No abstract

In order to meet strict Quality-of-Service (QoS) constraints imposed by some industrial applications, the configuration of industrial networks must address the requirements of traffic flows with different priorities such as minimum delay and packet loss. The performance is affected significantly if the end-to-end delay and packet loss surpasses a specific limit, and may become unbefitting for the destination. In this paper, we select Software-Defined Networking (SDN) technology to manage centralized devices and design an optimal path to guarantee the QoS requirements by taking into consideration two types of traffic flows: the first is low-delay while the second is both low-delay and low-loss. By using this optimal path, the Reactive Flow Installation (RFI) method increases the time delay in the forwarding of packets. So as to solve this issue, we propose a Mixed Flow Installation (MFI) method based on caching the flow rules which correspond to the optimal paths in the hash table deployed in the SDN controller memory in order to reduce the computation time of the forwarding path and the load at the SDN controller. Alternatively, the pre-configured flow rules in switches by the Proactive Flow Installation (PFI) method achieves the delay-sensitive. However, the PFI is not modified when the network status or the traffic type changes till the timeout value expires. This can affect the QoS requirements for industrial applications. To handle this challenge, we propose a PFI Re-routing (PFIR) method that redefined faster a new optimal path according to change without waiting the SDN controller for new flow rules. With the care of wireless and wired networks, we have built a simulation network via the OpenDayLight SDN controller and conducted an experimental testbed. The framework results are demonstrated by the performances through reduction of end-to-end delay, packet loss rate, and packet violation ratio.INDEX TERMS SDN, Industrial SDN (ISDN), optimal path, flow installation method, QoS.

No abstract

Software-defined networking (SDN) provides the prospect of logically centralized management in industrial networks and simplified programming among devices. It also facilitates the reconfiguration of connectivity when there is a network element failure. This paper presents a new Industrial SDN (ISDN) resilience that addresses the gap between two types of resilience: the first is restoration while the second is protection. Using a restoration approach increases the recovery time proportionally to the number of affected flows contrarily to the protection approach which attains the fast recovery. Nevertheless, the protection approach utilizes more flow rules (flow entries) in the switch which in return increments the lookup time taken to discover an appropriate flow entry in the flow table. This can have a negative effect on the end-to-end delay before a failure occurs (in the normal situation). In order to balance both approaches, we propose a Mixed Fast Resilience (MFR) approach to ensure the fast recovery of the primary path without any impact on the end-to-end delay in the normal situation. In the MFR, the SDN controller establishes a new path after failure detection and this is based on flow rules stored in its memory through the dynamic hash table structure as the internal flow table. At that time, it transmits the flow rules to all switches across the appropriate secondary path simultaneously from the failure point to the destination switch. Moreover, these flow rules which correspond to secondary paths are cached in the hash table by considering the current minimum path weight. This strategy leads to reduction in the load at the SDN controller and the calculation time of a new working path. The MFR approach applies the dual primary by considering several metrics such as packet-loss probability, delay, and bandwidth which are the Quality of Service (QoS) requirements for many industrial applications. Thus, we have built a simulation network and conducted an experimental testbed. The results showed that our resilience approach reduces the failure recovery time as opposed to the restoration approaches and is more scalable than a protection approach. In the normal situation, the MFR approach reduces the lookup time and end-to-end delay than a protection approach. Furthermore, the proposed approach improves the performance by minimizing the packet loss even under failing links.

Due to the explosive growth of the Internet of things (IoT) devices and the emergence of diverse new applications, network traffic volume is growing exponentially. The traditional centralized network architecture cannot fulfill IoT devices demand because of the heavy network traffic in industrial IoT. Moreover, IoT devices have limited computational ability and battery power. Energy consumption and time delay problems during computation offloading are fundamental issues. A new architecture known as mobile edge computing (MEC) was introduced to overcome these issues, which brings cloud services and its contents to the edge of the network. IoT devices can offload the data for computation to the cloud server or edge nodes. Different schemes have been proposed to overcome this problem under many scenarios (i.e., single-user, multiuser, and vehicular networks). In this paper, we proposed a modified delay mitigation Levenshtein distance algorithm (MDML). We consider an industrial scenario with multiple IoT devices and multiple servers (edge nodes). Each edge node consists of one MEC server. The proposed algorithm solves the offloading optimization problem of energy and mitigation of time delay with much lower complexity while significantly reducing offloading tasks’ execution time. It works on the basis of dynamic programming, where we break down a complex problem into subproblems. Performance evaluation of our proposed algorithm shows that it can achieve satisfactory energy efficiency and mitigate time delay in the industrial IoT environment.