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2022 ◽  
Vol 54 (7) ◽  
pp. 1-35
Author(s):  
Uttam Chauhan ◽  
Apurva Shah

We are not able to deal with a mammoth text corpus without summarizing them into a relatively small subset. A computational tool is extremely needed to understand such a gigantic pool of text. Probabilistic Topic Modeling discovers and explains the enormous collection of documents by reducing them in a topical subspace. In this work, we study the background and advancement of topic modeling techniques. We first introduce the preliminaries of the topic modeling techniques and review its extensions and variations, such as topic modeling over various domains, hierarchical topic modeling, word embedded topic models, and topic models in multilingual perspectives. Besides, the research work for topic modeling in a distributed environment, topic visualization approaches also have been explored. We also covered the implementation and evaluation techniques for topic models in brief. Comparison matrices have been shown over the experimental results of the various categories of topic modeling. Diverse technical challenges and future directions have been discussed.


Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2394
Author(s):  
Teo Poh Kuang ◽  
Hamidah Ibrahim ◽  
Fatimah Sidi ◽  
Nur Izura Udzir ◽  
Ali A. Alwan

Policy evaluation is a process to determine whether a request submitted by a user satisfies the access control policies defined by an organization. Naming heterogeneity between the attribute values of a request and a policy is common due to syntactic variations and terminological variations, particularly among organizations of a distributed environment. Existing policy evaluation engines employ a simple string equal matching function in evaluating the similarity between the attribute values of a request and a policy, which are inaccurate, since only exact match is considered similar. This work proposes several matching functions which are not limited to the string equal matching function that aim to resolve various types of naming heterogeneity. Our proposed solution is also capable of supporting symmetrical architecture applications, in which the organization can negotiate with the users for the release of their resources and properties that raise privacy concerns. The effectiveness of the proposed matching functions on real XACML policies, designed for universities, conference management, and the health care domain, is evaluated. The results show that the proposed solution has successfully achieved higher percentages of Recall and F-measure compared with the standard Sun’s XACML implementation, with our improvement, these measures gained up to 70% and 57%, respectively.


2021 ◽  
pp. 293-303
Author(s):  
Duc Thuan Le ◽  
Van Huong Pham ◽  
Van Hiep Hoang ◽  
Kim Khanh Nguyen

2021 ◽  
Author(s):  
Gabriele Ribeiro ◽  
Joberto S. B. Martins

Medical applications are increasingly using computing resources such as IoT sensors and network communications paradigms. An e-Health application requires a basic set of elements such as sensors, a communication framework, and a network structure adapted to the application's specific requirements. This work expands and develops a framework based on the Publish / Subscribe paradigm to develop PSIoT-Health. The PSIoT-Health framework focuses on medical applications that collect data produced in a distributed manner. The PSIoT-Health adapts the Pub/Sub model to the requirements of medical applications and proposes a solution for the production and consumption of data between producers and consumers of medical data in a distributed environment such as the one existing in a smart city.


Author(s):  
Shubh Goyal

Abstract: By utilizing the Hadoop environment, data may be loaded and searched from local data nodes. Because the dataset's capacity may be vast, loading and finding data using a query is often more difficult. We suggest a method for dealing with data in local nodes that does not overlap with data acquired by script. The query's major purpose is to store information in a distributed environment and look for it quickly. In this section, we define the script to eliminate duplicate data redundancy when searching and loading data in a dynamic manner. In addition, the Hadoop file system is available in a distributed environment. Keywords: HDFS; Hadoop distributed file system; replica; local; distributed; capacity; SQL; redundancy


2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Junaid Hassan ◽  
Danish Shehzad ◽  
Insaf Ullah ◽  
Fahad Algarni ◽  
Muhammad Umar Aftab ◽  
...  

