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In this paper, we introduce SLAC, a SLA definition language specifically devised for clouds as a formalism to support the whole SLA lifecycle. The main novelty of the language is the possibility of capturing within the SLA the dynamic aspects of the environment by defining the conditions and actions to change service levels at runtime. SLAC permits...
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... distinctive features, together with its ease of use and its expression power, enable SLAC to cover most scenarios in the cloud domain. Figure 3 depicts the sections of a SLA defined using SLAC. We informally present them via our running example SLA, reported in Table 1, which refers to a brokered provision of a IaaS service, assessed by an auditor. ...
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This study critically reviews the IaaS cloud's development on revenue maximization since 2012 to answer these research queries; i) What are the main influential factors towards revenue maximization in the cloud market? ii) What are the main challenges and resistance towards revenue maximization in cloud computing?, and iii) What are the possible so...
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... The reasons are two-fold: (1) Digital platforms have to interact with their consumers in a real-time manner and provide services with compelling user experience. For instance, the service capacity of the platforms has to be adjusted in response to the dynamics of customer traffic (Uriarte et al., 2019). The customer traffic is often related to the number of registered users. ...
Hardware manufacturers often use mobile apps to provide value-added services for their product users. These platform-based apps can also serve as a sales outlet for the product. Subsequently, manufacturers consider building their own app platforms over relying on third-party platforms. We propose an optimal control model where a manufacturer produces a physical product and sells it through a platform-based app, which subsequently provides services for the product in a finite time horizon. The instantaneous demand is sensitive to the sales price and service level while the stock of registered customers evolves over time. We derive results from two scenarios: Firm-owned platform and third-party platform. Thereafter, the model is extended to consider a competing platform’s service level as a reference quality. The results imply that it would be better for the manufacturer to build its own platform and operate in-house, if it pursues a higher level of service. In contrast, if the manufacturer intends to develop a larger quantity of registered customers, it would be better to use the third-party platform. However, the service level of the latter will gradually decline. To improve the service quality of the third-party platform, the competing platform’s reference quality level plays a significant role. Regardless of whether the initial reference is higher or lower, the third-party platform will increase the service level in the presence of the reference quality.
... It is external to the inspecting services and external to auditing services. Although the auditor sees this pseudonym on each operation made in cloud services and records it for accounting [40] and SLA monitoring [6], she should not obtain other information that could identify the client in the real world. ...
Enforcing Service Level Agreements (SLA) on service provisioning is a challenge in cloud computing environments. This paper proposes an architecture for multiparty (provider and client) auditing in cloud computing to identify SLA deviations. The architecture uses inspectors (software agents) and an independent auditor (third party) to collect SLA metrics from these parties. Privacy is preserved by using the separation of duties for all associated entities (inspectors and auditors). Additionally, service computing surges are automatically detected and handled using machine learning, avoiding performance bottlenecks and misinterpretation of measured SLA items. Thus, this paper improves service maintainability by avoiding service design changes when the service faces performance issues.
... Etymologizing fragmentation of the multiple smart devices and their architectures are associated with the middleware involved in them. Heterogeneous resources are sometimes mixed up and need a smart system to treat those mixed up at various Clouds levels [3]. ...
A Smart City understands the infrastructure, facilities, and schemes open to its citizens. According to the UN report, at the end of 2050, more than half of the rural population will be moved to urban areas. With such an increase, urban areas will face new health, education, Transport, and ecological issues. To overcome such kinds of issues, the world is moving towards smart cities. Cities cannot be smart without using Cloud computing platforms, the Internet of Things (IoT). The world has seen such incredible and brilliant ideas for rural areas and smart cities. While considering the Ecosystem in Smart Cities, there is a considerable requirement to improve the model to make life better. This proposed research integrates a city into a smart city using the Internet of Things (IoT) which focuses on the smart ecosystem. In this research work, a model is proposed to overcome an ecosystem's IoT and Machine Learning techniques issues. The Levenberg-Marquardt (LM), Bayesian Regularization (BR), and the Scaled Conjugate Gradient (SCG) algorithms are implemented with an ANN-based approach named to empower the ecosystem of the smart city while developing an efficient and smart ecosystem model. The proposed method's evaluation indicates that the BR algorithm achieves promising results concerning accuracy and miss rates. The predicted accuracy of the proposed model shows 91.55% performance of the ecosystem on the given factors.
... However, the DVFS technique does not consider the optimization of SLAs, which makes this technique has significant limitations in the existing cloud system. In [31], the authors deploy cloud resources in the data center under the client-level SLA requirements to minimize the overall power consumption. This research only concerns about the energy consumption of the environment. ...
