Privacy-aware cloud service composition based on QoS optimization in Internet of Things

Author(s):  
Parvaneh Asghari ◽  
Amir Masoud Rahmani ◽  
Hamid Haj Seyyed Javadi
IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 56737-56749 ◽  
Author(s):  
Heba Kurdi ◽  
Fadwa Ezzat ◽  
Lina Altoaimy ◽  
Syed Hassan Ahmed ◽  
Kamal Youcef-Toumi

2017 ◽  
Vol 8 (2) ◽  
pp. 142 ◽  
Author(s):  
Fabrizio Messina ◽  
Giuseppe Pappalardo ◽  
Antonello Comi ◽  
Lidia Fotia ◽  
Domenico Rosaci ◽  
...  

Author(s):  
Phillip Kendrick ◽  
Thar Baker ◽  
Zakaria Maamar ◽  
Abir Hussain ◽  
Rajkumar Buyya ◽  
...  

Author(s):  
Vivek Gaur ◽  
Praveen Dhyani ◽  
Om Prakash Rishi

Recent computing world has seen rapid growth of the number of middle and large scale enterprises that deploy business processes sharing variety of services available over cloud environment. Due to the advantage of reduced cost and increased availability, the cloud technology has been gaining unbound popularity. However, because of existence of multiple cloud service providers on one hand and varying user requirements on the other hand, the task of appropriate service composition becomes challenging. The conception of this chapter is to consider the fact that different quality parameters related to various services might bear varied importance for different user. This chapter introduces a framework for QoS-based Cloud service selection to satisfy the end user needs. A hybrid algorithm based on genetic algorithm (GA) and Tabu Search methods has been developed, and its efficacy is analysed. Finally, this chapter includes the experimental analysis to present the performance of the algorithm.


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