Profit Optimization for Splitting and Sampling Based Resource Management in Big Data Analytics-as-a-Service Platforms in Cloud Computing Environments

Data analytics plays a significant role in gaining insight of big data that can benefit in decision making and problem solving for various application domains such as science, engineering, and commerce. Cloud computing is a suitable platform for Big Data Analytic Applications (BDAAs) that can greatly reduce application cost by elastically provisioning resources based on user requirements and in a pay as you go model. BDAAs are typically catered for specific domains and are usually expensive. Moreover, it is difficult to provision resources for BDAAs with fluctuating resource requirements and reduce the resource cost. As a result, BDAAs are mostly used by large enterprises. Therefore, it is necessary to have a general Analytics as a Service (AaaS) platform that can provision BDAAs to users in various domains as consumable services in an easy to use way and at lower price. To support the AaaS platform, our research focuses on efficiently scheduling Cloud resources for BDAAs to satisfy Quality of Service (QoS) requirements of budget and deadline for data analytic requests and maximize profit for the AaaS platform. We propose an admission control and resource scheduling algorithm, which not only satisfies QoS requirements of requests as guaranteed in Service Level Agreements (SLAs), but also increases the profit for AaaS providers by offering a cost-effective resource scheduling solution. We propose the architecture and models for the AaaS platform and conduct experiments to evaluate the proposed algorithm. Results show the efficiency of the algorithm in SLA guarantee, profit enhancement, and cost saving.

As we come to terms with various big data challenges, one vital issue remains largely untouched. That is service level agreement (SLA) management to deliver strong Quality of Service (QoS) guarantees for big data analytics applications (BDAA) sharing the same underlying infrastructure, for example, a public cloud platform. Although SLA and QoS are not new concepts as they originated much before the cloud computing and big data era, its importance is amplified and complexity is aggravated by the emergence of time-sensitive BDAAs such as social network-based stock recommendation and environmental monitoring. These applications require strong QoS guarantees and dependability from the underlying cloud computing platform to accommodate real-time responses while handling ever-increasing complexities and uncertainties. Hence, the over-reaching goal of this PhD research is to develop novel simulation, modelling and benchmarking tools and techniques that can aid researchers and practitioners in studying the impact of uncertainties (contention, failures, anomalies, etc.) on the final SLA and QoS of a cloud-hosted BDAA.

Online service is used to be as Pay-Per-Use in Cloud computing. Service user need not be in a long time contract with cloud service providers. Service level agreements (SLAs) are understandings marked between a cloud service providers and others, for example, a service user, intermediary operator, or observing operators. Since cloud computing is an ongoing technology giving numerous services to basic business applications and adaptable systems to manage online agreements are significant. SLA maintains the quality-of-service to the cloud user. If service provider fails to maintain the required service SLA is considered to be SLA violated. The main aim is to minimize the SLA violations for maintain the QoS of their cloud users. In this research article, a toolbox is proposed to help the procedure of exchanging of a SLA with the service providers that will enable the cloud client in indicating service quality demands and an algorithm as well as Negotiation model is also proposed to negotiate the request with the service providers to produce a better agreement between service provider and cloud service consumer. Subsequently, the discussed framework can reduce SLA violations as well as negotiation disappointments and have expanded cost-adequacy. Moreover, the suggested SLA toolkit is additionally productive to clients so clients can secure a sensible value repayment for diminished QoS or conceding time. This research shows the assurance level in the cloud service providers can be kept up by as yet conveying the services with no interruption from the client's perspective

A Service Level Agreement (SLA) is a legal contract between parties to ensure the Quality of Service (QoS). It specifies one or more service level objectives (SLO), to ensure that the QoS delivered has met customer expectations. However, It becomes hard to guarantee QoS levels and detect SLA violations. Therefore, we propose to use MDE (Model Driven Engineering) to express the SLA contract requirements. This latter, created with a specific modeling language (DSML), will be used harmonically with a Multi-agent systems (MASs) in order to monitor SLA violations in real-time. Indeed, MASs are suitable tools for self-detection of failures and self-monitoring of cloud operations and services, QoS negotiation and SLA management. They are designed to operate in a dynamically changing environment. Our main motivation is firstly to use MDE technology for the creation of the SLA contract and then to integrate MASs in order to control the quality of service contract and guarantee transparency and symmetry with respect to the SLA contract between prospective signatories.

