Introducing a Distributed Cloud Architecture with Efficient Resource Discovery and Optimal Resource Allocation

Khethavath, Praveen; Thomas, Johnson; Chan-Tin, Eric; Liu, Hong

doi:10.1109/services.2013.68

Cited by 35 publications

(7 citation statements)

References 20 publications

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“…It is difficult to know all the nodes since information about the entire Internet is required. A user wishing to do specific processing that needs some resources (either processor power or amount of memory) must find enough nodes to fulfill their resource requirements in order to complete the computation task [47]. Resource discovery provides the ability to know which resource is available and the VM holding it.…”

Section: Resource Discoverymentioning

confidence: 99%

Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey

et al. 2022

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Cloud users have recently expanded dramatically. The cloud service providers (CSPs) have also increased and have therefore made their infrastructure more complex. The complex infrastructure needs to be distributed appropriately to various users. Also, the advances in cloud computing have led to the development of interconnected cloud computing environments (ICCEs). For instance, ICCEs include the cloud hybrid, intercloud, multi-cloud, and federated clouds. However, the sharing of resources is not facilitated by specific proprietary technologies and access interfaces used by CSPs. Several CSPs provide similar services but have different access patterns. Data from various CSPs must be obtained and processed by cloud users. To ensure that all ICCE tenants (users and CSPs) benefit from the best CSPs, efficient resource management was suggested. Besides, it is pertinent that cloud resources be monitored regularly. Cloud monitoring is a service that works as a third-party entity between customers and CSPs. This paper discusses a complete cloud monitoring survey in ICCE, focusing on cloud monitoring and its significance. Several current open-source monitoring solutions are discussed. A taxonomy is presented and analyzed for cloud resource management.

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Section: Resource Discoverymentioning

confidence: 99%

Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey

et al. 2022

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“…Khethavath et al [44 ] provided a decentralised RA mechanism based on the Nash equilibrium. A reserve rationally formulated bid is used to allocate the discovered resources to the request.…”

Section: Reviewing Existing Ra Mechanismsmentioning

confidence: 99%

Resource allocation mechanisms in cloud computing: a systematic literature review

et al. 2020

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Cloud computing offers a vast number of processing opportunities and heterogeneous resources and meets the requirements of numerous applications at various levels. Thus, the allocation and management of resources are vital in cloud computing. Resource allocation is a technique in which the available resources such as central processing unit, random‐access memory, storage, and network bandwidth in cloud data centres are divided among users in a way that facilitates resource utilisation, provider profit, and user satisfaction. Integration and interaction with other modules of the resource management system, security, privacy, fairness, non‐fragmentation of resources, resource utilisation, provider profit, user satisfaction, reducing energy consumption, load balancing, flexibility, scalability, availability, improvement the number and time of virtual machine migrations, and the number of overloaded resources are considered as challenges for the resource allocation mechanism. A systematic resource allocation survey with innovations in resource management system architecture, categorising mechanisms, addressing the challenges, and issues is presented. In addition to introducing the existing resource allocation mechanisms, other similar survey papers have been reviewed. Finally, there are some suggested topics for future work.

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“…However, how to discover users with available resource in the network was not given. The authors in [230], [231] proposed to use the kademlia protocol [232] which allows a buyer to perform a resource discovery process to find candidate sellers with available resource in the network before the reverse auction is executed. Indeed, the candidate sellers can submit to the buyer their asks, each of which includes the information about available resources (i.e., CPU, memory, and bandwidth), QoS (i.e., a latency), a participation factor, and an incentive value.…”

Section: Client-assisted Cloud Systemsmentioning

confidence: 99%

Resource Management in Cloud Networking Using Economic Analysis and Pricing Models: A Survey

Luong

Wang

Niyato

et al. 2017

IEEE Commun. Surv. Tutorials

204

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This paper presents a comprehensive literature review on applications of economic and pricing models for resource management in cloud networking. To achieve sustainable profit advantage, cost reduction, and flexibility in provisioning of cloud resources, resource management in cloud networking requires adaptive and robust designs to address many issues, e.g., resource allocation, bandwidth reservation, request allocation, and workload allocation. Economic and pricing models have received a lot of attention as they can lead to desirable performance in terms of social welfare, fairness, truthfulness, profit, user satisfaction, and resource utilization. This paper reviews applications of the economic and pricing models to develop adaptive algorithms and protocols for resource management in cloud networking. Besides, we survey a variety of incentive mechanisms using the pricing strategies in sharing resources in edge computing. In addition, we consider using pricing models in cloud-based Software Defined Wireless Networking (cloud-based SDWN). Finally, we highlight important challenges, open issues and future research directions of applying economic and pricing models to cloud networking.

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Introducing a Distributed Cloud Architecture with Efficient Resource Discovery and Optimal Resource Allocation

Cited by 35 publications

References 20 publications

Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey

Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey

Resource allocation mechanisms in cloud computing: a systematic literature review

Resource Management in Cloud Networking Using Economic Analysis and Pricing Models: A Survey

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