Owing to the limited resources of sensor nodes, we propose an efficient hybrid routing scheme using a dynamic cluster-based static routing protocol (DCBSRP), leveraging the ad hoc on-demand distance vector (AODV) routing protocol and low-energy adaptive clustering hierarchy (LEACH) protocol. In the proposed scheme, the cluster head (CH) nodes are formed dynamically for a fixed interval, whereas static routing is applied in the designated clusters by utilizing the AODV routing protocol. The static routing condition of the proposed scheme limits all connected nodes of the cluster for a defined interval of time (T) to share their collected information through a specific CH node. Once the time (T) interval is completed, all ordinary nodes connected with the specific CH are released and they are free to advertise their CH candidateship within the network. Likewise, the node receiving the maximum number of route replies (RREPs) is selected as the next CH node in the vicinity of deployed sensor nodes. However, with the DCBSRP protocol, the recently selected CH node does not advertise its candidateship for five consecutive cycles and acts as an ordinary node. The simulation result shows significant improvement in the lifetime and participation of ordinary nodes in the network until the end-stage of the network. In the proposed scheme, the participation of ordinary nodes in the network is 95.9 %, which not only balances load between participating nodes but also improves the network lifetime in the presence of field-proven schemes. Moreover, the simulation results show an out-performance of rival schemes in terms of communication cost, end to end delay, throughput, packet lost ratio, and energy consumption.

Deployment of new optimized routing rules on routers are challenging, owing to the tight coupling of the data and control planes and a lack of global topological information. Due to the distributed nature of the traditional classical internet protocol networks, the routing rules and policies are disseminated in a decentralized manner, which causes looping issues during link failure. Software-defined networking (SDN) provides programmability to the network from a central point. Consequently, the nodes or data plane devices in SDN only forward packets and the complexity of the control plane is handed over to the controller. Therefore, the controller installs the rules and policies from a central location. Due to the central control, link failure identification and restoration becomes pliable because the controller has information about the global network topology. Similarly, new optimized rules for link recovery can be deployed from the central point. Herein, we review several schemes for link failure recovery by leveraging SDN while delineating the cons of traditional networking. We also investigate the open research questions posed due to the SDN architecture. This paper also analyzes the proactive and reactive schemes in SDN using the OpenDayLight controller and Mininet, with the simulation of application scenarios from the tactical and data center networks.

As the Internet of Things (IoT) is expected to become pervasive in everyday life, it is also expected that numerous applications and services with a large number of Bluetooth Low Energy (BLE) devices will be developed for areas such as sports arenas, subways, shopping malls, and many other busy public places. The fast discovery of all BLE advertisers is one of the most challenging tasks in supporting such a large number of BLE-enabled services successfully. However, there has been no research published so far that presents a method of setting parameters that provide the best performance in the BLE neighbor discovery process. In this paper, we propose a method to determine an optimal value for the BLE advertisement interval to minimize the time in which all surrounding BLE advertisers are discovered by a scanner. To obtain the optimal advertisement interval, we derive a new analytical model to characterize the BLE discovery time with all possible parameters. We also analyze the effect of the optimal advertisement interval on energy consumption. The analytical model is validated by comparing the analysis results with the simulations. The simulation results show that the optimal advertisement interval for a given number of BLE advertisers can minimize the discovery time, and the energy consumption also is reduced significantly.

If an end-to-end (E2E) path includes multiple domains, we need inter-domain collaboration to ensure the E2E quality-of-service (QoS) for the applications. In heterogeneous networks, an E2E path may go through domains with several QoS classes in each domain. However, the prevalent legacy network architecture and the standard software-defined networking (SDN) model lack effective mechanisms for inter-domain collaboration and QoS class mapping. In this study, we propose a hierarchical SDN control plane approach to guarantee the E2E QoS among multiple domains with various QoS classes on the E2E path. We propose a controller module for selecting the most suitable QoS class for each domain in the E2E path based on multi-criteria decision-making by using the technique for order of preference by similarity to ideal solution (TOPSIS). We map the suitable service classes in the global controller (GC) for provisioning the E2E QoS according to the application service requests. First, we propose an SDN-based inter-domain communication scheme and the message processing algorithm for E2E service delivery when multiple QoS classes exist in each domain. Next, we formulate the problem of service class selection with TOPSIS, provide an E2E mapping scheme, and demonstrate it with an example. Finally, we compare the proposed approach with the existing schemes for E2E QoS class mapping in terms of E2E delay, jitter, packet loss rate (PLR), and cost (per bandwidth unit). According to our simulation results, the proposed approach ensures the E2E QoS and guarantees the E2E delay, jitter, PLR, and cost according to the application service requests.

The software-defined networking (SDN) paradigm has simplified the management of computer networks by decoupling data and control planes. Moreover, the separation of the data and control planes has transitioned network complexity from traditional devices to controllers; therefore, controllers have become indispensable entities in SDN. Controllers have multiple features and direct the network from a central point and respond to updates to topological changes. However, the supportive capability of these features is strong in one controller but weak in another. Due to several controllers and each controller having a set of features, selecting an optimal SDN controller can be considered to be a multi-criteria decision-making (MCDM) problem. Herein, a two-step approach is proposed for SDN controller selection. First, the controllers are ranked with analytical network process (ANP) according to their qualitative features which influence the performance of these controllers and then a performance comparison is performed to check for the QoS improvement. The controller with a high-weight value from the feature-based comparison is quantitatively analysed by experimental analysis. The main contribution of this paper is checking the applicability of the ANP for controller selection in SDN considering its features and performance analysis in real-world Internet and Brite topologies. The simulation results show that the controller computed through the proposed approach outperforms the controller selected with existing approaches. The selection of an optimum controller with ANP results in a reduction of topology discovery time and delay in the normal and traffic load scenario. Similarly, an increase in throughput with a reasonable utilization of the central processing unit (CPU) is observed for the proposed controller.