Brokering in interconnected cloud computing environments: A survey

Chauhan, Sameer Singh; Pilli, Emmanuel S.; Joshi, R. C.; Singh, Girdhari; Govil, Mahesh Chandra

doi:10.1016/j.jpdc.2018.08.001

Cited by 66 publications

(28 citation statements)

References 73 publications

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“…Brokering policies 25 make decisions during resource provisioning and resource adaptation depending on the user objectives as well as information exchanging among Clouds. Architecture of intercloud federation among adjacent layers of partner cloud and delegation between interlayers of local cloud is envisioned in Reference 26 and this technique requires the translation of requests for services between interdependent layers on the same cloud (eg, delegation mode).…”

Section: Factors Of Interconnected Cloud Managementmentioning

confidence: 99%

Characterizing the architectures and brokering protocols for enabling clouds interconnection

Latif

Gilani

Ali

et al. 2020

Concurrency and Computation

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Interconnecting the computing services of different tiers by multiple cloud providers is indispensable to overcome the exponentially increasing demands of enterprises. In view of highly dynamic and unpredictable environment, cloud providers have to face numerous challenges related to service provisioning of diversified applications while handling the critical management operations on resource layers. Proper configuration and uniform development of architectural components and protocols to setup interconnected clouds are inevitable, which play effective role in management. Various approaches have been proposed by research community to interconnect the geographically dispersed clouds to extend the capabilities of standalone provider. Fundamentally, this study encompasses the requirement factors and classification of interconnected cloud management from various aspects. Mainstream resource management elements, architectural components, and brokering protocols with respect to functional impact, which proposed in literature, have been discussed. These protocols and components play pivotal role for aggregating computing services from distinct providers and maintaining the quality of service parameters of service provisioning. Finally, the analysis of various projects is also presented to highlight the functionality of collaborated ecosystem with issues and further directions. K E Y W O R D S brokering, configuration, federation, interconnected clouds, standard interfaces 1 OVERVIEW OF INTERCONNECTED CLOUD Interconnected cloud (Intercloud) is an analogy to internet as latter developed by interlinking the multiple standalone networks, so on the same paradigm evolution of interconnected cloud is intrinsic. Intercloud with the aim to provide large-scale infrastructure that facilitates just-in-time, opportunistic, and scalable provisioning of application services, consistently achieving QoS target under varying workload, resources, and network conditions. In order to harness the geographically dispersed infrastructure of cloud computing in form of aggregated capabilities, interconnecting the standalone clouds through state-of-the-art components and protocols is inevitable with management point of view. 1 Since effective management of the interconnected clouds has great impact on optimal dynamic workload handling and utilization of resources from clients and providers perspective, respectively. Collaboration among multiple providers compose the ecosystem. Therefore, management in respect of resource discovery, monitoring, scheduling in decentralized environment requires the robust policies and automated architectural components to handle critical operations and spikes in demands. 2 Connecting the multiple clouds using diversified architectural components and protocols is vibrant paradigm that curb the issues of singleton cloud when spikes in demand ensuring resources availability and optimized performance. Interconnected cloud in federation 3,4 form also presents the new business model where service providers lease the under...

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Section: Factors Of Interconnected Cloud Managementmentioning

confidence: 99%

Characterizing the architectures and brokering protocols for enabling clouds interconnection

Latif

Gilani

Ali

et al. 2020

Concurrency and Computation

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“…In reference [21], cloud broker and its need in the related cloud environment are discussed. Also, cloud brokering frameworks of interconnected cloud environments are reviewed.…”

Section: Related Workmentioning

confidence: 99%

Bandwidth and Delay Optimization by Integration of Software Trust Estimator with Multi-user Cloud Resource Competence

Mirrezaei

2020

IJE

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Trust establishment is one of the significant resources to enhance the scalability and reliability of resources on cloud environments. To establish a novel trust model on SaaS (Software as a Service) cloud resources and to optimize the resource utilization of multiple user requests, an integrated software trust estimator with multiuser resource competence (IST-MRC) optimization mechanism is proposed in this paper. IST-MRC optimization mechanism combines its trustworthy properties with optimal resource allocation, on the requisition of the software apps, without any traffic occurrence in the cloud environment. Initially, a behavior trust estimator is developed in the IST-MRC mechanism to measure the trust value of the software service zone. The trust value is estimated, based on Software Availability Rate, Hit Rate, and User Feedback regarding the specific software apps. Next, the resources are optimized to multiple users using competence optimization. The competence optimization in the IST-MRC mechanism computes the processor speed, bandwidth, and latency to handle the varied traffic conditions on multiple user requests. Experiments are conducted to measure and evaluate factors, such as Successful Request Handles, Resource Utilization Efficiency, Latency Time, and Trust Success Ratio on the multiple users.

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“…To minimize the cost with keeping the performance high there are many algorithms have been proposed especially in transfer and scheduling data from the customer to cloud, the responsible party for sending and scheduling data in the cloud is the third-party broker. The third-party broker is an entity used for negotiates and manages the data transfer from customers to cloud storage [13,9].There are a set of factors that can affect data transfer costs include: the type of Service, Data transfer outside Region, Service provider, quality of Service, and amount of data sent and received. It is the maximum amount of data that moved successfully from one place to another over a network path in a given time period.…”

Section: Fig 1 Challenges In Cloud Of Thingsmentioning

confidence: 99%

“…In order to evaluate the proposed scheduling algorithms we have used a simulation tool knows as Cloudsim, it uses to evaluate the hypothesis before deployment in the real environment [9]. In this section, we evaluate the performance of the proposed algorithm.…”

Section: Performance Evaluationsmentioning

confidence: 99%

An improved PBMM Algorithm by Reduce Cloud Data Traffic and Transfer Costs in Cloud of Things

Obaid*,

Pani,

Pattnaik

2019

IJITEE

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Cloud computing has been widely studied over the recent years. Researchers have developed different algorithms for improving the performance and minimizing the cost. This paper proposes a new algorithm to improve and enhance the PBMM algorithm (Priority Based on Min-Min Algorithm). The proposed algorithm works with the aid of one of the Cloud of Things (CoT) services; this service is Sensing and Actuation as a Service (SAaaS). The proposed Algorithm works on third-party broker. However, it has two-phase: the first phase is Sensing: in this phase, the sensor observes the throughput for all tasks and compares it with the link capacity. The Second phase is Actuation: depending on the comparison in the first phase, the priority of all the takes will change depending on the link capacity, all tasks will have the same priority if the throughput is low (Green throughput). All tasks will have two priority levels (high, low) if the throughput medium (Yellow throughput), and finally, if the throughput is high (red throughput) all tasks will have a default priority which assigned to them when they are created. However, the efficiency and performance of the IPBMM algorithm depend on the capacity of the link. If capacity is high (traffic in the network is high), the performance is very good and the costly, but if the capacity is medium (traffic in the network is medium), the performance is good as well as the cost. While if the capacity is low (traffic in the network is low), the performance is good and the cost is free. Therefore, the outcomes of the proposed algorithm experiment given 30% better results than the PBMM algorithm and other state-of-the-art algorithms

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Brokering in interconnected cloud computing environments: A survey

Cited by 66 publications

References 73 publications

Characterizing the architectures and brokering protocols for enabling clouds interconnection

Characterizing the architectures and brokering protocols for enabling clouds interconnection

Bandwidth and Delay Optimization by Integration of Software Trust Estimator with Multi-user Cloud Resource Competence

An improved PBMM Algorithm by Reduce Cloud Data Traffic and Transfer Costs in Cloud of Things

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