◾ Resource Optimization for Multimedia Cloud Computing

2014 ◽  
pp. 43-68 ◽  
Keyword(s):  
Cloud Computing ◽  
Resource Optimization ◽  
Multimedia Cloud

Resource Optimization for Multimedia Cloud Computing

2014 ◽  
pp. 21-46
Author(s):  
Xiaoming Nan ◽  
Yifeng He ◽  
Ling Guan
Keyword(s):  
Cloud Computing ◽  
Resource Optimization ◽  
Multimedia Cloud

scholarly journals An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing

Sensors ◽  
2016 ◽  
Vol 16 (2) ◽  
pp. 246 ◽  
Author(s):  
Guangjie Han ◽  
Wenhui Que ◽  
Gangyong Jia ◽  
Lei Shu
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Multimedia Cloud ◽  
Virtual Machine Consolidation

scholarly journals Taxonomy and issues for antifragile-based multimedia cloud computing

2016 ◽  
Vol 2 (1) ◽  
pp. 37-49 ◽  
Author(s):  
Syed Fawad Haider ◽  
Laraib Abbas ◽  
Amjad Ali ◽  
Muddesar Iqbal ◽  
Imran Raza ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Multimedia Cloud

scholarly journals Ciphertext-Policy Attribute-Based Encryption with Outsourced Set Intersection in Multimedia Cloud Computing

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2685
Author(s):  
Yanfeng Shi ◽  
Shuo Qiu
Keyword(s):  
Cloud Computing ◽  
Computing System ◽  
Access Structure ◽  
Policy Model ◽  
Multimedia Cloud ◽  
Cryptographic Algorithm ◽  
Attribute Based Encryption ◽  
Set Intersection ◽  
Cloud Computing System ◽  
Ciphertext Policy

In a multimedia cloud computing system, suppose all cloud users outsource their own data sets to the cloud in the encrypted form. Each outsourced set is associated with an access structure such that a valid data user, Bob, with the credentials satisfying the access structure is able to conduct computing over outsourced encrypted set (e.g., decryption or other kinds of computing function). Suppose Bob needs to compute the set intersection over a data owner Alice’s and his own outsourced encrypted sets. Bob’s simple solution is to download Alice’s and Bob’s outsourced encrypted sets, perform set intersection operation, and decrypt the set intersection ciphertexts. A better solution is for Bob to delegate the cloud to calculate the set intersection, without giving the cloud any ability in breaching the secrecy of the sets. To solve this problem, this work introduces a novel primitive called ciphertext-policy attribute-based encryption with outsourced set intersection for multimedia cloud computing. It is the first cryptographic algorithm supporting a fully outsourced encrypted storage, computation delegation, fine-grained authorization security for ciphertext-policy model, without relying on an online trusted authority or data owners, and multi-elements set, simultaneously. We construct a scheme that provably satisfies the desirable security properties, and analyze its efficiency.

scholarly journals Fog Computing Resource Optimization: A Review on Current Scenarios and Resource Management

2019 ◽  
Vol 16 (2) ◽  
pp. 0419 ◽  
Author(s):  
Dar Et al.
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Fog Computing ◽  
Energy Resource ◽  
Optimization Methods ◽  
Resource Optimization ◽  
Data Generation ◽  
Computing Paradigm ◽  
Processing Power ◽  
Huge Data

            The unpredictable and huge data generation nowadays by smart computing devices like (Sensors, Actuators, Wi-Fi routers), to handle and maintain their computational processing power in real time environment by centralized cloud platform is difficult because of its limitations, issues and challenges, to overcome these, Cisco introduced the Fog computing paradigm as an alternative for cloud-based computing. This recent IT trend is taking the computing experience to the next level. It is an extended and advantageous extension of the centralized cloud computing technology. In this article, we tried to highlight the various issues that currently cloud computing is facing. Here in this research article, we present a comprehensive review of fog computing, differentiating it from cloud computing, also present various use-cases of fog computing in different domains, we came to conclude that Fog computing leads in an efficient energy resource management, leveraging the energy both in terms of consumption and cost scenarios. Further, we highlighted its key features, challenges and issues, resource optimization methods.

Enhanced Load Balancing Approach for Cloud Data Center Load Optimization

2021 ◽  
Vol 18 (4) ◽  
pp. 1270-1274
Author(s):  
J. Prassanna ◽  
V. Neelanarayanan
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Center ◽  
Resource Control ◽  
Resource Optimization ◽  
Computing Technology ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Load Optimization ◽  
Related Data

Cloud computing is a most popular technology that has huge response in markets. Cloud computing has the potential to access applications and their related data via the Internet anywhere. Most companies already pay for the use of cloud resources for storage purposes and ultimately reduce the costs of infrastructure spending. They can make use of this technology for accessing to company applications like pay-as-you-go approach. One of the major obstacles associated with cloud computing technology is to better optimization of resource allocation. Assigning of workloads to the servers using load balancing techniques is used to achieve less response time and better resource optimization across the server. Resource control and balance of load are the major conflicts in the cloud environment, which is why there are different load balancing algorithms, each with its own advantages and disadvantage. In order to achieve a better economy and mutual benefit, efficient algorithms can be derived simultaneously by optimizing servers, green computing and better utilization of resources. The objective of this paper is to analyze and enhance existing load balancing algorithms.

Sign in / Sign up

Export Citation Format

Share Document