Analyzing performance of openstate in software defined network with multiple failures scenarios

Software Defined Network (SDN) is an emerging network that decouples the control plane and data planes. Like other networks, SDN undergoes a recovery process upon occurrences of link or node failures. Openflow is considered as the popular standard used in SDN. In Openflow, the process of detecting the failure and communications with controller to recompute alternative path result to long recovery time. However, there is limit with regards time taken to recover from the failures. If it takes more than 50 msec, a lot of packet will be lost, and communication overhead and Round Trip Time (RTT) between switch – controller may be high. Openstate is an Openflow extension that allows a programmer to specify how forwarding rules should be adapted in a stateful fashion. Openstate has been tested only on single failure. This research conduct experiment based on Openstate pipeline design that provides detections mechanism based on switches periodic link probing and fast reroute of traffic flow even when controller is not reachable. In this research, the experiments use Mininet simulation software to analyse and evaluate the performance of Openstate with multiple failure scenarios. The research has compared Overhead communication, Round Trip Time (RTT) between switch – controller and number of packet loss with Openflow and Openstate. On the average, in Openstate packet loss is zero when the recovery time is less than or equal to 70 msec while communication overhead involves 60 packet-in. In Openflow, packet loss is zero when the recovery time is less than or equal to 85 msec while communication overhead involves 100 packet-in. Finally, the average RTTs for Openstate and Openflow are 65 msec and 90 msec respectively. Based on the results obtained, it can be concluded that Openstate has better performance compare to Openflow

On the number of distinct fuzzy subgroups of dihedral group of order 60

In this paper, we compute the number of distinct fuzzy subgroups of dihedral group of order 60 with respect to a new equivalence relation existing in literature. Our computation shows that the number of distinct fuzzy subgroups of dihedral group of order 60 is 150

Review of Path Selection Algorithms with Link Quality and Critical Switch Aware for Heterogeneous Traffic in SDN

Software Defined Networking (SDN) introduced network management flexibility that eludes traditional network architecture. Nevertheless, the pervasive demand for various cloud computing services with different levels of Quality of Service requirements in our contemporary world made network service provisioning challenging. One of these challenges is path selection (PS) for routing heterogeneous traffic with end-to-end quality of service support specific to each traffic class. The challenge had gotten the research community\u27s attention to the extent that many PSAs were proposed. However, a gap still exists that calls for further study. This paper reviews the existing PSA and the Baseline Shortest Path Algorithms (BSPA) upon which many relevant PSA(s) are built to help identify these gaps. The paper categorizes the PSAs into four, based on their path selection criteria, (1) PSAs that use static or dynamic link quality to guide PSD, (2) PSAs that consider the criticality of switch in terms of an update operation, FlowTable limitation or port capacity to guide PSD, (3) PSAs that consider flow variabilities to guide PSD and (4) The PSAs that use ML optimization in their PSD. We then reviewed and compared the techniques\u27 design in each category against the identified SDN PSA design objectives, solution approach, BSPA, and validation approaches. Finally, the paper recommends directions for further research

Ranking method for Z-numbers based on centroid-point

Zadeh introduced the concept of Z-number to provide a basis for computation with numbers that are not completely reliable, and it has the ability to portray fuzziness and reliability of information concurrently. Ranking of Z-numbers is an important aspect, especially in decision making Objective: Ranking method for Z-numbers. Method: By converting Z-number into fuzzy number, and then the centroid-point method and decision rules are used to rank the obtained fuzzy numbers. Results: A ranking method for Z-numbers is proposed, and a numerical example is provided to illustrate the feasibility and validity of the proposed method. Conclusions: However, converting Z-number into fuzzy number can lead to loss of original Z-information

Route Path Selection Optimization Scheme Based Link Quality Estimation and Critical Switch Awareness for Software Defined Networks

Software-defined network (SDN) is a new paradigm that decouples the control plane and data plane. This offered a more flexible way to efficiently manage the network. However, the increasing number of traffics due to the proliferation of the Internet of Things (IoT) devices also increase the number of flow arrival which in turn causes flow rules to change more often, and similarly, path setup requests increased. These events required route path computation activities to take place immediately to cope with the new network changes. Searching for an optimal route might be costly in terms of the time required to calculate a new path and update the corresponding switches. However, the current path selection schemes considered only single routing metrics either link or switch operation. Incorporating link quality and switch’s role during path selection decisions have not been considered. This paper proposed Route Path Selection Optimization (RPSO) with multi-constraint. RPSO introduced joint parameters based on link and switches such as Link Latency (LL), Link Delivery Ratio (LDR), and Critical Switch Frequency Score (CWFscore). These metrics encourage path selection with better link quality and a minimal number of critical switches. The experimental results show that the proposed scheme reduced path stretch by 37%, path setup latency by 73% thereby improving throughput by 55.73%, and packet delivery ratio by 12.5% compared to the baseline work

Adaptive and Hybrid Idle–Hard Timeout Allocation and Flow Eviction Mechanism Considering Traffic Characteristics

