scholarly journals Decoupling the control plane from program control flow for flexibility and performance in cloud computing

2018 ◽  
Author(s):  
Hang Qu ◽  
Omid Mashayekhi ◽  
Chinmayee Shah ◽  
Philip Levis
Keyword(s):  
Cloud Computing ◽  
Control Flow ◽  
Program Control ◽  
Control Plane ◽  
And Performance

scholarly journals Insights from Learning Analytics for Hands-On Cloud Computing Labs in AWS

2020 ◽  
Vol 10 (24) ◽  
pp. 9148
Author(s):  
Germán Moltó ◽  
Diana M. Naranjo ◽  
J. Damian Segrelles
Keyword(s):  
Cloud Computing ◽  
Learning Analytics ◽  
Cloud Provider ◽  
Online Students ◽  
Computing Services ◽  
Hands On ◽  
Data Processing Tool ◽  
Amazon Web Services ◽  
Course Length ◽  
And Performance

Cloud computing instruction requires hands-on experience with a myriad of distributed computing services from a public cloud provider. Tracking the progress of the students, especially for online courses, requires one to automatically gather evidence and produce learning analytics in order to further determine the behavior and performance of students. With this aim, this paper describes the experience from an online course in cloud computing with Amazon Web Services on the creation of an open-source data processing tool to systematically obtain learning analytics related to the hands-on activities carried out throughout the course. These data, combined with the data obtained from the learning management system, have allowed the better characterization of the behavior of students in the course. Insights from a population of more than 420 online students through three academic years have been assessed, the dataset has been released for increased reproducibility. The results corroborate that course length has an impact on online students dropout. In addition, a gender analysis pointed out that there are no statistically significant differences in the final marks between genders, but women show an increased degree of commitment with the activities planned in the course.

scholarly journals A Fast Optimization Method for Reliability and Performance of Cloud Services Composition Application

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Zhao Wu ◽  
Naixue Xiong ◽  
Yannong Huang ◽  
Qiong Gu ◽  
Chunyang Hu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
State Space ◽  
Generating Function ◽  
Performance Optimization ◽  
Optimization Method ◽  
Cloud Services ◽  
Services Composition ◽  
Fast Optimization ◽  
And Performance ◽  
Universal Generating Function

At present the cloud computing is one of the newest trends of distributed computation, which is propelling another important revolution of software industry. The cloud services composition is one of the key techniques in software development. The optimization for reliability and performance of cloud services composition application, which is a typical stochastic optimization problem, is confronted with severe challenges due to its randomness and long transaction, as well as the characteristics of the cloud computing resources such as openness and dynamic. The traditional reliability and performance optimization techniques, for example, Markov model and state space analysis and so forth, have some defects such as being too time consuming and easy to cause state space explosion and unsatisfied the assumptions of component execution independence. To overcome these defects, we propose a fast optimization method for reliability and performance of cloud services composition application based on universal generating function and genetic algorithm in this paper. At first, a reliability and performance model for cloud service composition application based on the multiple state system theory is presented. Then the reliability and performance definition based on universal generating function is proposed. Based on this, a fast reliability and performance optimization algorithm is presented. In the end, the illustrative examples are given.

AN EFFECTIVE CONTROL FLOW CHECKING METHOD FOR MULTITASK PROCESSING IN HARSH ENVIRONMENTS

2013 ◽  
Vol 22 (08) ◽  
pp. 1350067 ◽  
Author(s):  
SEYYED AMIR ASGHARI ◽  
ATENA ABDI ◽  
OKYAY KAYNAK ◽  
HASSAN TAHERI ◽  
HOSSEIN PEDRAM
Keyword(s):  
Error Detection ◽  
Optimal Solution ◽  
Control Flow ◽  
Simultaneous Optimization ◽  
Harsh Environments ◽  
Effective Control ◽  
Power Performance ◽  
Single Event Upsets ◽  
Novel Method ◽  
And Performance

Electronic equipment used in harsh environments such as space has to cope with many threats. One major threat is the intensive radiation which gives rise to Single Event Upsets (SEU) that lead to control flow errors and data errors. In the design of embedded systems to be used in space, the use of radiation tolerant equipment may therefore be a necessity. However, even if the higher cost of such a choice is not a problem, the efficiency of such equipment is lower than the COTS equipment. Therefore, the use of COTS with appropriate measures to handle the threats may be the optimal solution, in which a simultaneous optimization is carried out for power, performance, reliability and cost. In this paper, a novel method is presented for control flow error detection in multitask environments with less memory and performance overheads as compared to other methods seen in the literature.

scholarly journals Adjacency-Hash-Table Based Public Auditing for Data Integrity in Mobile Cloud Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Wenqi Chen ◽  
Hui Tian ◽  
Chin-Chen Chang ◽  
Fulin Nan ◽  
Jing Lu
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Security Analysis ◽  
Hash Table ◽  
The State ◽  
Public Auditing ◽  
The Arts ◽  
High Speed Data ◽  
And Performance ◽  
Data Updating

