Cloud computing

Open Access Article

1 - A Proposed Method of Decentralized Load Balancing Algorithm in Heterogeneous Cloud Environments
S. Hourali S. Jamali F. Hourali

20.1001.1.16823745.1395.14.2.16.0

One of the key strategies to improve the efficiency is load balancing. Choosing the appropriate VM to do any task, is function of various parameters such as the amount of required resources like CPU, memory, the size of VM resource, cost and maturity of VMs. In this pap More

One of the key strategies to improve the efficiency is load balancing. Choosing the appropriate VM to do any task, is function of various parameters such as the amount of required resources like CPU, memory, the size of VM resource, cost and maturity of VMs. In this paper, by considering each of these criteria and design objectives such as load balancing, reducing the rate of create new VM, and VM migration, we modeling the problem in terms of effective parameters in performance. Then, we solving this model by using the PROMETHEE method, which is one of the most widely used method for MADM problems. In this method, selecting the best VM occurs based on the value assigned to each of criteria which is calculated based on fuzzy logic. To evaluate the performance of this approach, the necessary simulations have been carried out on CloudSim simulator and shown that the proposed method has better performance compared to FIFO, DLB and WRR methods on average in terms of response time, rate of success tasks, load variation and rate of VM migration. Manuscript profile

Open Access Article

2 - Mobility-Aware and Fault-Tolerant Computation Offloading for Mobile Cloud Computing
R. Roostaei Z. Movahedi

20.1001.1.16823745.1396.15.4.14.9

Nowadays, Internet of Things (IoT) has emerged as an important field in information and communication technologies. Despite the progress of networks and communication technologies, the development of IoT has encountered some challenges mainly with regard to computation More

Nowadays, Internet of Things (IoT) has emerged as an important field in information and communication technologies. Despite the progress of networks and communication technologies, the development of IoT has encountered some challenges mainly with regard to computation power, battery lifetime and memory of mobile devices. In order to overcome these challenges, mobile cloud computing has been raised which uses the cloud storage space and computation power to extend the capabilities of mobile devices. In this regard, some of application’s components are selected to be offloaded to the cloud in order to optimize the execution time and energy consumption of application. Since the mobility has an important effect on the acquired condition of the access network and the quality of the connection, the mobility should be considered while selecting components for offloading. Although a number of mobility-aware offloading approaches has been already proposed, these works suffer from the lack of an appropriate mobility-model, ignorance of the fault-tolerance capability and use of only coarse-grain offloading. In order to address these issues, we propose a mobility-aware offloading scheme which uses the user mobility Markov chain and the fault tolerance capability in order to optimize the offloading decision. Evaluation results show that our proposed method significantly outperforms the existing alternatives, reaching respectively up to 75 and 65 percent enhancement in terms of the execution time and the energy consumption. Manuscript profile

Open Access Article

3 - Quality of Service Aware Service Composition Method Using Biogeography-Based Optimization (BBO) Algorithm
S. Saligheh B. Arasteh

20.1001.1.16823745.1398.17.3.10.7

Fast development in the utilization of cloud computing leads to publishing more cloud services on the cloud environment. The single and simple services cannot satisfy the users’ real-world complex requirements. To create a complex service, it is necessary to select and More

Fast development in the utilization of cloud computing leads to publishing more cloud services on the cloud environment. The single and simple services cannot satisfy the users’ real-world complex requirements. To create a complex service, it is necessary to select and compose a set of simple services. Therefore, it is essential to embed a service composition system in cloud computing environment. Service composition is one of the important NP-hard problems in the service-oriented computings. In this paper, a biogeography-based optimization algorithm is used to create the optimal composite-services. The proposed method was simulated and executed on five different scenarios with different number of tasks and candidate services. The throughput of the proposed method, genetic algorithm and particle swarm optimization algorithm are respectively 0.9997, 0.9975 and 0.9994; furthermore, the reliability of these methods are respectively 0.9993, 0.9980 and 0.9982. The results of simulations indicate that the proposed method outperforms the previous methods in the same conditions in terms of throughput, successability, reliability, response time, and stability. Manuscript profile

Open Access Article

4 - Green Cloud Computing with Reduced Energy Consumption in Live Migration Prioritizing Services
Mohammad Rostami Salman Goli

20.1001.1.16823745.1399.18.4.15.1

Today, the rapid growth in cloud computing resources usage has increased energy consumption in data centers. Green cloud computing goal is to decrease the energy consumption of data centers. In the meantime, service aggregation is a good method to reduce energy consumpt More

