Dynamic inter-SLA resource sharing in path-oriented differentiated services networks

Cloud computing it is a very demanding technology. in current times landscapes of cloud computing and distributed systems, maintaining the strict adherence to Service Level Agreements (SLAs) while managing resources efficiently is a main challenge. This challenge is further evaluated by the constantly moving nature of workloads and also the demands asked by large-scale infrastructures. Old resource management method sometimes falls short because of their rigidity and also limited adaptability. To Show these challenges, we propose a modern/new algorithm lied on reinforcement learning, which integrates the strategy sophisticated monitoring. This algorithm is made to dynamically optimize SLA compliance by adjusting the allocation of resources in real-time. Our method utilizes the reinforcement learning to catch the complex interactions between the allocation of resource, SLA adherence, and overall, the performance of system. By applying a monitoring policy that observe the important indicators of performance, the algorithm can predict the potential SLA violations and can proactively re-assign the resources to prevent them. This approach not only helps in consistent adherence to SLAs but also helps in improving the efficiency of resource by minimizing the waste and also by reducing costs. We have validated our method through the extreme simulations and also the experimental evaluations. The results show the consistent improvements in SLA compliance, utilization of resource, and the stability of system compared to exist methods. The algorithm is specifically effective in handling the unpredictable patterns of workload and variable of resource demands, making it a solution robust for modern environments of cloud.

In 5G and beyond wireless systems, Network Slicing (NS) feature will enable the coexistence of extremely different services by splitting the physical infrastructure into several logical slices tailored for a specific tenant or application. In sliced Radio Access Networks (RANs), an optimal traffic sharing among cells is key to guarantee Service Level Agreement (SLA) compliance while minimizing operation costs. The configuration of network functions leading to that optimal point may depend on the slice, claiming for slice-aware traffic steering strategies. This work presents the first data-driven algorithm for slice-aware traffic steering by tuning handover margins (a.k.a. mobility load balancing) per slice and adjacency with a proportional controller based on SLA criteria. The tuning process is driven by a novel indicator, derived from connection traces, showing the imbalance of SLA compliance among neighbor cells per slice. Performance assessment is carried out with a system-level simulator implementing a realistic sliced RAN offering services with different throughput, latency and reliability requirements. Results show that the proposed algorithm improves the overall SLA compliance by 9% in only 15 minutes of network activity compared to the case of not steering traffic, outperforming two legacy mobility load balancing approaches not driven by SLA.

Configuring routers and network devices to achieve quality of service (QoS) goals is a challenging task. In a DiffServ environment, traffic flows are assigned specific classes of service, and service level agreements (SLA) are enforced at routers within the domain. We present a model for QoS policy configurations that facilitates efficient property-based verification. Network configuration is given as a set of policies governing each device. The model efficiently checks the SLA against the current configuration using computation tree logic model checking. By following possible decision paths for a specific flow from source to destination, properties can be checked at each hop, and assessments can be made on how well configurations adhere to the specified agreement. The model also covers configuration debugging given a specific QoS violation.

The resource utilization of servers (such as CPU, memory) is an important performance metric in data center networks (DCNs). The cloud platform supported by DCNs aims to achieve high average resource utilization while guaranteeing the quality of cloud services. Previous papers designed various efficient virtual machine placement schemes to increase the average resource utilization and decrease the server overload ratio. Unfortunately, most of virtual machine placement schemes did not contain the service level agreements (SLAs) and statistical methods. In this paper, we propose a correlation-aware virtual machine placement scheme that effectively places virtual machines on physical machines. First, we employ neural networks model and factor model to forecast the resource utilization trend data according to the historical resource utilization data. Second, we design three correlation-aware virtual machine placement algorithms to enhance resource utilization while meeting the user-defined SLAs. The simulation results show that the efficiency of our virtual machine placement algorithms outperforms the generic algorithm and constant variance algorithm by about 15%-30%.

