Performance impact of imitation in Multi-Objective Security Service Provisioning

2013 ◽  
Author(s):  
Jalal Raissi
Keyword(s):  
Service Provisioning ◽  
Performance Impact ◽  
Multi Objective ◽  
Security Service

scholarly journals AN Internet of Things based Software Defined Security Service Provisioning Framework

2020 ◽  
Vol 8 (6) ◽  
pp. 3358-3362
Keyword(s):  
Internet Of Things ◽  
Software Defined Networking ◽  
System Structure ◽  
Service Provisioning ◽  
Social Event ◽  
The Past ◽  
Programming Framework ◽  
Security Service ◽  
Academic Network

Software Defined Networking (SDN) is a propelling system structure perspective that spotlights on the parcel of control and data planes. SDN gets creating care both from the academic network and adventure, all through an immense number of utility spaces. The proposal of extended progression in system purposes and diminished expense for framework directors has gotten over the frameworks organization world to the innovative and farsighted of Software Defined Networking (SDN). With the surge of widely inclusive detectable quality over the system and the likelihood to programming framework contraptions, architects have rushed to remunerate a variety generally SDN-pleasant hardware, programming and organizations. Regardless, amidst this free for all of movement, one key segment has least troublesome not exceptionally far in the past entered the discourse: organize protection. In this article, confirmation in SDN is considered offering both the investigation social event and industry advances with respect to this issue.

scholarly journals Oppositional Multi-Objective Particle Swarm Based Resource Optimized Job Scheduler for Load Balanced Cloud Service Provisioning

2020 ◽  
Vol 9 (1) ◽  
pp. 1848-1853
Keyword(s):  
Job Scheduling ◽  
Virtual Machines ◽  
Fitness Function ◽  
Particle Swarm ◽  
Cloud Service ◽  
Experimental Result ◽  
Function Evaluation ◽  
Minimal Amount ◽  
Service Provisioning ◽  
Multi Objective

Job scheduling is a key problem to be resolved in cloud service provisioning for balancing load and improving resource optimization performance. Recently, many research works have been designed for performing job scheduling using different techniques. However, job scheduling efficiency (SE) was not sufficient. In order to addresses the above limitations, Oppositional Multi-Objective Particle Swarm Based Resource Optimized Job Scheduling (OMPS-ROJS) technique is proposed. The designed OMPS-ROJS technique balances the load on computer resources by distributing tasks to available resources with higher efficiency. The OMPS-ROJS technique at first takes number of incoming user requested jobs to cloud server (CS) as input. Then, OMPS-ROJS technique develops Oppositional Particle Swarm Multi-Objective Optimization (OPSMO) algorithm in order to determine the optimal virtual machines for each input user requested jobs with a minimal amount of time. On the contrary to conventional works, OPSMO algorithm assume multi-objective such as energy, makespan, bandwidth, memory and cost for fitness function evaluation. This helps for OMPS-ROJS technique to find out the virtual machine which contains maximum resource availability as best to carry out the user requested jobs. Therefore, OMPS-ROJS technique efficientlybalancedynamic loads on CS through scheduling user requested jobs with a minimal time.Thus, OMPS-ROJS technique enhances the cloud service provisioning performance as compared to conventional works. Experimental result evident that OMPS-ROJS technique enhances the SE and lessen the EC as compared to conventional works.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

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