Software-defined networking (SDN) enables flexible fine-grained networking policies by allowing the SDN controller to install packet handling rules on distributed switches. The behaviour of SDN depends on the set of forwarding entries installed at the switch flow table. The increasing number of traffics from the proliferation of the Internet of Thing (IoT) devices increase the processing load on the controller and generates an additional number of entries stored in the flow table. However, the switch flow table memory (TCAM) cannot accommodate many entries. Packets from multimedia flows are usually large in size and thus suffer processing delay and require more flow set up requests. The SDN controller may be overloaded and face some scalability problems because it supports a limited number of requests from switches. OpenFlow uses timeout configuration to manage flow setup request. The conventional fixed timeout cannot cope up with the dynamic nature of traffic flows. This paper controls the frequent flow setup requests by proposing an adaptive and hybrid idle–hard timeout allocation (AH-IHTA). The algorithm considers traffic patterns, flow table usage ratio, and returns appropriate the timeout to different flows. The performance evaluations conducted have shown a 28% and 39% reduction in the flow setup request and flow eviction, respectively

Performance evaluation of flowtable eviction mechanisms for software defined networks considering traffic flows variabilities

Software Defined Networks (SDN) is a new paradigm that emerged to improve network management through separation of control from the data plane using a standardized protocol. OpenFlow is the most popular standard to achieve the benefit of SDN. For every arrived flow, a corresponding flow entry is installed in the switch flowtable to guide the data transmission process. The proliferation of the Internet of Things (IoT) devices increases the number of flows generation unfortunately switch flowtable is constraint with limited space. Consequently, it led to flowtable overflow. Several studies leverage the First in First Out, Random replacement policy to removed old flow entries when the flowtable is overflowed. Although some performance gains were reported. However. Flows exhibit variabilities in terms of duration, inter-arrival-time, and the number of packets differs. Usually, some flows contain a large number of packets others have few packets. Applying these replacement policies may not always meet the demand of these types of flows. As such, this study experiments eviction mechanism to evaluate the performance of the two schemes and observe their eviction behavior with respect to flow features. On average FIFO preserved flows with a large number of packets by 4.95% while Random preserved by 36.11%. In conclusion, Random showed better performance compared to FIFO with respect to an increasing flow generation and change in flowtable size

Adaptive and hybrid idle–hard timeout allocation and flow eviction mechanism considering traffic characteristics

Software-defined networking (SDN) enables flexible fine-grained networking policies by allowing the SDN controller to install packet handling rules on distributed switches. The behaviour of SDN depends on the set of forwarding entries installed at the switch flow table. The increasing number of traffics from the proliferation of the Internet of Thing (IoT) devices increase the processing load on the controller and generates an additional number of entries stored in the flow table. However, the switch flow table memory (TCAM) cannot accommodate many entries. Packets from multimedia flows are usually large in size and thus suffer processing delay and require more flow set up requests. The SDN controller may be overloaded and face some scalability problems because it supports a limited number of requests from switches. OpenFlow uses timeout configuration to manage flow setup request. The conventional fixed timeout cannot cope up with the dynamic nature of traffic flows. This paper controls the frequent flow setup requests by proposing an adaptive and hybrid idle–hard timeout allocation (AH-IHTA). The algorithm considers traffic patterns, flow table usage ratio, and returns appropriate the timeout to different flows. The performance evaluations conducted have shown a 28% and 39% reduction in the flow setup request and flow eviction, respectively

Software defined networking failure recovery with Flow Table aware and flows classification

Software Defined Networking (SDN) emerged to simplify network management and speed up innovation through a clear separation of the control plane from the data plane using OpenFlow standard. Link or switch failure occurs more often. The detect switch has to send a port status message to the controller to update the Flow Table with a new path or switch to a preconfigured backup path to recover from the failure. Most of the existing schemes are focusing on distance or delay in backup path selection. However, traffic flows exhibit variabilities and losses caused by flows also differ with respect to Flow Table utilization. Ternary Content Addressable Memory (TCAM) that stores flow entries in the Flow Table is costly with limited space. It is significant to reduce backup path entries resource consumption through different failure recovery strategies while considering the Flow Table utilization ratio at sampling time, flow classification, and shortest path. This paper devised an algorithm for backup path computation based on the shortest path, flow classification, and Flow Table utilization ratio. The simulation result shows higher throughput of (71.2), lower packet losses (3 %), and round-trip time (3.4 s)

Software defined networking flow table management of openflow switches performance and security challenges: a survey

Software defined networking (SDN) is an emerging network paradigm that decouples the control plane from the data plane. The data plane is composed of forwarding elements called switches and the control plane is composed of controllers. SDN is gaining popularity from industry and academics due to its advantages such as centralized, flexible, and programmable network management. The increasing number of traffics due to the proliferation of the Internet of Thing (IoT) devices may result in two problems: (1) increased processing load of the controller, and (2) insufficient space in the switches’ flow table to accommodate the flow entries. These problems may cause undesired network behavior and unstable network performance, especially in large-scale networks. Many solutions have been proposed to improve the management of the flow table, reducing controller processing load, and mitigating security threats and vulnerabilities on the controllers and switches. This paper provides comprehensive surveys of existing schemes to ensure SDN meets the quality of service (QoS) demands of various applications and cloud services. Finally, potential future research directions are identified and discussed such as management of flow table using machine learning