A service level agreement (SLA) is part of a contract between a cloud service provider (CSP) and a cloud service user (CSU) which defines and describes different agreed properties of the service. The negotiation of the SLA between a CSU and a CSP is a pivotal process in the SLA life cycle. An SLA may include many negotiable quality of service (QoS) parameters with each QoS parameter having multiple acceptable values. Different combinations of acceptable values for all QoS parameters grow exponentially as number of QoS parameters and their selectable values increase. Manually negotiating for all of the QoS parameters considering their various options can be an erroneous and diligent task with lower utility. In this paper, a time efficient flip-flop negotiation strategy for the SLAs in cloud services is presented. The flip-flop negotiation strategy is based on a time dependent 3D utility function and on a dynamic concession strategy using the polynomial extrapolation of opponent's concession. This negotiation strategy is useful for time-critical cloud services as it operates with a motive of reaching an agreement at earlier time without compromising over the utility level of the agreement. Moreover, a multi-provider concurrent negotiation method is presented in this work using the flip-flop negotiation strategy. Multiple experiments are performed (using the implementation of flip-flop negotiation strategy) to test the presented work. The results of the experiments enforce the validity of the flip-flop negotiation strategy for such cloud services where time is an important factor during the SLA negotiation process.

The advancement of technology has brought up so many elements of ease for human beings that now humans cannot afford to think of a life without all these. But all is not about ease and comfort. Along with all these elements, there are many modern complexities as well as challenges too. Big data analytics and cloud computing are among the elements in which we face many challenges. This document discusses some of the challenges in big data analytics and cloud computing.

As the cloud markets grow, the cloud providers are faced with new challenges such as reduction of power consumption and guaranteeing service level agreements (SLAs). One reason for these problems is the use of server consolidation policy based on virtualization technologies for maximizing the efficiency of resource usage. Because current virtualization technologies do not ensure performance isolation among active virtual machines (VMs), it is required to consider resource usage pattern of VMs to improve total throughput and quality of service. In this paper, we propose a virtual machine scheduler for multicore processors, which exploits the last-level cache (LLC) reference ratio. Specifically, we focus on the performance impact of contention in a shared LLC. We have found that the ratio of the number of LLC references to that of instructions (LLC reference ratio) is highly associated with the amount of cache demand, and a Performance-Maximizing VM (PMV) scheduling algorithm can be devised by using the ratio. We show that our PMV scheduler is effective by evaluation for various workloads.

This work presents a novel scheme for Service Level Agreements (SLAs) in a service-oriented architecture (SOA). An SLA is a contract that guarantees quality of service (QoS) between service providers and consumers. An SLA can be split into several parts for an SOA system which is consisting of different services. A split SLA is used to guarantee quality of services for one of services in an SOA system. However, these contract rules do not regulate follow-up process in services. SLA violations may occur consequently. For instance, interactions between services are not encrypted because the encryption parameter isn't included in the split SLA contract. Confidential data would be transmitted through unsafe channels. There would be a security issue of SLA Management for follow-up processes in an SOA system. The novel scheme in this work addresses these problems. Using SLAs management proposed in this work can identify the services that consumer needs and split the contracts for follow-up services. SLAs are not only guaranteed between service providers and consumers but also assured in follow-up processes. The proposed method improves the security and completeness of SLA using in an SOA system.

Service level agreement (SLA) in cloud computing can be defined as a contractual agreement signed between cloud user and cloud provider in order to manage the quality of service (QoS) parameters which are the fundamental part of SLAs. The current dynamic SLA monitoring approaches have considered the cloud provider's perspective only. To take into consideration the user's perspective; this research proposes a dynamic SLA monitoring approach by generating new SLA terms based on analysing the SLA penalties. A new proposed trade-off mechanism is applied between monthly cost and QoS guarantee values. Thus; we propose a dynamic model for updating QoS parameters of SLA in cloud environment. Java language is used with a QoS measurement dataset to experiment the proposed approach. The current Static SLA (SSLA) approaches are compared with the proposed Dynamic SLA (DSLA) approach. The results of this experimental study show that the number of SLA violations in DSLA are less than the number of SLA violations in SSLA.

Service level agreement (SLA) in cloud computing can be defined as a contractual agreement signed between cloud user and cloud provider in order to manage the quality of service (QoS) parameters which are the fundamental part of SLAs. The current dynamic SLA monitoring approaches have considered the cloud provider's perspective only. To take into consideration the user's perspective; this research proposes a dynamic SLA monitoring approach by generating new SLA terms based on analysing the SLA penalties. A new proposed trade-off mechanism is applied between monthly cost and QoS guarantee values. Thus; we propose a dynamic model for updating QoS parameters of SLA in cloud environment. Java language is used with a QoS measurement dataset to experiment the proposed approach. The current Static SLA (SSLA) approaches are compared with the proposed Dynamic SLA (DSLA) approach. The results of this experimental study show that the number of SLA violations in DSLA are less than the number of SLA violations in SSLA.

