Software Defined Networking (SDN) as an innovative network paradigm that separates the management and control planes from the data plane of forwarding devices by implementing both the management and control planes at a logically centralized entity, called controller. Therefore, it ensures simple network management and control. However, due to several reasons (e.g., deployment cost, fear of downtime) organizations are very reluctant to adopt SDN in practice. Therefore, a viable solution is to replace the legacy devices by SDN devices incrementally. This results in a new network architecture called hybrid SDN. In hybrid SDN, both SDN and legacy devices operate in such a way to achieve the maximum benefit of SDN. The legacy devices are running a traditional protocol and SDN devices are operating using Open-flow protocols. Network policies play an essential role to secure the entire network from several types of attacks like unauthorized access and port/protocol control. In a hybrid SDN, policy implementation is a tedious task that requires extreme care and attention due to the hybrid nature of network traffic. Network policies may be implemented at various positions in hybrid SDN, e.g., near the destination or source node, and at the egress or ingress ports of a router. Each of these schemes has some trade-offs. For example, if policies are implemented near the source nodes then each packet generated from the source must pass through the filter and, thus, requires more processing power, time, resources, etc. Similarly, if policies are installed near the destination nodes, then a lot of unwanted traffic generated causing network congestion. This is an NP-hard problem. To address these challenges, we propose a systematic design approach to implement network policies optimally by using decision tree and K-partite graph. By traversing all the policies, we built up the decision tree that identifies which source nodes can communicate with which destination. Then, we traverse the decision tree and constructs K-partite graph to find possible places (interfaces of the routers) where ACL policies are to be implemented based on the different criteria (i.e., the minimum number of ACL rules and the minimum number of transmissions for unwanted traffic). The edge weight represents the cost per criteria. Then, we traverse the K-partite graph to find the optimal place for ACL rules implementation according to the given criteria. The simulation results indicate that the proposed technique outperforms existing approaches in terms of computation time, traffic optimization and successful packet delivery, etc. The results also indicate that the proposed method improves network performance and efficiency by decreasing network congestion and providing ease of policy implementation.

In last decade, application developers attained improved performances by merely employing the machines based on higher-clocked processors. However, in 2003 multi-core processors emerged and eradicated the old processor manufacturing technology based on increasing processor’s clock frequencies. After emergence of new parallel processor architectures, serial applications must be re-engineered into parallel versions to exploit the computing power of the existing hardware. In this paper, we present an efficient parallel implementation of minimum spanning tree algorithm to take advantage of the computing power of multi-core machines. Computer network routing, civil infrastructure planning and cluster analysis are typically use-cases of spanning tree problem. The experimental results show that the proposed algorithm is scalable for different machine and graph sizes. The methodology is simple and can easily be implemented using different shared-memory parallel programming models.

Software Configuration Management (SCM) aims to provide a controlling mechanism for the evolution of software artifacts created during software development process. Controlling software artifacts evolution requires many activities to be carried out such as, construction and creation of versions, computation of mappings and differences between versions, merging (i.e. combining of two or more versions) and so on. Traditional SCM systems are file-based SCM systems, which are not adequate for performing software configuration management activities. File-based SCM systems consider software artifacts as a set of text files, while today’s software development is model-driven and models are the main artifacts produced in the early phases of software development process. New challenges of model mappings, differencing, merging, and conflict detection arise when applying file-based solution to model-driven software. The goal of this paper is to develop a configuration management solution for model merging and conflict resolution that overcomes the challenges faced by traditional SCM systems for model-based development. We represent models at finegrained level as graph structures, which is an intermediate representation based on graph theory. Our approach follows a 3-way model merge process, where a base and its derived versions are used for comparison. To differentiate between conflicted and non-conflicted cases, we have defined different merge cases, and established a merge policy based on merge cases. Merge cases are used along with the comparison result in order to perform conflict resolution and merge operation. We performed a controlled experiment using open source eclipse modeling framework and compare our approach with an open source tool Eclipse Modeling Framework (EMF) Compare. The results proved the accuracy and efficiency of our proposed approach.