CVSHR: Enchantment Cloud-based Video Streaming using the Heterogeneous Resource Allocation

Elsharkawey, Mohamed A.; Refaat, Hosam E.

doi:10.5815/ijcnis.2017.09.01

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…Actually, the different scheduling algorithms based on QoS parameters have been introduced for different environments in [22]. The scheduling is performed to achieve the huge service requests and to enhance the efficiency of the workload.…”

Section: Related Workmentioning

confidence: 99%

DLBS: Decentralize Load-Balance Scheduling Algorithm for Real-Time IoT Services in Mist Computing

Refaat¹,

A.Mead²

2019

IJACSA

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Internet of Things (IoT) has been industrially investigated as Platforms as a Services (PaaS). The naive design of these types of services is to join the classic centralized Cloud computing infrastructure with IoT services. This joining is also called CoT (Cloud of Things). In spite of the increasing resource utilization of cloud computing, but it faces different challenges such as high latency, network failure, resource limitations, fault tolerance and security etc. In order to address these challenges, fog computing is used. Fog computing is an extension of the cloud system, which provides closer resources to IoT devices. It is worth mentioning that the scheduling mechanisms of IoT services work as a pivotal function in resource allocation for the cloud, or fog computing. The scheduling methods guarantee the high availability and maximize utilization of the system resources. Most of the previous scheduling methods are based on centralized scheduling node, which represents a bottleneck for the system. In this paper, we propose a new scheduling model for manage real time and soft service requests in Fog systems, which is called Decentralize Load-Balance Scheduling (DLBS). The proposed model provides decentralized load balancing control algorithm. This model distributes the load based on the type of the service requests and the load status of each fog node. Moreover, this model spreads the load between system nodes like wind flow, it migrates the tasks from the high load node to the closest low load node. Hence the load is expanded overall the system dynamically. Finally, The DLBS is simulated and evaluated on truthful fog environment.

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Section: Related Workmentioning

confidence: 99%

DLBS: Decentralize Load-Balance Scheduling Algorithm for Real-Time IoT Services in Mist Computing

Refaat¹,

A.Mead²

2019

IJACSA

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“…Actually, the various scheduling algorithms of the changing in the used QoS parameters have been offered for different environments in [17]. The scheduling is performed to accomplish the massive income and to improve the effectiveness of the work load.…”

Section: Related Workmentioning

confidence: 99%

MLRTS: Multi-Level Real-Time Scheduling Algorithm for Load Balancing in Fog Computing Environment

Elsharkawey¹,

Refaat²

2018

IJMECS

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Cloud computing is an innovative technology which is based on the internet to preserve large applications. It is warehoused as a shared data over one platform. In addition, it offers better services to clients who belong to different organizations. In spite of the maximum utilization of computational resources provided by the cloud computing with lower cost, it suffers from specific restrictions. These restrictions are encountered through the load balancing of data in the cloud data centers. These restrictions are represented in the less bandwidth utilization, resource limitations, fault tolerance and security etc. In order to overcome these limitations, new computing model called Fog Computing is presented. It aims to offer the required service of the sensitive data to end users without delaying. The function of the fog computing is similar to the cloud computing with two preferred advantages. The first one is that it is placed more near to the end users to introduce its service in less time. Secondly, it is more valuable for streaming the real time applications, sensor networks, IOT which need high speed and reliable internet connection. In this paper, a novel load balancing algorithm has been proposed over a novel architectural model in the Fog Computing environment. The proposed model aims to serve the real-time tasks within their deadline. In addition, it serves the different soft tasks without starving. The soft tasks are classified according to the execution time and the priority levels. In addition, they are served according to their waiting time and priority-level. Furthermore, the proposed algorithm is employed to maximize the throughput, the resources and the network utilization and preserving the data consistency with less complexity to accomplish the end users demand.

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CVSHR: Enchantment Cloud-based Video Streaming using the Heterogeneous Resource Allocation

Cited by 2 publications

References 14 publications

DLBS: Decentralize Load-Balance Scheduling Algorithm for Real-Time IoT Services in Mist Computing

DLBS: Decentralize Load-Balance Scheduling Algorithm for Real-Time IoT Services in Mist Computing

MLRTS: Multi-Level Real-Time Scheduling Algorithm for Load Balancing in Fog Computing Environment

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