With emerging programmable network architectures gaining momentum in the networking industry, it is necessary to look at how the services currently offered on traditional network architectures can be fully migrated to the programmable networks. In traditional networks, lightpaths are used for providing high-bandwidth consuming services that are usually sensitive to delay. Lightpath scheduling requires admission control mechanisms, routing and wavelength assignment algorithms, and protection and restoration mechanisms that ensure reliable and efficient lightpath routing. Software defined networking (SDN) is the emerging programmable network architecture that paves the way for easier network management and configuration by using application programming interfaces. The state-of-the-art in lightpath routing for wavelength division multiplexing networks focusing on lightpath scheduling, routing, protection and restoration in optical software defined networks is surveyed. Moreover, open research issues for SDN lightpath routing solution are discussed.

The ability to enhance network routing for flexible support of different application requirements is essential to widen the horizon for the Internet of things (IoT) deployments. The Internet protocol (IP) version 6 routing protocol for low-power and lossy networks (RPL) provides an effective routing solution addressing such a challenge. It realises flexible end-to-end IP routing that can be adapted to support different IoT applications. This is based on the concept of customisable objective functions (OFs), which facilitates application-specific routing using a wide range of routing metrics. There are only two default OFs of basic routing metrics, which are specified by the Internet engineering task force for RPL. However, a number of others have been proposed by the network research community to address single- and multi-objective RPL routing enhancement. These research proposals followed different methodological approaches and adopted a variety of routing metrics to achieve different optimisation goals. Up-to-date research efforts to improve RPL routing and topology optimisation have been reviewed, and recent RPL OFs and routing metrics in the literature have been discussed. The major aim is shedding light on relevant contributions to establish a firm understanding of recent RPL developments and outline plausible areas for follow-up researches.

Across the globe, right from people who are technologically naive to people who are with high-technical knowledge, use, share, spread, and connect with each other through online social networks. People start believing and sharing the social network content without any proof of its authenticity. In several cases, the reliability of the information that gets shared between the users remains questionable due to the anonymity of the information creators. In this work, a fuzzy detection algorithm is proposed to identify the trustable content in social media. The proposed methodology is evaluated on Twitter social network platform. By computing the predictive measures, the efficiency of the proposed approach is well established.

The cooperative behaviour of end-systems in efficiently and fairly utilizing the scarce bandwidth is of paramount significance in the best effort Internet. Not only does the uncooperative behaviour result in unfairness, but it may also induce congestion collapse. How to urge end-systems to share the bandwidth cooperatively is a problem that depends, in essence, on incentives. This study presents a novel fairness-driven active queue management (AQM)-based incentive scheme to detect and take punitive action against any uncooperative behaviour. Different from all other fairness-driven AQM schemes, the proposed scheme offers a dual-mode control function that can adaptively switch between stateless and partial-state modes in order to be scalable. The control function remains stateless at low to moderate congestion levels and maintains a partial-state when congestion becomes severe. In the stateless mode, the identification and restriction of unresponsive flows are based on a matched-drop mechanism having a dynamic drawing factor to differentially drop packets from unresponsive flows. In the partial-state mode, a fair-share is estimated and flows whose arrival rates exceed the fair-share bandwidth get their rates limited to the fair rate. Simulation results demonstrate the reasonable performance improvement of the proposed scheme over well-known fairness-driven AQM schemes.

The vertex colouring problem (VCP) and its generalisations have myriad applications in computer networks. To solve the VCP with colours, numerous distributed algorithms based on LOCAL model have been proposed to reduce time complexity (the number of rounds), where is the maximum vertex degree in the graph. In this paper, the authors present a distributed algorithm based on modified LOCAL model (DIAMOND) that reduces the number of rounds to one. It greedily solves the VCP with at most colours. Computational results on Geometry (GEOM) graphs show that the number of used colours to colour each instance using DIAMOND is about . DIAMOND is easily extended to solve greedily generalised VCPs in only one round. Moreover, they present two efficient resource allocation algorithms using DIAMOND. They allocate more resource to the graph compared with -colouring and even to -colouring algorithms, where is the average vertex degree of the graph. They run in two and rounds.

Clustering is one of the mechanisms for routing in wireless sensor networks which reduces the energy and bandwidth requirements to improve network lifetime. A centralised cluster head selection and distributed cluster formation scheme by using fuzzy techniques is proposed in this study. The fuzzy c-means is used by the sink to find cluster centres and their associated member nodes. A cluster head is selected from each cluster centre associated member nodes based on the fitness of the nodes which is computed using residual energy and distance to the cluster centre as inputs to fuzzy inference system. Nodes associate with a cluster head depending on their proximity, thereby forming clusters. Proximity will be found out by node with the assistance of signal strength parameter from cluster head which broadcast selection advertisement. This completes a round of cluster formation. At the end of each round, the nodes transmit their fitness value to their respective cluster head which in turn is forwarded to the sink. The sink selects a node with highest fitness value from each cluster centre associated members as cluster head for the next round. The scheme is compared with self-management model and optimal clustering mechanism to demonstrate the improved performance.