rigorous security analysis, but flexible enough to accommodate current and future functional requirements and use cases. A CBDC will also in some way need to address an innate tension between privacy and transparency, protecting user data from abuse while selectively permitting data mining for end-user services, policymakers, and law enforcement investigations and interventions. In this paper, we enumerate the fundamental technical design challenges facing CBDC designers, with a particular focus on performance, privacy, and security. Through a survey of relevant academic and industry research and deployed systems, we discuss the state of the art in technologies that can address the challenges involved in successful CBDC deployment. We also present a vision of the rich range of functionalities and use cases that a well-designed CBDC platform could ultimately offer users.

AN INTEGRATED THREE-FLOW APPROACH FOR FRONT-END SERVICE COMPOSITION

End-User Service Composition (EUSC) aims to enable end-user programmers who are not professional developers develop applications by composing or aggregating existing web services. Despite the effort, studies have shown that, end-user programmers are not able to deal with the technical complexities involved in EUSC. One way to deal with this issue is Front-End Service Composition (FESC), which allows end-user programmers to compose web services at the presentation layer of an application by configuring user interface (UI) widgets that represent the back-end web services. However, there are not many studies on FESC and the existing ones suffer two main problems, namely, lack of control flow and/or application flow visualization, and they still require end-user programmers to have certain technical knowledge in the service composition process that these end-user programmers generally do not possess. Following that, this study proposes an integrated three-flow approach (application flow, control flow and data flow) to deal with the current limitations of FESC. The approach generates the GUI of web services automatically, thus allowing the UI of the application to be developed at the same time the required web services are assembled. The approach allows end-user programmers to explicitly configure the three different types of flows involved in service composition. A proof-of-concept prototype, QuickWSC, that incorporates the three-flow approach was developed. It adopts a side-by-side multiple-view design to support visual configuration of the three flows in an uncluttered yet synchronized manner that adhered to established design guidelines. A user evaluation study was conducted on QuickWSC. The results show that it is easy to compose web services by explicitly specifying the three flows, that the configurations of the three flows integrated in the two views helps in composing application from web services, and that no technical knowledge is required to use QuickWSC

Energy-Efficient Heterogeneous Multi-Processor Environment in Cloud using Modern Artificial BEE Colony

Cloud Computing is an expansion in distributed, parallel as well as grid computing. The purpose behind cloud computing is the provision of dynamic hiring of server proficiencies as a virtualized and accessible service for customers and end-users. A key issue found in the cloud is the management of resources. Load balancing is a key problem in the management of resources. The job scheduling issue has charmed abundant courtesy in the field of operation research. There are various algorithms like Ant optimization, genetic algorithms, artificial bee colony which can be used to solve the problem of scheduling. No doubt, Parallelization is proved to be the best method that can be utilized for improving the concert of the above algorithms. In this article, a modified artificial bee colony is utilized in order to crack the problem of scheduling in a heterogeneous multi-processor environment. In this, ABC has various colonies located on dissimilar network hosts as well as the algorithm is accepted in several colonies in parallel fashion. The colonies communicate with each other, which is approved through exchanging immigrants. In order to determine the communication of colonies with neighbors, a dynamic strategy is followed up. The algorithm is useful in making the parallel environment more efficient by reducing energy consumption. The energy consumption is reduced for each job in the DAG. Scheduling with MABC in the heterogeneous environment becomes easy as well as effective

Synthesis of derivatives of complex signals based on nonlinear discrete sequences with improved correlation properties

