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Software-Defined Networking Based on Load Balancing Using Mininet
Abstract
In traditional networking devices, there is a tight coupling of data plane and control plane. It handles a huge volume of traffic on the Internet which is not possible in traditional networking devices. The strategy emerged of disassociating the control plane from the data plane is defined as software-defined networking (SDN). The rapid increase in the number of Internet users is becoming a difficult task for conventional load balancers to handle network traffic. SDN provides power over the network from the centralized controller to distinguish between the control plane and the data plane. SDN is a prominent technology in today’s Internet. Nowadays, our networks handle the extensive amount of traffic that serves the hundreds and thousands of clients where it is very difficult for the single server to handle such a huge load. To overcome this problem, the load balancing technique came into existence. The main purpose of this work is to show how SDN applications can be created without using any controller and analyze the efficiency/effectiveness of load balancing algorithms based on SDN.
... Presently, the exponential increase of real-time applications usually requires rigorous guidance for Quality of Service (QoS) as well as Quality of Experience (QoE) forces network software developers to develop communication protocols which deploy expected performance guidance. Therefore, the enormous use of the web has turned it into a portion of one's society 's crucial infrastructures [6,25]. Meanwhile physical infrastructure and interface design, and online media performance is an absolutely challenging task. ...
With the increasing growth in the network and latest technologies by which people communicates via voice or data and modifies the radio devices easily and cost effectively. Software defined radio brings the flexibility, power and efficiency including cloud and big data, control and management of the traditional networks has raised the challenges for the development of multimedia applications. Multimedia applications require to handle the large amount of data at the servers which has increased the load on them. To resolve this issue, Software Defined Networking (SDN) came into existence which makes the management of the network more conformable. To satisfy the constraints of Quality of Service (QoS) and Quality of Experience (QoE) with the limited network availability, one of the keynotes that have been taken into consideration is the load balancing. Therefore, many servers can be used with the load balancers which behave as the front end. The present paper aims to reflect impact on the efficiency of the usage of software-defined networks service in various multimedia applications. A genetic load balancing algorithm (GLBA) is proposed and is implemented on POX controller with mininet emulator in python language to compute its effectiveness and efficiency. Validation of GLBA for 100 to 600 users over server load, weighted round robin, round robin, dynamic server and LBBSRT algorithms with parameters, throughput, response time, memory and CPU utilization has proved the significance of proposed algorithm.
With improvements in wireless technology and digital electronics, a variety of small devices have begun to be employed in various aspects of daily life. These devices have the ability to sense, compute, and communicate. Low-power radios, a number of smart sensors, and integrated CPUs are common components (Central Processing Units). These devices are being used to create a wireless sensor network (WSN), which is required for sensing and monitoring environmental variables. Similar to WSNs, the concept of the internet of things (IoT) is growing rapidly, with IoT being defined as the connecting of identifiable items through a connection to the internet for sensing and monitoring purposes. This chapter presents the evolution of WSN and IoT, growth of WSN. It also discusses the applications of the WSN and later the technologies in WSN and IoT are described. Furthermore, it resolves the research issues in the integration of WSN and IoT.KeywordsWireless sensor networks (WSN)Internet of things (IoT)ApplicationsTechnologiesResearch issues
In traditional network devices, tight coupling of data plane with the control plane so large amount of traffic on the web is not correctly handled by the Traditional network devices. The emerging strategy that decoupled the data plane from control plane is called Software Defined Networking (SDN). Control plane of these devices act like a brain or master. It is also called Software Defined networking controller or Openflow controller. Data plane is called slave that behave according to the instructions given by the master or control plane. To convert a data plane into powerful network devices we have to create Firewall, Load balancer, Intrusion Detection system applications and then run that applications at management plane that is on top of control plane. In such a manner we can convert data plane into powerful network devices according to the application. The application that we have created on the top of control plane is load balancer application that convert the dumb data plane into load balancer. Load balancer architecture consists of number of servers and clients which distributed the client traffic among number of servers based on particular strategy. There are number of strategies are available such as Round Robin, random policy. Each load balancing policy has some advantages and disadvantages. We created "least delay dynamic weighted round robin (LDDWRR)" strategy in this paper and run on the top of SDN controller. Then we evaluate the result of our load balancing strategy by comparing with the round robin strategy. Mininet is used for the experiment and controller that is used as control plane is called POX controller.