With the growth and expansion of cloud data centers, energy consumption has become an urgent issue for smart cities system. However, most of the current resource management approaches focus on the traditional cloud computing scheduling scenarios but fail to consider the feature of workloads from the Internet of Things (IoT) devices. In this paper, we analyze the characteristic of IoT requests and propose an improved Poisson task model with a novel mechanism to predict the arrivals of IoT requests. To achieve the trade-off between energy saving and service level agreement, we introduce an adaptive energy efficiency model to adjust the priority of the optimization objectives. Finally, an energy-efficient virtual machine scheduling algorithm is proposed to maximize the energy efficiency of the data center. The experimental results show that our strategy can achieve the best performance in comparison to other popular schemes.
... The output P is a two-dimensional array where P[i][j] contains the node j in partition i. The rest of the algorithm iterates over all combinations of k partitions picking exactly one node from each partition by maintaining an index for each partition I (line 8), adding the indexed element from each partition to the set C (12-14), and updating the indices (23)(24)(25)(26)(30)(31)(32)(33). For each combination C, it computes the success probability p and detects the combination R with the highest p (15)(16)(17)(18)(19). The search stops prematurely if the required trust level (t) is reached (20)(21)(22) or normally if all combinations are exhausted (27)(28)(29). ...
... It is of interest to evaluate whether proposed algorithms can maintain the reliability with fewer replicas, hence the lower cost. The deciding factor here is the trust parameter, which is agreed between the provider and consumer in the Service Level Agreement [25]. In our data set, the vast majority of tasks (3,114 out of 3,172) require the trust levels of either one or four. ...
... SLAs formalize the terms for the service's provisioning and its quality. In this context, with SLAC, 2 In this article, we propose a framework, named cloud service smart contract manager (CSSCM), for the definition and enforcement of SLAs by transforming them into smart contracts, which are then executed in the blockchain. The process is mainly divided into the off-chain and blockchain (transaction network) phases. ...
... The envisioned framework has been realized by extending our previous work, 2,8,20 concerned with a language and an associated framework for the definition and management of dynamic SLAs, with the capability of (i) transforming dynamic SLAs into smart contracts, (ii) enforcing smart contracts via the blockchain by relying on appropriate mechanisms for contract management and consensus attainment, and (iii) exploiting an oracle interface for retrieving information about the sensed cloud service for better supporting decision making during the SLA enforcement. ...
The current cloud market is dominated by a few providers, which offer cloud services in a take‐it‐or‐leave‐it manner. However, the dynamism and uncertainty of cloud environments may require the change over time of both application requirements and service capabilities. The current service‐level agreement (SLA) management solutions cannot easily guarantee a trustworthy, distributed SLA adaptation due to the centralized authority of the cloud provider who could also misbehave to pursue individual goals. To address the above issues, we propose a novel SLA management framework, which facilitates the specification and enforcement of dynamic SLAs that enable one to describe how, and under which conditions, the offered service level can change over time. The proposed framework relies on a two‐level blockchain architecture. At the first level, the smart SLA is transformed into a smart contract that dynamically guides service provisioning. At the second level, a permissioned blockchain is built through a federation of monitoring entities to generate objective measurements for the smart SLA/contract assessment. The scalability of this permissioned blockchain is also thoroughly evaluated. The proposed framework enables creating open distributed clouds, which offer manageable and dynamic services, and facilitates cost reduction for cloud consumers, while it increases flexibility in resource management and trust in the offered cloud services.
... Indeed, blockchain and smart contracts have attracted attention from industry and academia. Several projects are emerging on the area, e.g., [43,45], but there are still many open gaps, such as, defining QoS and pricing policies [32,47,49], comparing resource offers and providing seamless handover. For an overview of the challenges and advantages of these solutions, we refer to [46]. ...
Latency-sensitive and data-intensive applications, such as IoT or mobile services, are leveraged by Edge computing, which extends the cloud ecosystem with distributed computational resources in proximity to data providers and consumers. This brings significant benefits in terms of lower latency and higher bandwidth. However, by definition, edge computing has limited resources with respect to cloud counterparts; thus, there exists a trade-off between proximity to users and resource utilization. Moreover, service availability is a significant concern at the edge of the network, where extensive support systems as in cloud data centers are not usually present. To overcome these limitations, we propose a score-based edge service scheduling algorithm that evaluates network, compute, and reliability capabilities of edge nodes. The algorithm outputs the maximum scoring mapping between resources and services with regard to four critical aspects of service quality. Our simulation-based experiments on live video streaming services demonstrate significant improvements in both network delay and service time. Moreover, we compare edge computing with cloud computing and content delivery networks within the context of latency-sensitive and data-intensive applications. The results suggest that our edge-based scheduling algorithm is a viable solution for high service quality and responsiveness in deploying such applications.