The structure of modern information and communication systems (ICS) is characterized by considerable spatial diversity of a large number of interacting subscribers. In these conditions, technologies of processing, storage, protection, transmission and reception of information on the network under conditions of natural and artificial interferences (impacts), as well as limited frequency and energy resources of ICS play an extremely important role in ensuring the quality of service of end users. ICS, especially for critical applications, are increasingly demanding to ensure the effectiveness of their functioning (speed of information transmission, electromagnetic compatibility, noise immunity, information security, survivability, secrecy, information security). The ability to implement these requirements is largely disregarded by applicable information technology. There is a contradiction between the strict requirements for secrecy, confidentiality, integrity, authenticity of data stored and transmitted through communication lines, on the one hand, and existing models, methods and technologies for managing telecommunications networks, information security, services and quality of service, on the other hand. The main ways to resolve this contradiction is to increase the noise immunity, secrecy and information security of ICS based on the improvement of methodological bases for the construction of ICS by developing methods of information exchange, methods of synthesis of signals of physical data carriers with the necessary properties. The principles of construction of derivative signal systems are given. The requirements for output and source signals are defined. The justification of the possibility of using random (pseudorandom) processes for the production of signals is used to construct them. The results of studies of ensemble, correlation, and structural properties of the obtained systems of derivative signals are presented. It is shown that the use of this class of complex nonlinear discrete signals in modern ICS will improve such performance indicators of such systems as noise immunity, information and structural stealth.

Real‐time BDS signal‐in‐space anomaly detection method considering receiver anomalies

Signal-in-space user range error (SIS URE) can reach tens of meters or even tens of thousands of meters, and this may introduce hazardous misleading information (HMI) to real-time navigation and positioning. Monitoring of real-time SIS anomalies could improve the reliability of navigation and location services for end-users. For BeiDou satellites, the user range accuracy (URA) index currently broadcasted by navigation ephemeris does not reflect the true variation of URE. The anomaly detection method employed uses priori information from precise ephemerides, remains difficult for real-time detection. Additionally, the existing SIS anomalies detection method for BeiDou satellites does not exclude the influence of receiver anomalies. To address these problems, a method for calculating the instantaneous URE (IURE) was developed, and the empirical threshold was obtained by statistically analysing IURE before detecting SIS anomalies. Data of 14 stations from the Multi-GNSS Experiment (MGEX) and the international GNSS Monitoring & Assessment System (iGMAS) in the Asia-Pacific region were selected for detecting anomalies. Results were analysed in combination with the broadcast ephemeris health status indicator and the precise ephemeris detection results to verify the effectiveness of the method. It shows that the proposed method can accurately detect the starting and ending times of SIS anomalies.

Assessment of Adaptive Polling Contention Resolution for Optical Switching in Edge Data Center Networking

Edge Data Center (EDC) provides delay-sensitive services for end-users in edge computing. In Edge Data Center Network (EDCN), fast optical switching is the most promising technology due to low latency, high bandwidth, and transparency of rate/modulation format. However, packets contention of optical switching causes optical packets loss leading to low throughput and high latency. For buffer-less optical switches, it is challenging to solve packets contention because of lack of backup resources for contended packets. In this article, we propose a contention resolution, Adaptive Polling Contention Resolution (APCR), and assess the throughput, latency, and packet loss performance in DCN. An experimental demonstration based on flow control is implemented to test different contention resolution for the admissible load. The APCR algorithm can be adaptive to different load by buffer occupation status. APCR employs hybrid polling scheme to improve throughput and decrease average latency by global desynchronizing in high load. We assess the proposed algorithm performance in intra-cluster and inter-cluster EDCN. The results show that the proposed APCR can increase throughput by more than 15% and reduce the contention count by 43.72% at 0.4 loads.

Analysis of a Distance-Based Pairing Scheme for Collaborative Content Distribution via Device-to-Device Communications

With the increasing penetration of smart devices, device-to-device (D2D) communications offer a promising paradigm to accommodate the ever-growing mobile video traffic and unremitting demands for fast content distribution. The redundant storage and communication capacities of smart devices can be exploited for collaborative content caching and distribution. Such united resources at the network edge can serve end users with low delivery cost and high performance. In this paper, we analyze a heuristic distance-based scheme, which appropriately pairs a device requesting a content item with a cache device within a collaboration distance and providing the requested content. An analytical framework is developed to derive the optimal collaboration distance so as to maximize the likelihood that the paired cache devices successfully fulfill the content requests. The simulation results validate the analytical framework and the effectiveness of the heuristic distance-based scheme for D2D-assisted content distribution. We also investigate the effects of various system parameters on the performance in terms of expected satisfaction probability.

