Mobility-Aware Hybrid Flow Rule Cache Scheme in Software-Defined Access Networks

Due to the dynamic mobility feature, the proactive flow rule cache method has become one promising solution in software-defined networking (SDN)-based access networks to reduce the number of flow rule installation procedures between the forwarding nodes and SDN controller. However, since there is a flow rule cache limit for the forwarding node, an efficient flow rule cache strategy is required. To address this challenge, this paper proposes the mobility-aware hybrid flow rule cache scheme. Based on the comparison between the delay requirement of the incoming flow and the response delay of the controller, the proposed scheme decides to install the flow rule either proactively or reactively for the target candidate forwarding nodes. To find the optimal number of proactive flow rules considering the flow rule cache limits, an integer linear programming (ILP) problem is formulated and solved using the heuristic method. Extensive simulation results demonstrate that the proposed scheme outperforms the existing schemes in terms of the flow table utilization ratio, flow rule installation delay, and flow rules hit ratio under various settings.

An active detection of compromised nodes based on en-route trap in wireless sensor network

With the development and wide use of wireless sensor network, security arises as an essential issue since sensors with restrict resources are deployed in wild areas in an unattended manner. Most of current en-route filtering schemes could filter false data effectively; however, the compromised nodes could take use of the filtering scheme to launch Fictitious False data Dropping attack, the detection of this attack is extremely difficult since the previous hop node is unable to distinguish whether the forwarding node dropt a false data report with incorrect Message Authentication Codes or a legitimate report. This is the first attempt to address the Fictitious False data Dropping attack; in this article, we propose an Active Detection of compromised nodes based on En-route Trap to trap compromised nodes in the scenario of a false data dropping. A trust model is used to evaluate trust level of neighbor nodes with respect to their authentication behaviors. A detecting algorithm of compromised node is used to detect compromised nodes. Simulation results showed that our scheme can address the Fictitious False data Dropping attack and detect 60% of compromised nodes with a low false positive rate; consequently, the packet accuracy of an Active Detection of compromised nodes based on En-route Trap increases rapidly and reaches to 86%.

Low Energy Routing Protocol for Oil and Gas Pipeline Internet of Things

Nodes in the Internet of Things of oil and gas pipelines are linearly distributed according to the direction of pipelines, so it is difficult to realize timely and large-scale battery replacement. Therefore, effective energy management has always been a key factor restricting the performance of the IoT of oil and gas pipelines.In addition, the end-to-end delay determines the response time of pipeline safety accidents and is also a key parameter to improve the real-time performance of the network. Considering energy effciency and delay comprehensively, this paper proposes PIOT-LPRP (Pipeline Internet of Things - Low Power Routing Protocol) protocol. The remaining energy of nodes and the distance between nodes and sink nodes are used as indicators to select candidate forwarding nodes in opportunistic routing to achieve energy balance in the network. The use of energy collection technology to extend the service life of the network. By choosing the node which is far away from the transmission as the forwarding node, the number of hops of data transmission can be effectively reduced, so as to reduce the end-to-end delay of the network. The simulation results show that PIOT-LPRP can effectively take into account the network life and network latency, and improve the network performance, by comparing with the classical opportunistic routing protocol EXOR, the same type of protocol RE-OR, and the HER protocol using energy harvesting technology.

LWTSM-IoT: Light Weight Trust Sensing Mechanism for Internet of Things

In Internet of Things (IoT), secure communication is a prime concern since the open internet source and vast heterogeneity offers several challenges to the network. To achieve an enhanced security, an effective trust evaluation model is required through which the abnormal nodes can be detected and isolated. Towards this objective we have proposed a Light Weight Trust Sensing (LWTS) mechanism for IoT routing. Several factors like Packet Forwarding Factor, Packet Consistency Factor and Packet Repetition Factor are employed to analyze the behaviour of IoT nodes. Along with these factors, the proposed model also checks for energy efficiency to achieve an improved network lifetime. Trust Calculation process is accomplished in two phases; they are direct and indirect fashion. Finally based on obtained total trust, each neighbour node are categorized as No Trust, Average Trust, Fair Trust and Good Trust and the node with good trust is selected as next-hop forwarding node. For the proposed approach extensive simulations are carried out and the performance is measured through Packet Delivery Ratio, Malicious Detection Rate and Average Energy Consumption. The obtained results prove the effectiveness when compared to existing approaches.

Stable routing and energy-conserved data transmission over wireless sensor networks

