Traditional Wireless Sensor Networks protocols used in Internet of Things Networks (IoTNs) today face challenges in high-and ultra-density network topology conditions. New networking paradigms like Software-Defined Networks (SDN) have emerged as an up-and-coming approach to address IoT application requirements through implementing global protocol strategies and network programmability. This paper proposes a divide-and-conquer solution that aims to improve the PDR in ultra-dense IoT (UDIoT) network environments using network slicing. As such, we develop and evaluate DENIS-SDN, an opensource SDN solution for UDIoT Network environments consisting of a modular SDN controller and an OpenFlow-like data-plane protocol. DENIS-SDN utilizes our Network Density Control mechanism based on operational specification requirements, which address the challenges UDIoT network deployments pose, including interference, congestion, resource management, control, and quality of service (QoS) performance issues. To achieve this, it divides dense IoT networks into either logically sliced subnetworks separating nodes using routing rules or physically sliced sub-networks separating nodes into different radio channels. We provide evaluation results over realistic scenarios demonstrating improved PDR performance up to 4.8% for logically and up to 11.6% for physically sliced network scenarios.

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The Internet of Things (IoT) is gradually incorporating multiple environmental, people, or industrial monitoring deployments with diverse communication and application requirements. The main routing protocols used in the IoT, such as the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), are focusing on the many-to-one communication of resource-constraint devices over wireless multi-hop topologies, i.e., due to their legacy of the Wireless Sensor Networks (WSN). The Software-Defined Networking (SDN) paradigm appeared as a promising approach to implement alternative routing control strategies, enriching the set of IoT applications that can be delivered, by enabling global protocol strategies and programmability of the network environment. However, SDN can be associated with significant network control overhead. In this paper, we propose VERO-SDN, an open-source SDN solution for the IoT, bringing the following novelties in contrast to the related works: (i) programmable routing control with reduced control overhead through inherent protocol support of a long-range control channel; and (ii) a modular SDN controller and an OpenFlow-like protocol improving the quality of communication in a wide range of IoT scenarios through supporting two alternative topology discovery and two flow establishment mechanisms. We carried out simulations with various topologies, network sizes and high-volume transmissions with alternative communication patterns. Our results verified the robust performance and reduced control overhead of VERO-SDN for alternative IoT deployments, e.g., achieved up to 47% reduction in network's overall end-to-end delay time compared to RPL and a packet delivery ratio of over 99.5%. INDEX TERMSInternet of Things, out-of-band control, software-defined networks, wireless sensor networks.

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This paper intends to shed light on the security problems faced by e-learning software; which, until now has not been systematically tested for vulnerabilities and weaknesses. These result to web programs exposed to attacks that are fairly easy to implement. Additionally, e-learning software deals with intelligent, studious individuals; The intended audience for the product has the knowledge, or is potentially being taught the knowledge, to compromise the software. The problem is that in a situation like this, the compromised software remains unrevealed, probably for ever, because the beneficiaries have absolutely no need to reveal their findings, but rather exploit the very best of it.