Cloud computing aims to provide reliable, customized, and quality of service (QoS) guaranteed dynamic computing environments for end-users. However, there are applications such as e-health and emergency response monitoring that require quick response and low latency. Delays caused by transferring data over the cloud can seriously affect the performance and reliability of real-time applications. Before outsourcing e-health care data to the cloud, the user needs to perform encryption on these sensitive data to ensure its confidentiality. Conventionally, any modification to the user data requires encrypting the entire data and calculating the hash of the data from scratch. This data modification mechanism increases communication and computation costs over the cloud. The distributed environment of fog computing is used to overcome the limitations of cloud computing. This paper proposed a certificate-based incremental proxy re-encryption scheme (CB-PReS) for e-health data sharing in fog computing. The proposed scheme improves the file modification operations, i.e., updation, deletion, and insertion. The proposed scheme is tested on the iFogSim simulator. The iFogSim simulator facilitates the development of models for fog and IoT environments, and it also measures the impact of resource management techniques regarding network congestion and latency. Experiments depict that the proposed scheme is better than the existing schemes based on expensive bilinear pairing and elliptic curve techniques. The proposed scheme shows significant improvement in key generation and file modification time.


2021 ◽  
Author(s):  
◽  
Kyle Chard

<p>The computational landscape is littered with islands of disjoint resource providers including commercial Clouds, private Clouds, national Grids, institutional Grids, clusters, and data centers. These providers are independent and isolated due to a lack of communication and coordination, they are also often proprietary without standardised interfaces, protocols, or execution environments. The lack of standardisation and global transparency has the effect of binding consumers to individual providers. With the increasing ubiquity of computation providers there is an opportunity to create federated architectures that span both Grid and Cloud computing providers effectively creating a global computing infrastructure. In order to realise this vision, secure and scalable mechanisms to coordinate resource access are required. This thesis proposes a generic meta-scheduling architecture to facilitate federated resource allocation in which users can provision resources from a range of heterogeneous (service) providers. Efficient resource allocation is difficult in large scale distributed environments due to the inherent lack of centralised control. In a Grid model, local resource managers govern access to a pool of resources within a single administrative domain but have only a local view of the Grid and are unable to collaborate when allocating jobs. Meta-schedulers act at a higher level able to submit jobs to multiple resource managers, however they are most often deployed on a per-client basis and are therefore concerned with only their allocations, essentially competing against one another. In a federated environment the widespread adoption of utility computing models seen in commercial Cloud providers has re-motivated the need for economically aware meta-schedulers. Economies provide a way to represent the different goals and strategies that exist in a competitive distributed environment. The use of economic allocation principles effectively creates an open service market that provides efficient allocation and incentives for participation. The major contributions of this thesis are the architecture and prototype implementation of the DRIVE meta-scheduler. DRIVE is a Virtual Organisation (VO) based distributed economic metascheduler in which members of the VO collaboratively allocate services or resources. Providers joining the VO contribute obligation services to the VO. These contributed services are in effect membership “dues” and are used in the running of the VOs operations – for example allocation, advertising, and general management. DRIVE is independent from a particular class of provider (Service, Grid, or Cloud) or specific economic protocol. This independence enables allocation in federated environments composed of heterogeneous providers in vastly different scenarios. Protocol independence facilitates the use of arbitrary protocols based on specific requirements and infrastructural availability. For instance, within a single organisation where internal trust exists, users can achieve maximum allocation performance by choosing a simple economic protocol. In a global utility Grid no such trust exists. The same meta-scheduler architecture can be used with a secure protocol which ensures the allocation is carried out fairly in the absence of trust. DRIVE establishes contracts between participants as the result of allocation. A contract describes individual requirements and obligations of each party. A unique two stage contract negotiation protocol is used to minimise the effect of allocation latency. In addition due to the co-op nature of the architecture and the use of secure privacy preserving protocols, DRIVE can be deployed in a distributed environment without requiring large scale dedicated resources. This thesis presents several other contributions related to meta-scheduling and open service markets. To overcome the perceived performance limitations of economic systems four high utilisation strategies have been developed and evaluated. Each strategy is shown to improve occupancy, utilisation and profit using synthetic workloads based on a production Grid trace. The gRAVI service wrapping toolkit is presented to address the difficulty web enabling existing applications. The gRAVI toolkit has been extended for this thesis such that it creates economically aware (DRIVE-enabled) services that can be transparently traded in a DRIVE market without requiring developer input. The final contribution of this thesis is the definition and architecture of a Social Cloud – a dynamic Cloud computing infrastructure composed of virtualised resources contributed by members of a Social network. The Social Cloud prototype is based on DRIVE and highlights the ease in which dynamic DRIVE markets can be created and used in different domains.</p>


