Optimal collaboration of thin–thick clients and resource allocation in cloud computing

Architecting cloud‐enabled systems: a systematic survey of challenges and solutions

“…Mobile devices also have a capability estimation module that analyzes capability of the devices for the tasks and sends information to the control device. Hung et al [PS45] present a broker-centric architecture for data distribution and collaboration between thick servers and thin mobile clients according to quality of service (QoS) parameters. Benharref and Serhani [PS6] present an architecture for collection and analysis of chronic diseases data that is collected from wearable mobile devices and processes on the cloud.…”

An Adaptive Procedure for Task Scheduling Optimization in Mobile Cloud Computing

“…In the second layer, there is a thick client functioning as a centralized management node, also known as a broker, which (1) receives all computation requests of users, (2) manages processor's profiles (processing capacity, network bandwidth) as well as computation costs together with results of data query returned from processors, and (3) accordingly creates the most reasonable schedule for an input workflow. In particular, it sends data to clouds in a single connection but when VMs send data to cloud customer layer, the data will be divided into different parts with different sizes before being delivered to thick clients in multiconnections according to a previous research [8]. Moreover, the system has to satisfy the following requirements:…”

“…Meanwhile, gaining more and more popularity in recent years, cloud computing (CC) [4,5], widely known as the next generation's computing infrastructure with virtual unlimited resource and service provision, offered a considerable complement to mobile thin clients such as smartphones, tablets, or even the Google cutting-edge invention, Google Glass [6], and Apple's iWatch [7] by expanding their power and extending the capability of mobile computing. This integration results in a new paradigm named mobile cloud computing, allowing mobile devices to run computation-intensive applications, providing end users with rich computing experience [8]. However, it is still insufficient and vulnerable to inherent obstacles of thin devices: unstable accessibility, low network connectivity, especially the weak processing capacity.…”

“…For example, it would be really costly to process workflow by using solely cloud resources, for which users are charged based on the number of virtual machine (VM) instances and on hours of usage [13][14][15]. Thus, it is understandably suggested that thin clients be coupled with thick clients to achieve a desirable access to cloud, as stated in [8], as well as optimizing the cloud cost.…”

“…However, task scheduling is still one of the main issues in [8], which may negatively affect the performance, QoS, and user experience. Consequently, in this paper, the crucial technical contribution, based on the idea in [8], is to introduce an enhanced solution with a novel genetic algorithm in order to exploit the collaboration between thin-thick clients and cloud network to optimize task scheduling of the processing system so as to deal with the above issues, accordingly improving QoS, user experience, and reliable performance of the system. In particular, our proposal takes into account not only the network contention but also the cost charged to cloud customers (CCs) since these two factors play important roles in satisfying user's expectations [16].…”