A Service Level Agreement (SLA) establishes the trustworthiness of service providers and consumers in several domains; including the Internet of Things (IoT). Given the proliferation of Blockchain technology, we find it compelling to reconsider the assumption of trust and centralised governance typically practised in SLA management including monitoring, compliance assessment, and penalty enforcement. Therefore, we argue that, such critical tasks should be operated by blockchain-based smart contracts in a non-repudiable manner beyond the influence of any SLA party. This paper envisions an IoT scenario wherein a firefighting station outsources end-to-end IoT operations to a specialised service provider. The contractual relationship between them is governed by an SLA which stipulates a set of quality requirements and violation consequences. The main contribution of this paper lies in designing, deploying and empirically experimenting a novel blockchain-based SLA monitoring and compliance assessment framework in the context of IoT. This is done by utilising Hyperledger Fabric (HLF), an enterprise-grade blockchain technology. Our work highlights a set of considerations and best practice at two sides, the IoT application monitoring-side and the blockchain-side. Moreover, it experimentally validates the reliability of the proposed monitoring approach, which collects relevant metrics from each IoT component and examines them against the quality requirements stated in the SLA. Finally, we propose a novel design for smart contracts at the blockchain-side, analyse and benchmark the performance, and demonstrate that the new design proves to successfully handle Multiversion Concurrency Control (MVCC) conflicts typically encountered in blockchain applications, while maintaining sound throughput and latency.

The emerging transformation from a product oriented economy to a service oriented economy based on Cloud environments envisions new scenarios where actual QoS (Quality of Service) mechanisms need to be redesigned. In such scenarios new models to negotiate and manage Service Level Agreements (SLAs) are necessary. An SLA is a formal contract which defines acceptable service levels to be provided by the Service Provider to its customers in measurable terms. SLAs are an essential component in building Cloud systems where commitments and assurances are specified, implemented, monitored and possibly negotiable. This is meant to guarantee that consumers’ service quality expectations can be achieved. In fact, the level of customer satisfaction is crucial in Cloud environments, making SLAs one of the most important and active research topics. This paper presents an SLA implementation for negotiation, monitoring and renegotiation of agreements for Cloud services based on the CMAC (Condition Monitoring on A Cloud) platform. CMAC offers condition monitoring services in cloud computing environments to detect events on assets as well as data storage services.

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.

C-SLA-MLO: Enhancing SLA Compliance in Industrial Wi-Fi through Cooperative Multilink Operation

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.

This paper presents the contributions of the phd thesis “Mechanisms for management of SLA for Virtual Software Defined Networks based on QoS Classes”. Over the years the Internet has become the primary means of communication, where the users expect to access the Internet anytime, anywhere, and with a certain quality level. As a consequence, in the past few years the traffic demand to Internet access has increased. However, since the current Internet does not guarantee Quality of Service (QoS) and Quality of Experience (QoE), the companies apply a Service Level Agreements (SLA) with Internet Service Providers (ISPs). In this way, the Internet service providers aim to improve utilization of network resources and service delivery to the users through the deployment of Virtual Networks (VNs) over Software Defined Networks (SDNs), called virtual software defined networks (VSDNs). However, the management of this type of environment still presents open issues. In this context, a set of mechanisms to manage VSDN was developed. The objectives of the developed mechanisms are to negotiate, to deploy and to adapt the VSDNs according to the current state of the network infrastructure and the SLA definition.

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.

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) 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.

This study evaluated facility operations services by means of exploring key metrics like Mean Time to Repair (MTTR), Mean Time Between Failures (MTBF), Service Level Agreement (SLA) targets, Reliability (R(t)) and Failure Rate (λ). The analysis was carried out in three regions namely Eastern region, Northern region, and Western region by x-raying 10 months of data collected from operational records, incident logs, and SLA compliance results from a facilities maintenance company in Nigeria. The Western region was faced with the highest number of incidents, peaking at 933 in the month of April, while that of the Eastern region recorded 371 incidents in the month of May, and the Northern region had 166 incidents in the month of August all in year 2024. MTBF was used to measure failure frequency, while the MTTR provided insights into incident resolution times. In the Western region, the MTTR averaged 2.5 hours in in the month of April, resulting to operational inefficiencies. The facility efficiency was measured against a 95% SLA target and the performance shows a drop to about 76% in the month of March but there was efforts along the line that shows recovery to 100% by the month of September and October 2024. The reliability analysis also showed that the high incident rates negatively impacted operational continuity. The outcome of this study emphasizes the significance of constantly monitoring the MTBF, the MTTR, and the SLA compliance to improve operational efficiency. The findings also highlight the Western region’s operational challenges and the need for focused on improvements in the maintenance and repair processes method of pattern to attain steady 99-100% efficiency across all regions.