TABLE 4 - uploaded by Sourav Banerjee
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Cloud Computing is known as a provider of dynamic services. It utilizes a very large, scalable and virtualized resource over the Internet. So many industries have joined this bandwagon nowadays. One of the major research issues is to maintain good Quality of Service (QoS) of a Cloud Service Provider (CSP). The QoS encompasses different parameters,...
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For a fixed graph $H$, the reconfiguration problem for $H$-colourings (i.e. homomorphisms to $H$) asks: given a graph $G$ and two $H$-colourings $\varphi$ and $\psi$ of $G$, does there exist a sequence $f_0,\dots,f_m$ of $H$-colourings such that $f_0=\varphi$, $f_m=\psi$ and $f_i(u)f_{i+1}(v)\in E(H)$ for every $0\leq i<m$ and $uv\in E(G)$? If the...
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Since the CSP dichotomy conjecture has been established, a number of other dichotomy questions have attracted interest, including one for list homomorphism problems of signed graphs. Signed graphs arise naturally in many contexts, including for instance nowhere-zero flows for graphs embedded in non-orientable surfaces. The dichotomy classification...
Two graph parameters are equivalent if, for every graph class, they are either both bounded or both unbounded. We provide a list of graph parameters equivalent to the acyclic chromatic number, which contains in particular the 2-edge-colored chromatic number. Recently, the CSP dichotomy conjecture has been reduced to the case of 2-edge-colored homom...
Citations
... is defined pattern has not been under the principle of SLA [20]. ...
Due to the purpose of this study that reducing power consumption in the cloud network is based on load balancing, the fitness function measures the load balance between cloud network and servers (the hosts). This technique is appropriate for handling the resource optimization challenges, due to the ability to convert the load balancing problem into an optimization problem (reducing imbalance cost). In this research, combining the results of the particle swarm genetic optimization (PSGO) algorithm and using a combination of advantages of these two algorithms lead to the improvement of the results and introducing a suitable solution for load balancing operation, because in the proposed approach (LBPSGORA), instead of randomly assigning the initial population in the genetic algorithm, the best result is procured by putting the initial population. The LBPSGORA method is compared with PSO, GA, and hybrid GA-PSO. The execution cost, load balancing, and makespan have been evaluated and our method has performed better than similar methods.
... RR is generally used in web-servers which generally have HTTP requests with similar natures. This defined algorithm is inconsistence with the principle of service level agreement [28]. ...
... In [28] an architecture is suggested which is aimed at management of energy in virtualized data centers. In this architecture, resources are managed under local and global levels. ...
p>There are several physical data centers in cloud environment with hundreds or thousands of computers. Virtualization is the key technology to make cloud computing feasible. It separates virtual machines in a way that each of these so-called virtualized machines can be configured on a number of hosts according to the type of user application. It is also possible to dynamically alter the allocated resources of a virtual machine. Different methods of energy saving in data centers can be divided into three general categories: 1) methods based on load balancing of resources; 2) using hardware facilities for scheduling; 3) considering thermal characteristics of the environment. This paper focuses on load balancing methods as they act dynamically because of their dependence on the current behavior of system. By taking a detailed look on previous methods, we provide a hybrid method which enables us to save energy through finding a suitable configuration for virtual machines placement and considering special features of virtual environments for scheduling and balancing dynamic loads by live migration method.</p
... The proposed work is an additional improvement strategy over the existing IRRCSA [14] using optimal time quantum (OTQ). The use of OTQ in cloudlet scheduling policy has brought a great improvement in terms of increasing the QoS of CSP [28,29]. The QoS of CSP [30] encompasses various issues like -WT, TAT, [23,24] CS, MS etc. ...
Cloud computing is one of the most emerging technologies which has created a revolution in the High performance Computing (HPC) domain. The term Quality of Service (QoS) plays a vital role in the formation of more flexible integration of various technologies. The Waiting Time (WT), Turnaround Time (TAT), Context Switching (CS) and Makespan (MS) are the primary parameter that has great impact on the scheduling of cloudlets. The Proposed algorithm has improved the resource utilization system of the existing Round Robin Algorithm (RRA) and Improved Round Robin Cloudlet Scheduling Algorithm (IRRCSA) by introducing the concept of dynamically calculated Time Quantum (TQ) for each virtual machine (VM) according to the allocated cloudlets. This new approach in cloudlet scheduling drastically reduced average WT, average TAT and Number of CS of the VMs, which further enhanced the capability of cloud service providers (CSPs) to provide better QoS.
... In Banerjee et al. (2014), the proposed scheme has achieved the customer as a service CAAS using internet techniques. However, it has not discussed dynamicity, modeling, and simulation. ...
... In [50], the proposed scheme has achieved the customer as a service CAAS using internet techniques. However, it has not discussed dynamicity, modeling, and simulation. ...
The emergence of cloud computing has gained massive attention for both industry and academia. Resource management in cloud computing is a challenging task due to the complex nature of user requirements and fluctuating workloads. The current research has primarily focused on scheduling algorithms, load balancing, and efficient resource sharing in computational clouds, however; classifying state information collection strategies have largely been neglected. This paper presents a survey of Information Collection Centric Techniques (ICCT) for cloud resource management. The paper contributes by providing a thematic taxonomy of the current state-of-the-art techniques to present a comprehensive classification of the state information collection mechanisms. Moreover, a thorough comparative analysis based on various parameters of the state-of-the-art ICCT have been carried out to highlight their merits and demerits. Finally, the paper concludes by presenting recommendations, issues and open research challenges that should be considered while proposing and designing novel resource management techniques.
... The cloud computing enables the delivery of IT resources over the Internet and follows an on-demand service model where the users are charged based on their consumption. There are various types of Cloud providers into hierarchy of as-a-service terms [4,5]-software as a service (SaaS), platform as a service (PaaS), infrastructure as a service (IaaS), database as a service (DaaS), identity as a service (IdaaS), etc. Moreover, they offer the flexibility, elasticity and scalability to acquire or release resources with varying configuration to best suit the requirements of an application. ...
Cloud computing offers the proficiency to use computing and storage resources on a metered basis and reduces the investments in Information Technology domain. This paper highlights a major research issue, i.e., providing good quality of service (QoS) to the cloud users. The QoS is associated with several parameters such as completion time, response time, turnaround time (TAT), waiting time (WT), bandwidth. A new cloudlet scheduling algorithm—improved round robin cloudlet scheduling algorithm—has been proposed which improves the TAT, WT and number of context switching. It enhances the resource utilization. The experimental results are obtained by CloudSim toolkit extending few base classes and compared by classical round robin algorithm.
Distribution network of smart grid imposes higher requirement on data processing of next-generation consumer electronics devices. Container-based cloud-edge-device collaboration improves quality of service (QoS) by flexible data offloading and parallel data processing. However, the matching among consumer electronics devices, servers, and containers, and container competition further complicates the problem. In this paper, we propose three-dimensional learning-matching-based joint selection algorithm of server and container for multi-service data processing. The formulated problem is firstly reduced to a two-dimensional problem by combination-based dimension reduction. Then, it is solved by the proposed dynamic learning-matching price rising mechanism based on service priority, data size, and upper confidence bound. By avoiding low-priority service preempting container resources of high-priority service, simulation results validate that the proposed algorithm has superior delay reduction performance.