The software defined networking (SDN) paradigm separates the control plane from the data plane, where an SDN controller receives requests from its connected switches and manages the operation of the switches under its control. Reassignments between switches and their controllers are performed dynamically, in order to balance the load over SDN controllers. In order to perform load balancing, most dynamic assignment solutions use a central element to gather information requests for reassignment of switches. Increasing the number of controllers causes a scalability problem, when one super controller is used for all controllers and gathers information from all switches. In a large network, the distances between the controllers is sometimes a constraint for assigning them switches. In this paper, a new approach is presented to solve the well-known load balancing problem in the SDN control plane. This approach implies less load on the central element and meeting the maximum distance constraint allowed between controllers. An architecture with two levels of load balancing is defined. At the top level, the main component called Super Controller, arranges the controllers in clusters, so that there is a balance between the loads of the clusters. At the bottom level, in each cluster there is a dedicated controller called Master Controller, which performs a reassignment of the switches in order to balance the loads between the controllers. We provide a two-phase algorithm, called Dynamic Controllers Clustering algorithm, for the top level of load balancing operation. The load balancing operation takes place at regular intervals. The length of the cycle in which the operation is performed can be shorter, since the top-level operation can run independently of the bottom level operation. Shortening cycle time allows for more accurate results of load balancing. Theoretical analysis demonstrates that our algorithm provides a near-optimal solution. Simulation results show that our dynamic clustering improves fixed clustering by a multiplicative factor of 5.
With the advent of OpenFlow, the concept of Software-Defined Networking (SDN) becomes much popular. In the past, SDN had often been used for network virtualization; however, with the rise of OpenFlow, which speeds up network performance by separating the control layer from the data layer, SDN can be further used to manage physical network facilities. Currently, some OpenFlow controller providers have already provided users with load balancer packages in their controllers for virtual networks, such as the Neutron package in OpenStack; nevertheless, the existing load balancer packages work in the old fashion that causes extra delay since they poll controllers for every new coming connection. In this paper, we use the wildcard mask to implement the load balance method directly on switches or routers and add a user prediction mechanism to change the range of the wildcard mask dynamically. In this way, the load balance mechanism can be applied conforming to real service situations. In our experiment, we test the accuracies of flow prediction for different predicted algorithms and compare the delay times and balance situations of the proposed method with other load balancers. With the popularity of cloud computing, the demand for cloud infrastructure also increases. As a result, we also apply our load balance mechanism on cloud services and prove that the proposed method can be implemented to varieties of service platforms.
Advent of big data, cloud computing and IOTs resulted into significant increase in traffic on servers used in traditional networks as these networks are normally non-programmable, complex in management, highly expensive in nature, and have tightly coupled control plane with data plane. To overcome these traditional network-based issues a newly emerging technology software defined networking (SDN) has been introduced which decouples the data plane and control plane and makes the network fully programmable. SDN controllers are programmable so an efficient load balancing algorithms must ensure the effective management of resources as per client’s request. Based on these parameters i.e. throughput, transaction rate, & response time the qualitative comparison between the load balancing algorithms of SDN is done to generate the best results.
RSA algorithm is one of the most popular and secure public key cryptographic algorithms. To guarantee data security in cloud computing, RSA algorithm has been widely used in cloud. The security of RSA algorithm lies in the difficulty of factoring large integers efficiently. The General Number Field Sieve (GNFS) algorithm is the most efficient algorithm for factoring integers greater than 110 digits at present, and cloud computing is able to provide powerful ability for carrying out GNFS algorithm. Focussing on the research regarding security of RSA, in this paper, we study the GNFS algorithm in cloud. More specifically, we discuss the current research about solving large and sparse linear systems over GF(2), which is one of the most time-consuming steps of the GNFS algorithm. Then, we propose a novel parallel block Wiedemann algorithm in cloud to reduce the communication cost of solving large and sparse linear systems over GF(2). The proposed parallel block Wiedemann algorithm includes strip partitioning, cyclic partitioning, and improved strip partitioning which accelerate different steps in the block Wiedemann algorithm in a parallel way. Theoretical and experimental results show that the parallel block Wiedemann algorithm can greatly enhance the performance of GNFS compared with other existing algorithm, in terms of both execution time and speedup.
Abstract – These days our networks have to handle large amount of traffic, serve thousands of clients. It is very difficult for a single server to handle such huge load. The solution is to use multiple servers with load balancer acting as a front end. The clients will send the requests to the load balancer. The load balancer will forward the client requests to different servers depending upon load balancing strategy. Load balancer use dedicated hardware. That hardware is expensive and inflexible. Currently available load balancers contain few algorithms that can be used. Network administrators can not create their own algorithms since traditional load balancer are vendor locked, non programmable. On the other hand SDN load balancers are programmable and allow you to design and implement your own load balancing strategy. Other advantages of SDN load balancer is we do not need dedicated hardware. The dumb silicon device can be converted to a powerful load balancer by using SDN controllers. In this paper we are implementing and comparing Round-Robin load balancing strategy with already implemented random strategy using an OpenFlow switch connected to a POX controller