Mobile Cloud IoT for Resource Allocation with Scheduling in Device- Device Communication and Optimization based on 5G Networks

Internet of Things (IoT) is revolutionising technical environment of traditional methods as well as has applications in smart cities, smart industries, etc. Additionally, IoT enabled models' application areas are resource-constrained as well as demand quick answers, low latencies, and high bandwidth, all of which are outside of their capabilities. The above-mentioned issues are addressed by cloud computing (CC), which is viewed as a resource-rich solution. However, excessive latency of CC prevents it from being practical. The performance of IoT-based smart systems suffers from longer delay. CC is an affordable, emergent dispersed computing pattern that features extensive assembly of diverse autonomous methods. This research propose novel technique resource allocation and task scheduling for device-device communication in mobile Cloud IoT environment based on 5G networks. Here the resource allocation has been carried out using virtual machine based markov model infused wavelength division multiplexing. Task scheduling is carried out using meta-heuristic moath flame optimization with chaotic maps. So, by scheduling tasks in a smaller search space, system resources are conserved. We run simulation tests on benchmark issues and real-world situations to confirm the effectiveness of our suggested approach. The parameters measured here are resource utilization of 95%, response time of 89%, computational cost of 35%, power consumption of 38%, QoS of 85%

Novel Load Balancing Optimization Algorithm to Improve Quality-of-Service in Cloud Environment

Scheduling cloud resources calls for allocating cloud assets to cloud tasks. It is possible to improve scheduling outcomes by treating Quality of Service (QoS) factors as essential constraints. However, efficient scheduling calls for improved optimization of QoS parameters, and only a few resource scheduling algorithms in the available literature do so. The primary objective of this paper is to provide an effective method for deploying workloads to cloud infrastructure. To ensure that workloads are executed efficiently on available resources, a resource scheduling method based on particle swarm optimization was developed. The proposed method's performance has been measured in the cloud. The experimental results prove the efficiency of the proposed approach in reducing the aforementioned QoS parameters. Several metrics of algorithm performance are used to gauge how well the algorithm performs

Furthering the Growth of Cloud Computing by Providing Privacy as a Service

The evolution of Cloud Computing as a viable business solution for providing hardware and software has created many security concerns. Among these security concerns, privacy is often overlooked. If Cloud Computing is to continue its growth, this privacy concern will need to be addressed. In this work we discuss the current growth of Cloud Computing and the impact the public sector and privacy can have in furthering this growth. To begin to provide privacy protection for Cloud Computing, we introduce privacy constraints that outline privacy preferences. We propose the expansion of Cloud Service Level Agreements (SLAs) to include these privacy constraints as Quality of Service (QoS) levels. This privacy QoS must be agreed upon along with the rest of the QoS terms within the SLA by the Cloud consumer and provider. Finally, we introduce Privacy as a Service (PraaS) to monitor the agreement and provide enforcement if necessary

Multimedia Storage System Providing QoS in Cloud Based Environment

Cloud computing and mobile computing are moderately new trend in Information Technology which are growing rapidly. Mobile devices are replacing personal computers by joining large mobile networks and are effortlessly switching between different network providers. Currently, to maintain network connectivity all the time different service handover mechanisms is used so that cloud services can be accessed by user without any interruption. In this scenario, if user mobility is considered, then he is connected to its local cloud to access the different cloud services. As user is moving from one geographical location to another because of this mobility factor network congestion increases which causes degradation in QoS. For this reason a framework is introduced which will deliver services to the users to improve QoS in order to provide better QoE to the clients. In this paper, we are further developing this framework in which an algorithm is designed in service delivery layer which will help for better solution to the efficient management of network resources while providing a high QoE for the clients. And as the demand for specific services increases in a location, using this framework it will be more efficient to move those services closer to that location. This framework will help to reduce high traffic loads due to multimedia streams and will offer service providers an automated resource allocation and management mechanism for their services

The Quality Demonstration projected in Cloud supervisions

A defender amongst the preeminent vital current examinations inside of the Cloud Computing provisioning is that the Service Level Agreement and its application in ensuring the gave appropriated figuring organizations. The strategy for giving appropriated organizations has been reconsidered as partner result of using dispersed figuring that as a region of flip has well known new challenges with every suppliers and customers. Estimation the character of circulated processing procural from the client's point of view is basic accordingly on surety that the organization fits in with the sum decided inside of the understanding; this is regularly typically implied as Quality of skill. There has been some work in estimation the standard of Service as a strategy for ensuring the organization level in dispersed processing. One in everything about troubles with estimation the standard of aptitude parameters is that gigantic quantities of the parameters are subjective, and thusly makes it challenging to portray a deliberate metric to be utilized for instrumenting the gave organization. This paper depicts a working - headway investigate that attempts to portray partner assessed metric that may be utilized as partner execution live to benchmark SaaS applications in appropriated processing. Such a metric are significant to cloud suppliers and also buyers for ensuring that the sent organizations meet the shopper wants. The conveyed registering applications brings another course of action of data security issues. The cloud security model see capable of SLA (Service Level Agreement) was centered on. From the assurance troubles of conveyed figuring , appropriated registering security risks was compound widely, the organization level understandings was augmented, the CSLA (Cloud Service Level Agreement) structure was anticipated, the cloud security course of action was arranged, the cloud security level auxiliary designing and cloud organizations evaluating and charging models was anticipated

