scholarly journals A Deadline Constrained Time-Cost effective Salp Swarm Algorithm for Resource Optimization in Cloud Computing

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Cloud Computing ◽  
Cost Effective ◽  
Bat Algorithm ◽  
Resource Optimization ◽  
Grey Wolf Optimizer ◽  
Time Cost ◽  
Salp Swarm Algorithm ◽  
Swarm Algorithm ◽  
Deadline Constraints

Nowadays, Cloud Computing has become the most attractive platform, which provides anything as a Service (XaaS). Many applications may be developed and run on the cloud without worrying about platforms. It is a big challenge to allocate optimal resources to these applications and satisfy user's quality of service requirements. Here, in this paper, a Deadline Constrained Time-Cost effective Salp Swarm Algorithm (DTC-SSA) is proposed to achieve optimized resource allocation. DTC-SSA assigns the user's task to an appropriate virtual machine (Vm) and achieves a trade-off between cost and makespan while satisfying the deadline constraints. Rigorous examination of the algorithm is conducted on the various scale and cloud resources. The proposed algorithm is compared with Particle Swarm Optimization (PSO), Grey Wolf Optimizer(GWO), Bat Algorithm(BAT), and Genetic Algorithm(GA). Simulation results prove that it outperforms others by minimizing makespan, execution cost, Response time, and improving resource utilization throughput.

Reliability, Fault Tolerance, and Quality-of-Service in Cloud Computing

2015 ◽  
pp. 358-370 ◽  
Author(s):  
Piyush Kumar Shukla ◽  
Gaurav Singh
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Fault Tolerance ◽  
Cost Effective ◽  
Independent Manner ◽  
System Failures ◽  
Computing Paradigm ◽  
Computing Services ◽  
Management Effort

In this chapter we are focusing on reliability, fault tolerance and quality of service in cloud computing. The flexible and scalable property of dynamically fetching and relinquishing computing resources in a cost-effective and device-independent manner with minimal management effort or service provider interaction the demand for Cloud computing paradigm has increased dramatically in last few years. Though lots of enhancement took place, cloud computing paradigm is still subject to a large number of system failures. As a result, there is an increasing concern among community regarding the reliability and availability of Cloud computing services. Dynamically provisioning of resources allows cloud computing environment to meet casually varying resource and service requirements of cloud customer applications. Quality of Service (QoS) plays an important role in the affective allocation of resources and has been widely investigated in the Cloud Computing paradigm.

Current Applications in Health Care Communication and Technology

2021 ◽  
Vol 3 (1) ◽  
Keyword(s):  
Health Care ◽  
Cloud Computing ◽  
Social Networking ◽  
Care Setting ◽  
Online Social Network ◽  
Cost Effective ◽  
Computing Technology ◽  
Health Care Communication ◽  
Communication And Technology

Communication and technology in a health care setting is the most important tool in health promotion. Recently, cloud computing technology is used to enable cost-effective applications to facilitate communication, information sharing and record maintenance regarding health and medicine. It allows dissemination of information from facebook, which is currently the largest online social network. Combining cloud computing and social networking could allow creating health social networking system employing a human –oriented, interactive medical web and this would improve the quality of current applications in health care communication and technology.

scholarly journals Salp Swarm Algorithm for Node Localization in Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Huthaifa M. Kanoosh ◽  
Essam Halim Houssein ◽  
Mazen M. Selim
Keyword(s):  
Computing Time ◽  
Wireless Sensor ◽  
Grey Wolf Optimizer ◽  
Localization Algorithm ◽  
Node Localization ◽  
Localization Accuracy ◽  
Salp Swarm Algorithm ◽  
Localization Scheme ◽  
Swarm Algorithm ◽  
Better Than

Nodes localization in a wireless sensor network (WSN) aims for calculating the coordinates of unknown nodes with the assist of known nodes. The performance of a WSN can be greatly affected by the localization accuracy. In this paper, a node localization scheme is proposed based on a recent bioinspired algorithm called Salp Swarm Algorithm (SSA). The proposed algorithm is compared to well-known optimization algorithms, namely, particle swarm optimization (PSO), Butterfly optimization algorithm (BOA), firefly algorithm (FA), and grey wolf optimizer (GWO) under different WSN deployments. The simulation results show that the proposed localization algorithm is better than the other algorithms in terms of mean localization error, computing time, and the number of localized nodes.

scholarly journals Modified Salp Swarm Algorithm based Energy-Efficient Resource Allocation in Cloud-Computing Data Centers

2019 ◽  
Vol 8 (12) ◽  
pp. 3713-3720
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machines ◽  
Vm Placement ◽  
Cloud Computing Environment ◽  
Cloud Data ◽  
Salp Swarm Algorithm ◽  
Efficient Resource ◽  
Swarm Algorithm ◽  
Energy Efficient Resource Allocation

In a cloud data centre the consolidation of the virtual machines (VMs) assist to optimize the resources need and diminish the energy consumption. In the consolidation of the VMs the VM placement acts an important role. By considering optimized energy consumption the researchers have developed various algorithms for VM placement. However, these algorithms be deficient in the exploitation mechanism use resourcefully. This paper attend to VM placement issues by offering metaheuristic algorithms that is, the Modified Salp Swarm Algorithm (MSSA) presenting the comparative analysis relating to energy optimization. The comparison are made adjacent to the existing particle swarm optimization (PSO), and salp swarm algorithm (SSA) and the energy consumption results of all the contributing algorithms confirm that the proposed MSSA is more efficient than the other algorithms. The simulation result demonstrates that MSSA outperforms effectively than other presented approaches in optimal VM placement in cloud computing environment with maximal resource use, minimal energy consumption, minimum SLA violation and reduced migration cost

Data Integrity Techniques in Cloud Computing: An Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 121 ◽  
Author(s):  
Neha Thakur ◽  
Aman Kumar Sharma
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Data Integrity ◽  
Advantages And Disadvantages ◽  
Security Models ◽  
Cloud Storage Service ◽  
Storage Service ◽  
Cloud Users ◽  
It Enterprises

Cloud computing has been envisioned as the definite and concerning solution to the rising storage costs of IT Enterprises. There are many cloud computing initiatives from IT giants such as Google, Amazon, Microsoft, IBM. Integrity monitoring is essential in cloud storage for the same reasons that data integrity is critical for any data centre. Data integrity is defined as the accuracy and consistency of stored data, in absence of any alteration to the data between two updates of a file or record.  In order to ensure the integrity and availability of data in Cloud and enforce the quality of cloud storage service, efficient methods that enable on-demand data correctness verification on behalf of cloud users have to be designed. To overcome data integrity problem, many techniques are proposed under different systems and security models. This paper will focus on some of the integrity proving techniques in detail along with their advantages and disadvantages.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

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