Cloud storage, one of the core services of cloud computing, provides an effective way to solve the problems of storage and management caused by high-speed data growth. Thus, a growing number of organizations and individuals tend to store their data in the cloud. However, due to the separation of data ownership and management, it is difficult for users to check the integrity of data in the traditional way. Therefore, many researchers focus on developing several protocols, which can remotely check the integrity of data in the cloud. In this paper, we propose a novel public auditing protocol based on the adjacency-hash table, where dynamic auditing and data updating are more efficient than those of the state of the arts. Moreover, with such an authentication structure, computation and communication costs can be reduced effectively. The security analysis and performance evaluation based on comprehensive experiments demonstrate that our protocol can achieve all the desired properties and outperform the state-of-the-art ones in computing overheads for updating and verification.

Compensation and Convergence — Comparing and Combining Deployment Automation Approaches

2015 ◽  
Vol 24 (03) ◽  
pp. 1541001 ◽  
Author(s):  
Johannes Wettinger ◽  
Uwe Breitenbücher ◽  
Frank Leymann
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Configuration Management ◽  
Fine Grained ◽  
Design Time ◽  
Major Class ◽  
Continuous Delivery ◽  
And Performance

Leading paradigms to develop, deploy, and operate applications such as continuous delivery, configuration management, and the merge of development and operations (DevOps) are the foundation for various techniques and tools to implement automated deployment. To make such applications available for users and customers, these approaches are typically used in conjunction with Cloud computing to automatically provision and manage underlying resources such as storage and virtual servers. A major class of these automation approaches follow the idea of converging toward a desired state of a resource (e.g. a middleware component deployed on a virtual machine). This is achieved by repeatedly executing idempotent scripts to reach the desired state. Because of major drawbacks of this approach, we discuss an alternative deployment automation approach based on compensation and fine-grained snapshots using container virtualization. We perform an evaluation comparing both approaches in terms of difficulties at design time and performance at runtime. Moreover, we discuss concepts, strategies, and implementations to effectively combine different deployment automation approaches.

scholarly journals Cloud Computing based on the Load Balancing Algorithm

2018 ◽  
Vol 7 (4.7) ◽  
pp. 131
Author(s):  
NV Abhinav Chand ◽  
A Hemanth Kumar ◽  
Surya Teja Marella
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
User Satisfaction ◽  
Easy Access ◽  
Future Research ◽  
Computing Technology ◽  
Main Challenge ◽  
Load Balancing Algorithm ◽  
And Performance ◽  
Time Resource

Emerging cloud computing technology is a big step in virtual computing. Cloud computing provides services to clients through the internet. Cloud computing enables easy access to resources distributed all over the world. Increase in the number of the population has further increased the challenge. The main challenge of cloud computing technology is to achieve efficient load balancing. Load balancing is a process of assigning load to available resources in such a way that it avoids overloading of resources. If load balancing is performed efficiently, it improves QoS metric including cost, throughput, response time, resource utilization and performance. Efficient load balancing techniques also provide better user satisfaction. Various load balancing algorithms are used in different scenarios for ensuring the same. In the current research, we will study different algorithms for load balancing and benefits and limitations caused to the system due to the algorithms. In this paper, we will compare static and dynamic load balancing algorithms for various measures of efficiency. These will be useful for future research in the concerned field. 

scholarly journals Reconciling optimization with secure compilation

2021 ◽  
Vol 5 (OOPSLA) ◽  
pp. 1-30
Author(s):  
Son Tuan Vu ◽  
Albert Cohen ◽  
Arnaud De Grandmaison ◽  
Christophe Guillon ◽  
Karine Heydemann
Keyword(s):  
Side Effects ◽  
Control Flow ◽  
Partial Ordering ◽  
Input Output ◽  
Machine Code ◽  
Fine Grained ◽  
Control Flow Integrity ◽  
Correct Execution ◽  
Source Level ◽  
And Performance

Software protections against side-channel and physical attacks are essential to the development of secure applications. Such protections are meaningful at machine code or micro-architectural level, but they typically do not carry observable semantics at source level. This renders them susceptible to miscompilation, and security engineers embed input/output side-effects to prevent optimizing compilers from altering them. Yet these side-effects are error-prone and compiler-dependent. The current practice involves analyzing the generated machine code to make sure security or privacy properties are still enforced. These side-effects may also be too expensive in fine-grained protections such as control-flow integrity. We introduce observations of the program state that are intrinsic to the correct execution of security protections, along with means to specify and preserve observations across the compilation flow. Such observations complement the input/output semantics-preservation contract of compilers. We introduce an opacification mechanism to preserve and enforce a partial ordering of observations. This approach is compatible with a production compiler and does not incur any modification to its optimization passes. We validate the effectiveness and performance of our approach on a range of benchmarks, expressing the secure compilation of these applications in terms of observations to be made at specific program points.

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