... In the future we plan to: (i) analyse the impact of using Average Placement Rate to estimate the running time of the method; (ii) adapt works that propose specific objectives as objective functions in our approach; (iii) use smart strategies to reorder the application of rules; and (iv) implement rules based on formal languages, such as SLAC 33,34,35 and SCEL 36 . ...
We propose a flexible meta‐heuristic framework for virtual machine (VM) organisation, provisioning, and adaptation in the cloud domain, based on migration costs and environment constraints. Order@Cloud improves VM placements according to multiple objectives represented by rules, qualifiers, and improvement cost, which can be easily modified and extended. Order@Cloud theoretically guarantees the adoption of a better set of placements, after considering their costs and benefits, by prioritising the worst VM placements. While existing solutions address only specific objectives, our framework is objective‐agnostic and extensible, which enables the adoption and implementation of new policies and priorities. We conduct experiments using a real cloud environment data and discuss the framework's performance, flexibility, and optimality and provide insights on the challenges and benefits of deploying this framework.
... On the other side, in the Customer-Based SLA, the metrics are adaptable in order to adjust the provided services according to the user's needs. Although this SLA is progressively adaptable, this methodology is essentially more complex and less utilized [6]. In a clearer sense, the traditional SLA uses the managing and monitoring processes only to pick up any errors or violations in the SLA functions, and also to ensure the compliance of the service with regard to a metric's function by means of analyzing the tools (e.g. ...
... The dynamism concerns with the modification in the users' and providers' needs, while the elasticity gives the providers and users the ability to maintain their QoS within the specified range (e.g. adding memory, decreasing response time, and the like) [6]. ...
The volatile nature of Cloud user’s needs is considered a worthy challenge in formulating the Service Level Agreement (SLA) negotiation. The sterility of the standard SLA templates in handling the diversity in the users’ requirements motives the concept of the dynamic SLA. Establishing the SLA contract is mainly based on converting the user’s QoS requirements into a meaningful Service Level Objectives (SLO) during the negotiation phase, but in case of modification in these QoS requirements especially during the run-time, the current negotiation may be violated and the provider may resort to terminate the current negotiation and re-establish it. This paper presents a novel methodology based on arithmetic and fuzzy logic model to establish a dynamic SLA’s Negotiation system commensurate with the dynamic aspects of the Cloud environment. The proposed negotiation system mainly based on defining pre-conditions and decisions to modify only the required SLO at the run-time without completely hang-up the SLA.
According to the latest statistics, the number of connected people to the Internet is still exponentially growing and the high quality of cloud services will remain significantly requested in the coming years. Facing the resulting tremendous growth of the intra-data center traffic, the traditional Data Center Network (DCN) architectures are not capable to stay ahead of the demand in terms of scalability and cost lowering. Besides, DCNs suffer from the degradation of their network Quality of Service (QoS) performances which deeply impact the users Quality of Experience (QoE). As a result, cloud architects and service providers are pressed to deal with this rapid explosion of data center traffic by reconsidering their data center architecture to fit their customers’ needs. Hence, implementing new techniques based on optimized algorithms become compulsory to overcome these challenges within data center networks. In this regard, we tackle the performance of data center networks by investigating new promising approaches able to improve intra-data center communication and to optimize the resource allocation within their infrastructures. Motivated by its architecture strengths, we study in this thesis the CamCube Server-Only data center managed by ONOS SDN controller. Besides, we aim to implement and analyze the performance of strategies to address the optimization of routing and resource allocation for intra-CamCube servers communications. In fact, our objective consists of improving network performance and decreasing network congestion. The problem of resource allocation and routing in SDN-based CamCube topology is NP-hard. In order to overcome this challenge, we investigate the problem through three increasing complexity steps. In the first stage, we consider unicast intra-CamCube communication by proposing new methods named CRP and ACOCRP respectively based on Linear Programming Ant Colony Optimization. The latters generate an optimized path to forward packet in a typical CamCube network subjects to the constraints of network performance in terms of latency and path length. In the second phase, we propound a new M-CRP and ACO-MCRP approaches to tackle the multicast communications in SDN-based CamCube network. Our approaches addressed multicast routing and resource allocation of online arrived flows. We show that our propounded approach enhanced the CamCube QoS and the quality of the proposed multicast tree. In this thesis, we online treat the routing and the resource allocation for the communication of each arrived flow. As a third step, we focused on resource allocation optimization for batch mode arrival of traffic flows within ONOS-based CamCube topology by proposing batch-(M)CRP strategy. Note that we emulated the propounded environment to test the full proposed schemes, through extensive experimentations conducted with Mininet. We evaluate the performance of our propositions in terms of E2E delay, jitter and packet loss. Obtained results demonstrate that our proposals outperform the existing state-ofthe-art strategies such as the shortest path and OSPF routing schemes respectively for CamCube and traditional Clos DCNs architectures.
