Privacy and Control in Mobile Cloud Systems

Alwada'n, Tariq; Al-zitawi, Omar; Khawaldeh, Sufian; Almasarweh, Mohammed

doi:10.5120/19789-1170

Cited by 5 publications

(3 citation statements)

References 13 publications

(12 reference statements)

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“…Combining IoT and cloud 4 of 17 networks in the Cloud of Things (CoT) is one of the best ways to overcome almost all the barriers to the IoT [29]. Moreover, the CoT can streamline the processes of IoT data collection, processing, integration, and deployment [2,29]. The creation of new IoT applications is complicated due to the huge number of IoT devices with heterogeneous paradigms [30].…”

Section: Fog Computingmentioning

confidence: 99%

“…Cloud computing is considered as a massive dynamic and distributed resource of storage, services, and computing power available on request to users over the Internet [1,2]. Conventionally, resources in cloud computing are located in a huge data storage center and are managed and controlled by a third party, who offers computing infrastructures for the cloud users to be used by anyone from anywhere via the Internet [3].…”

Section: Introduction 1cloud Computingmentioning

confidence: 99%

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Fog Computing, Cloud Computing and IoT Environment: Advanced Broker Management System

Masarweh

Alwada'n

Afandi

2022

JSAN

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Cloud computing is a massive amount of dynamic ad distributed resources that are delivered on request to clients over the Internet. Typical centralized cloud computing models may have difficulty dealing with challenges caused by IoT applications, such as network failure, latency, and capacity constraints. One of the introduced methods to solve these challenges is fog computing which makes the cloud closer to IoT devices. A system for dynamic congestion management brokerage is presented in this paper. With this proposed system, the IoT quality of service (QoS) requirements as defined by the service-level agreement (SLA) can be met as the massive amount of cloud requests come from the fog broker layer. In addition, a forwarding policy is introduced which helps the cloud service broker to select and forward the high-priority requests to the appropriate cloud resources from fog brokers and cloud users. This proposed idea is influenced by the weighted fair queuing (WFQ) Cisco queuing mechanism to simplify the management and control of the congestion that may possibly take place at the cloud service broker side. The system proposed in this paper is evaluated using iFogSim and CloudSim tools, and the results demonstrate that it improves IoT (QoS) compliance, while also avoiding cloud SLA violations.

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Section: Fog Computingmentioning

confidence: 99%

Section: Introduction 1cloud Computingmentioning

confidence: 99%

Fog Computing, Cloud Computing and IoT Environment: Advanced Broker Management System

Masarweh

Alwada'n

Afandi

2022

JSAN

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“…Cloud computing, cluster computing, and grid computing models are designed to give access to a vast amount of computing power by sharing information technology (IT) resources or services by running a single or a group of system interfaces. Service computing is defined as IT resources (hardware or software) where service providers establish those resources and provide them on demand [1], [2]. Service requesters can pay the service providers on pay-per-use charging mode.…”

Section: Introductionmentioning

confidence: 99%

Dynamic congestion management system for cloud service broker

Alwada'n

Al-Tamimi

Mohammad

et al. 2023

IJECE

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<span lang="EN-US">The cloud computing model offers a shared pool of resources and services with diverse models presented to the clients through the internet by an on-demand scalable and dynamic pay-per-use model. The developers have identified the need for an automated system (cloud service broker (CSB)) that can contribute to exploiting the cloud capability, enhancing its functionality, and improving its performance. This research presents a dynamic congestion management (DCM) system which can manage the massive amount of cloud requests while considering the required quality for the clients’ requirements as regulated by the service-level policy. In addition, this research introduces a forwarding policy that can be utilized to choose high-priority calls coming from the cloud service requesters and passes them by the broker to the suitable cloud resources. The policy has made use of one of the mechanisms that are used by Cisco to assist the administration of the congestion that might take place at the broker side. Furthermore, the DCM system is used to help in provisioning and monitoring the works of the cloud providers through the job operation. The proposed DCM system was implemented and evaluated by using the CloudSim tool.</span>

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