The Implementation of Wakalah Contract by Multifinance Companies in Indonesia

The purpose of this paper is to discuss Wakalah contract which is one of the Islamic banking contracts. Therefore, our main study is the implementation of Wakalah in Indonesia. Wakalah in Indonesia has special reference which is Multifinance company (MFC). MFC is an entity of non-bank financial institution conducts business activities to finance goods or services.Therefore, this research is going to discuss how Wakalah is practiced in Indonesia, where Islamic banks appoint MFC as an agent to do service for end user “customer” on behalf of the bank. Consequently, the objective of this paper is to discuss the implementation of Wakalah with Mudharabah and Wakalah with Murabahah by MFC in Indonesia in terms of operation, the potential risks that might be occur and shariah issues in terms of ownership and fee. However, there are particular areas in terms of operation that MFC should improve, as well as, banks have to be aware of its operational way of conducting agreement so banks mitigate any kind of risks or negligence.

Two Time-Scale Edge Caching and BS Association for Power-Delay Tradeoff in Multi-Cell Networks

More network operators have recently provided content delivery network (CDN) services, where traffic engineering techniques, such as the base station (BS) association, are jointly employed with content delivery. This deployment attempts to reduce the network operating cost and enhance the quality of service (QoS) of end users. Toward this end, we study the BS association and file caching problem considering the spatial diversity of the file popularity and the realistic time-scale separation between the file caching and the BS association decisions in this paper. Our design aims to minimize the file delivery latency and operating power consumption in the cellular networks, where the tradeoff between these conflicting objectives is controlled by a single parameter. The short time-scale BS association problem is solved by using the convex optimization technique for a given file caching solution. However, the long time-scale file caching problem considering the varying BS association decisions taken at the short time-scale is difficult to tackle. To solve this file caching problem, we prove and leverage the submodularity property of the underlying objective function to develop a greedy content caching algorithm that guarantees a constant approximation ratio of the optimal objective value. Via simulations using real-world datasets, we show that the proposed algorithms outperform file caching and BS association algorithms that do not consider the spatial diversity of the file popularity in terms of the power consumption and delay performance in the geographically heterogeneous file popularity scenario.

Data Security Model using Artificial Neural Networks and Database Fragmentation in Cloud Environment

Data security is a one of the challenging issue in present scenario. In that one of the on demand service is cloud computing and it provides so many services for end users and also it provides a dynamic environment for end user to provide quality of services on data it leads to improve in the confidentiality of the data. The proposed work presents a new cloud data security model with the help of Artificial Neural Network. It improves the confidentiality and security in cloud environment. This proposed algorithm is implemented using dynamic hashing fragmented component. It is implemented for storing fragmented sensitive secret data. The neural network cryptographic proposed algorithm is used for data to deal with encryption process for secret and improve the confidentiality. This algorithm applied for various number of cloud databases and it shows high confidentiality on data security.

User Studies on End-User Service Composition

Context: End-user service composition (EUSC) is a service-oriented paradigm that aims to empower end users and allow them to compose their own web applications from reusable service components. User studies have been used to evaluate EUSC tools and processes. Such an approach should benefit software development, because incorporating end users’ feedback into software development should make software more useful and usable. Problem: There is a gap in our understanding of what constitutes a user study and how a good user study should be designed, conducted, and reported. Goal: This article aims to address this gap. Method: The article presents a systematic review of 47 selected user studies for EUSC. Guided by a review framework, the article systematically and consistently assesses the focus, methodology and cohesion of each of these studies. Results: The article concludes that the focus of these studies is clear, but their methodology is incomplete and inadequate, their overall cohesion is poor. The findings lead to the development of a design framework and a set of questions for the design, reporting, and review of good user studies for EUSC. The detailed analysis and the insights obtained from the analysis should be applicable to the design of user studies for service-oriented systems as well and indeed for any user studies related to software artifacts.