Monitoring self-adaptive applications within edge computing frameworks: A state-of-the-art review

Taherizadeh, Salman; Jones, Andrew C.; Taylor, Ian; Zhao, Zhiming; Stankovski, Vlado

doi:10.1016/j.jss.2017.10.033

Cited by 120 publications

(69 citation statements)

References 29 publications

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“…Therefore, the use of the right cloud monitoring technologies is needed to assure the performance of these applications. Recent researches shows that none of the existing widely-used cloud monitoring tools yet provides an integrated monitoring solution within edge computing frameworks (Taherizadeh et al, 2018). Hence, a detailed analysis for both functional and non-functional requirements is provided in order to address all kind of organizations' needs for this step.…”

Section: Follow-upmentioning

confidence: 99%

“…Table 3 shows a high-level analysis of functional requirements for cloud monitoring tools, while Table 4 a non-functional requirement analysis for cloud monitoring systems. This analysis was the result by comparing ten widely used cloud monitoring tools, both open source and commercial, along with their capabilities and shortcomings, as well as how these monitoring systems meet varied requirements (Taherizadeh et al, 2018).…”

Section: Follow-upmentioning

confidence: 99%

“…A detailed analysis of functional requirements for cloud monitoring tools is available at the paper entitled "Monitoring self-adaptive applications within edge computing frameworks: A state-of-the-art review" (Taherizadeh et al, 2018). We refer the reader to that paper to find more detailed information about this process.…”

Section: Follow-upmentioning

confidence: 99%

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Moving the IT Infrastructure to the Cloud

et al. 2018

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Cloud computing services are nowadays advertised as an emerging business model. Moreover, these services bring innovative solutions in a more sophisticated competitive market. But, the decision for their adoption could be significantly reduced due to organizations’ concerns related to security, privacy, and trust. The challenge involves such questions as where to start, which provider should the company choose or whether it is even worthwhile. Thus, this paper proposes an improved unified framework, based on a previous study where a 6 step process framework was introduced. This improved framework add one new step for security and control after the migration process. At the end, a 7 processes framework is proposed aimed to fulfill organizations’ concerns when decide to adopt cloud computing services with a follow-up step. This additional step intends to help IT directors to make sure everything is working properly in a methodological way, in order to achieve a successful cloud computing migration process. An effective solution that is gaining momentum and popularity for competitive organizations.

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Section: Follow-upmentioning

confidence: 99%

Section: Follow-upmentioning

confidence: 99%

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Moving the IT Infrastructure to the Cloud

et al. 2018

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“…Since a lot of applications tend to run on clouds [4], it is therefore become an important way to ensure their QoS through enforcing SLA, especially when migrating time-critical applications [5][6] [7]. Though there exist various of frameworks for service monitoring to detect the service violation [8], the agreement is still hard to be enforced in practice. Because following gaps hinder the traditional SLA to be really adopted and feasible in industry: i) Manual verification.…”

Section: Introductionmentioning

confidence: 99%

Trustworthy Cloud Service Level Agreement Enforcement with Blockchain Based Smart Contract

Zhou

Laat

Zhao

2018

2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

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Cloud Service Level Agreement (SLA) is challengeable due to lacking a trustworthy platform. This paper presents a witness model to credibly enforce the cloud service level agreement. Through introducing the witness role and using the blockchain based smart contract, we solve the trust issues about who can detect the service violation, how the violation is confirmed and the compensation is guaranteed. In this model, a verifiable consensus sortition algorithm proposed by us is firstly leveraged to select independent witnesses to form a witness committee. They are responsible for a specific service level agreement and get paid by monitoring and detecting service violation. Through carefully designing the witness' payoff function in the agreement, we further leverage game theory to analyze and prove that it is not the witness itself is trustworthy. Instead, the witness has to tell the truth because of its greedy nature, which is the desire to maximize its own revenue. As long as the service violation is confirmed by the witness committee, the compensation is automatically transferred to the customer by the smart contract. Finally, we implement a proof-of-concept prototype with the smart contract of Ethereum blockchain. It demonstrates the feasibility of our model.

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“…By introducing real-time analytics processed on the nodes at the extreme edge of the network [3], and hence fast, safe communication with stakeholders such as driver, benefits (e.g. accident prevention or cost optimization) would be put to the advanced level with additional services enabled, not being possible with today's infrastructure.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Data-Intensive Telematics Functionalities at the Extreme Edge of the Network: Experience with the PrEstoCloud Project

Taherizadeh

Novak

Komatar

et al. 2018

2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC)

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Abstract-In recent years, use of different sensors connected to vehicles is dramatically increasing in order to enhance transportation efficiency. The current Big Data technologies are predominantly used to store large amount of telematics data especially in the cloud, and they are only able to perform simple querying for the purpose of reporting. While all the data is stored in the cloud-centric datacenters, these telematics systems are not capable of exploiting other functionalities offered by advanced real-time analytics such as run-time anomaly detection. In this paper, we propose an advanced telematics system orchestrated upon an edge computing framework in the context of the PrEstoCloud (Proactive Cloud Resources Management at the Edge for Efficient Real-Time Big Data Processing) project. This telematics system is a real-time data-intensive application running at the extreme edge of the network for drivers' behavior profiling and triggering run-time alerts. Such functionalities may be useful in order to notify stakeholders for example drivers and logistic centers on situations where a possible accident may occur or attention is required.

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Monitoring self-adaptive applications within edge computing frameworks: A state-of-the-art review

Cited by 120 publications

References 29 publications

Moving the IT Infrastructure to the Cloud

Moving the IT Infrastructure to the Cloud

Trustworthy Cloud Service Level Agreement Enforcement with Blockchain Based Smart Contract

Real-Time Data-Intensive Telematics Functionalities at the Extreme Edge of the Network: Experience with the PrEstoCloud Project

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