Stable routing and energy conservation over a wireless sensor network (WSN) is a major issue in Internet of Things applications. The network lifetime can be increased when studying this issue with interest. Data transmission is a dominant factor in IoT networks for communication overhead and energy consumption. A proposed efficient node stable routing ($$ENSR$$ ENSR ) protocol is introduced to guarantee the stability of transmission data between the source and destination nodes, in a dynamic WSN conditions. $$ENSR$$ ENSR minimizes energy consumption and selects more stable nodes for packets forwarding. Stability becomes the most important factor that qualifies the node's centrality. A node’s stability is characterized by residual energy, link quality, and number of hops needed to reach the destination from the node. To calculate node's stability, an enhanced centrality concept, known as stable betweenness centrality ($$SBC$$ SBC ) is introduced. In $$ENSR$$ ENSR , at first, some nodes will be selected as the stable forwarding nodes, usually with maximum $$SBC$$ SBC between their neighbors within a limited communication radio range of a particular region. Furthermore, each stable forwarding node then broadcasts its identity, including $$SBC$$ SBC , to the source node separately. The source node can compute a stable path to forward packets to the corresponding stable forwarding node, based on a proper designed stable path routing metric ($$SPRM$$ SPRM ). Then, the stable forwarding node will behave as a new source node and start another stable path routing process until the packets are forwarded and reached to the destination node. In addition, the change of stable nodes over time balances and conserves node energy consumption, thereby mitigating “hot spots”. The proposed routing protocol is validated through simulation. The numerical results show that the proposed protocol outperforms the existing algorithms, global and local reliability-based routing ($$GLRR$$ GLRR ) and reliable energy-aware routing protocol $$(RER)$$ ( R E R ) , in terms of network efficiency and reliability.

Q -Learning-Based High Credibility and Stability Routing Algorithm for Internet of Medical Things

With the outbreak of COVID-19, people’s demand for using the Internet of Medical Things (IoMT) for physical health monitoring has increased dramatically. The considerable amount of data requires stable, reliable, and real-time transmission, which has become an urgent problem to be solved. This paper constructs a health monitoring-enabled IoMT network which is composed of several users carrying wearable devices and a coordinator. One of the important problems for the proposed network is the unstable and inefficient transmission of data packets caused by node congestion and link breakage in the routing process. Based on these, we propose a Q -learning-based dynamic routing selection (QDRS) algorithm. First, a mathematical model of path optimization and a solution named Global Routing selection with high Credibility and Stability (GRCS) is proposed to select the optimal path globally. However, during the data transmission through the optimal path, the node and link status may change, causing packet loss or retransmission. This is a problem not considered by standard routing algorithms. Therefore, this paper proposes a local link dynamic adjustment scheme based on GRCS, using the Q -learning algorithm to select the optimal next-hop node for each intermediate forwarding node. If the selected node is not the same as the original path, the chosen node replaces the downstream node in the original path and so corrects the optimal path in time. This paper considers the congestion state, remaining energy, and mobility of the node when selecting the path and considers the network state changes during packet transmission, which is the most significant innovation of this paper. The simulation results show that compared with other similar algorithms, the proposed algorithm can significantly improve the packet forwarding rate without seriously affecting the network energy consumption and delay.

Dynamic Space-Covered Broadcast Algorithm Based on Neighbor-Degree in Mobile Ad Hoc Wireless Networks

Broadcast is an important link in mobile ad hoc wireless networks (MANETs). In order to improve broadcast coverage, reduce forwarding probability and broadcast collision, a dynamic space-covered broadcast algorithm based on neighbor-degree in MANETs is proposed. The concepts of neighbor-degree, available-angel and available-distance are introduced. The neighbor-degree is used to generate the initial forwarding probability of a node. Based on the available-angle and available-distance, the node weight is proposed to calculate the final forwarding probability, thereby realizing the dynamic selection of forwarding node and reflecting the dynamic space-covered of node. The forwarding strategy is proposed to reduce broadcast collision. Simulation results show that, compared with dynamic probability broadcast and node location based space-covered broadcast, proposed broadcast algorithm reduces the broadcast collision, improves the broadcast coverage, and reduces the forwarding probability when the number of nodes is large.

Motion Prediction Based TDMA Protocol in VANETs

In Vehicular Ad Hoc Networks (VANETs), the high mobility of vehicle nodes makes the network topology change frequently, reducing the forwarding efficiency of MAC protocol. In the existing enhanced TDMA-based MAC protocol, the farthest node in the current transmission range is chosen as the forwarding node to accelerate the multi-hop transmission. However, we use probabilistic model to show that there potentially exist better forwarding nodes, which could effectively improve transmission efficiency. Therefore, we propose a motion-prediction based TDMA protocol, which predicts the network topology in the next frame to select the better forwarding node. The test results of highway and urban scenarios show that the motion-prediction based TDMA protocol effectively reduces the number of hops in multi-hop transmission and decreases the broadcast delay by 50% to cover the whole network.

Novel Cluster Rotating and Routing Strategy for software defined Wireless Sensor Networks

The biggest problems faced by the software defined wireless sensor network are energy conservation and load balancing techniques which impose a high level of constraint. In general clustering is used in a network in order to decrease the use of energy thereby enhancing lifetime of the network. Hot spot problems are a common issue caused due to drainage of battery when there are more multi-hop networks that are close to the base station. In order to overcome this restriction, we have proposed the use of multilayer clustering architecture that is used to choose the intra and inter-cluster communication, rotation of cluster head and forwarding node. Using the routing table, the proposed methodology will be able to efficiently handle the rotation of the forwarder node. The rotation takes place based on the residual energy’s threshold levels and also exploits the non-forwarder node, backup forwarder node, forwarder node and decision maker node to enhance the routing strategy of the WSN. Testing and evaluation of the proposed work is done using C programming language and results show that this methodology has better results than EADUC and TLPER as far as hop count, communication and energy consumption are taken into consideration in the cluster formation.