Load Balancing and Resource Allocation Model for SaaS Applications with Time and Cost constraints forcloud-computing

Instead of Traditional Software, nowadays we are using Cloud Computing. It enables the on-going revenue for software providers..Advancement of Cloud Computing due to use of well established research in Web Services, networks, utility computing and virtualization has resulted in many advantages in cost, flexibility and availability for service users. These advantages has further increased the demand for Cloud Services, increasing both the Cloud's customer base and the scale of Cloud installations. This has resulted in many technical issues in Service Oriented Architectures and Internet of Services (IoS) type applications such as high availability and scalability, fault tolerance. Central to these issues is the establishment of effective load balancing techniques. In this paper focus on the load balancing and resources provisioning approaches.Here, using the linear programming approach for dynamically allocates the resources with balancing the load.Mainly focus on the time and cost constraints. DOI: 10.17762/ijritcc2321-8169.15072

An Optimal Virtual Machine Placement Method in Cloud Computing Environment

Cloud computing is formally known as an Internet-centered computing technique used for computing purposes in the cloud network. It must compute on a system where an application may simultaneously run on many connected computers. Cloud computing uses computing resources to achieve the efficiency of data centres using the virtualization concept in the cloud. The load balancers consistently allocate the workloads to all the virtual machines in the cloud to avoid an overload situation. The virtualization process implements the instances from the physical state machines to fully utilize servers. Then the dynamic data centres encompass a stochastic modelling approach for resource optimization for high performance in a cloud computing environment. This paper defines the virtualization process for obtaining energy productivity in cloud data centres. The algorithm proposed involves a stochastic modelling approach in cloud data centres for resource optimization. The load balancing method is applied in the cloud data centres to obtain the appropriate efficiency

Towards Automated and Optimized Security Orchestration in Cloud SLA

In cloud computing, providers pool their resources and make them available to customers. Next-generation computer scientists are flocking to the cutting-edge field of cloud computing for their research and exploration of uncharted territory. There are still several barriers that cloud service providers must overcome in order to provide cloud services in accordance with service level agreements. Each cloud service provider aspires to achieve maximum performance as per Service Level Agreements (SLAs), and this is especially true when it comes to the delivery of services. A cloud service level agreement (SLA) guarantees that cloud service providers will satisfy the needs of large businesses and offer their clients with a specified list of services. The authors offer a web service level agreement–inspired approach for cloud service agreements. We adopt patterns and antipatterns to symbolize the best and worst practices of OCCI (Open Cloud Computing Interface Standard), REST (Representational State Transfer), and TOSCA (Topology and Orchestration Specification for Cloud Applications) with DevOps solutions, all of which API developers should bear in mind when designing APIs. When using this method, everything pertaining to the cloud service, from creation to deployment to measurement to evaluation to management to termination, may be handled mechanically. When distributing resources to cloud apps, our system takes into account the likelihood of SLA breaches and responds by providing more resources if necessary. We say that for optimal performance, our suggested solution should be used in a private cloud computing setting. As more and more people rely on cloud computing for their day-to-day workloads, there has been a corresponding rise in the need for efficient orchestration and management strategies that foster interoperability

Cloud and HPC Headway for Next-Generation Management of Projects and Technologies

In the last decade, cloud computing has changed dramatically. More providers and administration contributions have entered the market, and cloud infrastructure, once limited to single-provider data centers, is expanding. This article discusses the shifting cloud foundation and the benefits of decentralizing computing from data centers. These patterns necessitate novel cloud computing architectures. These models may affect linking people and devices, data-intensive computing, the service space, and self-learning frameworks. Finally, we compiled a list of issues to consider while assessing modern cloud frameworks. Architectural and urban design projects breach scale and predictability constraints and seek enhanced competency, maintainability, energy performance, and cost-efficiency. Simulation and large-scale information processing drive this cycle. Advances in calculations and computer power help address the complex elements of a coordinated whole-structure framework. Adaptability is a barrier to the configuration, control, and development of whole-system frameworks. This position paper proposes several solutions for semi-or fully automated projects, such as short-plan boundary space exploration, large-scope high-accuracy simulation, and integrated multidisciplinary development. These computer-intensive operations were previously only accessible to the exam network. Once empowered by cloud computing and high-performance computing, these methods can stimulate intelligent plan measures, leading to enhanced results and shorter development times