Abstract As a fundamental metric, the connectivity to assess fault tolerance and reliability of interconnection networks has been extensively explored. However, classical connectivity is not very effective at evaluating large-scale networking systems. To overcome this deficiency, two new indices, cluster connectivity and super cluster connectivity, have been proposed to characterize the robustness of interconnection networks. This paper focuses on investigating $\mathcal{H} (\mathcal{H}^{*})$-cluster connectivity and super $\mathcal{H} (\mathcal{H}^{*})$-connectivity of composition graph $DQ_{n}$, based on disc-ring and hypercube, for $\mathcal{H}\in \{K_{1,r}\ |\ 0\leq r\leq n+1\}$, respectively. In detail, we show that $\kappa (DQ_{n}|K_{1,1} (K_{1,1}^{*}))=\kappa ^{\prime}(DQ_{n}|K_{1,1}(K_{1,1}^{*})) =n+1 (n\geq 3)$, $\kappa (DQ_{n}|K_{1,r}(K_{1,r}^{*})) =\left\lceil \frac{n}{2}\right\rceil +1 (2\leq r\leq 4)$ for $n\geq 3$, $\kappa ^{\prime}(DQ_{n}|K_{1}(K_{1}^{*})) =\kappa ^{\prime}(DQ_{n})=2n (n\geq 3)$, and for $2\leq r\leq 3$ and $k\geq 2$, $$\begin{align*} \kappa^{\prime}(DQ_{n}|K_{1,r}(K_{1,r}^{*}))=\left\{\begin{array}{@{}ll} n+1, & if\ n=2k+1; \\ n, & if\ n=2k. \end{array}\right. \end{align*}$$As by-products, we show that DQcube is super $K_{1,r}-\ (K_{1,r}^{*}-)$connected $(2\leq r\leq 3)$, and derive the 4-extra connectivity of DQcube $\kappa _{4}(DQ_{n}) = 5n-9 (n\geq 4)$.

The TOUCAN project proposed an ontology for telecommunication networks with hybrid technologies – the TOUCAN Ontology (ToCo), available at http://purl.org/toco/ , as well as a knowledge design pattern Device-Interface-Link (DIL) pattern. The core classes and relationships forming the ontology are discussed in detail. The ToCo ontology can describe the physical infrastructure, quality of channel, services and users in heterogeneous telecommunication networks which span multiple technology domains. The DIL pattern is observed and summarised when modelling networks with various technology domains. Examples and use cases of ToCo are presented for demonstration.

With network attacks becoming more sophisticated and unpredictable, detecting their onset and mitigating their effects in an automated manner become increasingly challenging. Lightweight and agile detection mechanisms that are able to detect zero-day attacks are in great need. High true-negative rate and low false-positive rate are the most important indicators for a intrusion detection system. In this paper, we exploit the logically-centralised view of Software-Defined Networking (SDN) to increase true-negative rate and lower false-positive rate in a intrusion detection system based on the Artificial Immune System (AIS). We propose the use of an antibody fuser in the controller to merge and fuse the mature antibody sets trained in the individual switches and turn the real intrusion records each switch has seen into antibodies. Our results show that both the false-positive rate and true-negative rate experience significant improvement with the number of local antibody sets fused grows, consuming less cpu usage overhead. A peak improvement can reach over 80% when antibody sets from all switches are taken into consideration.