Today, the rapid growth in cloud computing resources usage has increased energy consumption in data centers. Green cloud computing goal is to decrease the energy consumption of data centers. In the meantime, service aggregation is a good method to reduce energy consumption in these systems. Existing aggregation methods with unnecessary migration, the unbalanced workload of hosts, and ignoring the relationship between services may reduce the quality of service and increase energy consumption. Therefore, in this study, by migrating the necessary services based on priority (including the number of children, the level and communication cost of each service), from hosts with the unbalanced workload to hosts that contain partner services, the productivity of available resources is improved and the energy consumption is decreased. Live services migration based on prioritizing and minimizing the number of migrations can also lead to response time decrease and system efficiency increase. The proposed method can lead to an 11.79% decrease in energy consumption, a 12.15% reduction in the number of service migrations, and a 1.55% increase in the number of hosts that have been shut down. Manuscript profile

Open Access Article

5 - Reliable and Energy Efficient Deployment Optimization of Internet of Things Applications in Cloud and Fog Infrastructure by Using Cuckoo Search Algorithm
Yaser Ramzanpoor میرسعید حسینی شیروانی

20.1001.1.16823745.1400.19.4.11.4

Deployment applications of internet of things (IoT) in fog infrastructure as cloud complementary leads effectively computing resource saving in cloud infrastructure. Recent research efforts are investigating on how to better exploit fog capabilities for execution and su More

Deployment applications of internet of things (IoT) in fog infrastructure as cloud complementary leads effectively computing resource saving in cloud infrastructure. Recent research efforts are investigating on how to better exploit fog capabilities for execution and supporting IoT applications. Also, the distribution of an application’s components on the possible minimum number of fog nodes for the sake of reduction in power consumption leads degradation of the service reliability level. In this paper, a hybrid meta-heuristic algorithm based on cuckoo search algorithm is presented for static deployment the components of IoT applications on fog infrastructure in the aim of trade-off between efficient power usage, reduction in the effect of one point of failure and boosting the application reliability against failure. The results of simulations show that the proposed approach in this paper reduces the power consumption of fog network and meets the quality of service requirement of IoT application with the high reliability level. Manuscript profile

Open Access Article

6 - Multi-Objective Optimization Solution for Virtual Machine Placement Problem in Cloud Datacenters with Minimization of Power Consumption and Resource Dissipation Perspectives by Simulated Annealing Algorithm
Mirsaeid Hosseini Shirvani

20.1001.1.16823745.1400.19.2.15.4

Nowadays, cloud computing industry has been transformed to a new supply chain between cloud service providers and service requesters. To this end, cloud service provisioning in datacenters is procured via virtualization platforms in which it can potentially increase the More

Nowadays, cloud computing industry has been transformed to a new supply chain between cloud service providers and service requesters. To this end, cloud service provisioning in datacenters is procured via virtualization platforms in which it can potentially increase the utilization of computing resources at infrastructure level. Inefficient virtual machine placement (VMP) schemes lead lower system utilization, increase of resource dissipation, and high rate of power consumption. Therefore, this paper formulates VMP problem on physical machines of cloud datacenters to a multi-objective optimization problem with minimization of both power consumption and resource dissipation perspectives which is computationally NP-Hard. Since the most meta-heuristic algorithms are designed for continuous optimization problems and are also susceptible to get stuck in local optimum, to figure out this combinatorial problem an optimization algorithm based on simulated annealing algorithm commensurate with discrete search space of stated problem is extended, so that the possibility of getting stuck in local optimum is reduced. To validate the proposed approach, several scenarios are introduced and conducted. Reported results from simulation of different scenarios show that the proposed approach outperforms against other existing approaches in terms of reduction in power consumption, resource dissipation, and the number of active server in use. Manuscript profile

Open Access Article

7 - Provide an Energy-aware Markov Based Model for Dynamic Placement of Virtual Machines in Cloud Data Centers
mehdi rajabzadeh Abolfazl Toroghi Haghighat Amir Masoud Rahmani

20.1001.1.16823745.1401.20.1.4.8

The use of energy-conscious solutions is one of the important research topics in the field of cloud computing. By effectively using virtual machine placement and aggregation algorithms, cloud suppliers will be able to reduce energy consumption. In this paper, a new mode More

The use of energy-conscious solutions is one of the important research topics in the field of cloud computing. By effectively using virtual machine placement and aggregation algorithms, cloud suppliers will be able to reduce energy consumption. In this paper, a new model is presented that seeks to achieve the desired results by improving the algorithms and providing appropriate methods. Periodic monitoring of resource status, proper analysis of the data obtained, and prediction of the critical state of the servers using the proposed Markov model have reduced the number of unnecessary migrations as much as possible. The combination of genetic algorithm and simulated annealing in the replacement section along with the definition of the adsorbent Markov chain has resulted in better and faster performance of the proposed algorithm. Simulations performed in different scenarios in CloudSim show that compared to the best algorithm compared, at low, medium and high load, energy consumption has decreased significantly. Violations of service level agreements also fell by an average of 17 percent. Manuscript profile

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