2021 ◽  
Author(s):  
◽  
Kyle Chard

<p>The computational landscape is littered with islands of disjoint resource providers including commercial Clouds, private Clouds, national Grids, institutional Grids, clusters, and data centers. These providers are independent and isolated due to a lack of communication and coordination, they are also often proprietary without standardised interfaces, protocols, or execution environments. The lack of standardisation and global transparency has the effect of binding consumers to individual providers. With the increasing ubiquity of computation providers there is an opportunity to create federated architectures that span both Grid and Cloud computing providers effectively creating a global computing infrastructure. In order to realise this vision, secure and scalable mechanisms to coordinate resource access are required. This thesis proposes a generic meta-scheduling architecture to facilitate federated resource allocation in which users can provision resources from a range of heterogeneous (service) providers. Efficient resource allocation is difficult in large scale distributed environments due to the inherent lack of centralised control. In a Grid model, local resource managers govern access to a pool of resources within a single administrative domain but have only a local view of the Grid and are unable to collaborate when allocating jobs. Meta-schedulers act at a higher level able to submit jobs to multiple resource managers, however they are most often deployed on a per-client basis and are therefore concerned with only their allocations, essentially competing against one another. In a federated environment the widespread adoption of utility computing models seen in commercial Cloud providers has re-motivated the need for economically aware meta-schedulers. Economies provide a way to represent the different goals and strategies that exist in a competitive distributed environment. The use of economic allocation principles effectively creates an open service market that provides efficient allocation and incentives for participation. The major contributions of this thesis are the architecture and prototype implementation of the DRIVE meta-scheduler. DRIVE is a Virtual Organisation (VO) based distributed economic metascheduler in which members of the VO collaboratively allocate services or resources. Providers joining the VO contribute obligation services to the VO. These contributed services are in effect membership “dues” and are used in the running of the VOs operations – for example allocation, advertising, and general management. DRIVE is independent from a particular class of provider (Service, Grid, or Cloud) or specific economic protocol. This independence enables allocation in federated environments composed of heterogeneous providers in vastly different scenarios. Protocol independence facilitates the use of arbitrary protocols based on specific requirements and infrastructural availability. For instance, within a single organisation where internal trust exists, users can achieve maximum allocation performance by choosing a simple economic protocol. In a global utility Grid no such trust exists. The same meta-scheduler architecture can be used with a secure protocol which ensures the allocation is carried out fairly in the absence of trust. DRIVE establishes contracts between participants as the result of allocation. A contract describes individual requirements and obligations of each party. A unique two stage contract negotiation protocol is used to minimise the effect of allocation latency. In addition due to the co-op nature of the architecture and the use of secure privacy preserving protocols, DRIVE can be deployed in a distributed environment without requiring large scale dedicated resources. This thesis presents several other contributions related to meta-scheduling and open service markets. To overcome the perceived performance limitations of economic systems four high utilisation strategies have been developed and evaluated. Each strategy is shown to improve occupancy, utilisation and profit using synthetic workloads based on a production Grid trace. The gRAVI service wrapping toolkit is presented to address the difficulty web enabling existing applications. The gRAVI toolkit has been extended for this thesis such that it creates economically aware (DRIVE-enabled) services that can be transparently traded in a DRIVE market without requiring developer input. The final contribution of this thesis is the definition and architecture of a Social Cloud – a dynamic Cloud computing infrastructure composed of virtualised resources contributed by members of a Social network. The Social Cloud prototype is based on DRIVE and highlights the ease in which dynamic DRIVE markets can be created and used in different domains.</p>


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