Content Placement (CP) problem in Cloud-based Content Delivery Networks (CCDNs) leverage resource elasticity to build cost effective CDNs that guarantee QoS. In this paper, we present our novel CP model, which optimally places content on surrogates in the cloud, to achieve (a) minimum cost of leasing storage and bandwidth resources for data coming into and going out of the cloud zones and regions, (b) guarantee Service Level Agreement (SLA), and (c) minimize degree of QoS violations. The CP problem is NP-Hard, hence we design a unique push-based heuristic, called Weighted Social Network Analysis (W-SNA) for CCDN providers. W-SNA is based on Betweeness Centrality (BC) from SNA and prioritizes surrogates based on their relationship to the other vertices in the network graph. To achieve our unique objectives, we further prioritize surrogates based on weights derived from storage cost and content requests. We compare our heuristic to current state of the art Greedy Site (GS) and purely Social Network Analysis (SNA) heuristics, which are relevant to our work. We show that W-SNA outperforms GS and SNA in minimizing cost and QoS. Moreover, W-SNA guarantees SLA but also minimizes the degree of QoS violations. To the best of our knowledge, this is the first model and heuristic of its kind, which is timely and gives a fundamental pre-allocation scheme for future online and dynamic resource provision for CCDNs.

Big data analytics (BDA) is a key technology that is used in a variety of corporate fields, including the welfare medical profession. In the actual world, there is no such thing as a flawless security solution for a certain activity or application.Technological growth has provided a variety of different ways over the years that may aid in the development of unique algorithms and techniques. The potential for cyberthreats and cyberattacks grows as more consumer and organizational information is digitized and collected for data analytics. Security and tactical information are two important areas where big data analytics is anticipated to make a substantial contribution. Current security problem and tracking systems (or SIEM) systems, which typically operate with a small selection of traditional data sources like firewalls, intrusion detection systems, etc., in a software system, do not adequately address security analytics in a big data context. The paper addressed the security challenges of big data analytics in social network platform. The paper also looked at the user engagement in different social media platforms.

Utility computing enables the use of computational resources and services by consumers with service obligations and expectations defined in Service Level Agreements (SLAs). Parallel applications and workflows can be executed across multiple sites to benefit from access to a wide range of resources and to respond to dynamic runtime requirements. A utility computing provider has the difficult role of ensuring that all current SLAs are provisioned, while concurrently forming new SLAs and providing multiple services to numerous consumers. Scheduling to satisfy SLAs can result in a low return from a provider's resources due to trading off Quality of Service (QoS) guarantees against utilisation. One technique is to employ advance reservations so that an SLA aware scheduler can properly manage and schedule its resources. To improve system utilisation we exploit the principle that some consumers will be more flexible than others in relation to the starting or completion time, and that we can juggle the execution schedule right up until each execution starts. In this paper we present a QoS scheduler that uses SLAs to efficiently schedule advance reservations for computation services based on their flexibility. In our SLA model users can reduce or increase the flexibility of their QoS requirements over time according to their needs and resource provider policies. We introduce our scheduling algorithms, and show experimentally that it is possible to use flexible advance reservations to meet specified QoS while improving resource utilisation.

Service level agreement (SLA) is a formal contract between a service provider and a service consumer to guarantee the Quality of service (QoS) expectations, it is used in all areas of information technology, such as Cloud Computing, Internet of Things (IoT), networks and Web services. For IoT applications, the main challenges are: (1) how to describe the SLA terms, such as QoS properties, service levels, penalties in SLA violation, (2) how to monitor these terms, and (3) how to integrate an SLA into all the IoT application layers. Therefore, in this paper, we propose ML-SLA-IoT, a framework for SLA specification and monitoring. It covers the entire layers of an IoT application. It describes precisely QoS levels, provided services, and obligations. It differs from other SLA specification languages in the specification of user preferences, the use of microservices (for reusability, dynamism and ease of integration) and ML-SLA (multi-level metrics and QoS according to existing constraints and user preferences). Furthermore, ML-SLA-IoT monitors SLA terms in an automatic and decentralised manner using smart contracts and blockchain technologies without the intervention of the third-party. Finally, we present a comparative study and experiments with existing solutions regarding to some criteria for SLA specification and monitoring. Our results show that ML-SLA-IoT gives better performance in terms of dynamic pricing, obligation combination, and SLA monitoring.

Service Level Agreements (SLA) represents the principal means to control the Quality of Service (QoS). In cloud computing, various advanced SLA strategies are used; some techniques among others try to avoid the SLA violations. Taking into account the cloud consumer contextual parameters is a promising way to predict and avoid costly SLA violations. Therefore, in this paper, we propose a context-aware system for the SLA in order to guarantee the QoS. We create a contextual ontology to introduce the semantic meaning of the cloud consumer contextual parameters. In addition, using reasoning techniques, we (1) predict SLA violations and we (2) choose and apply the corrective actions in autonomous manner. This allows getting a proactive adjustment of the cloud service execution and respecting the SLA parameters.