Connected vehicles provide advanced transformations and attractive business opportunities in the automotive industry. Presently, IEEE 802.11p and evolving 5G are the mainstream radio access technologies in the vehicular industry, but neither of them can meet all requirements of vehicle communication. In order to provide low-latency and high-reliability communication, an SDN-enabled network architecture assisted by MEC, which integrates different types of access technologies, is proposed. MEC technology with its on-premises feature can decrease data transmission time and enhance quality of user experience in latency-sensitive applications. Therefore, MEC plays as important a role in the proposed architecture as SDN technology. The proposed architecture was validated by a practical use case, and the obtained results have shown that it meets application- specific requirements and maintains good scalability and responsiveness.

A Scalable and Quick-Response Software Defined Vehicular Network Assisted by Mobile Edge Computing

As an enabler for smart industrial Internet of Things (IoT), sensor cloud facilitates data collection, processing, analysis, storage, and sharing on demand. However, compromised or malicious sensor nodes may cause the collected data to be invalid or even endanger the normal operation of an entire IoT system. Therefore, designing an effective mechanism to ensure the trustworthiness of sensor nodes is a critical issue. However, existing cloud computing models cannot provide direct and effective management for the sensor nodes. Meanwhile, the insufficient computation and storage ability of sensor nodes makes them incapable of performing complex intelligent algorithms. To this end, mobile edge nodes with relatively strong computation and storage ability are exploited to provide intelligent trust evaluation and management for sensor nodes. In this article, a mobile edge computing-based intelligent trust evaluation scheme is proposed to comprehensively evaluate the trustworthiness of sensor nodes using probabilistic graphical model. The proposed mechanism evaluates the trustworthiness of sensor nodes from data collection and communication behavior. Moreover, the moving path for the edge nodes is scheduled to improve the probability of direct trust evaluation and decrease the moving distance. An approximation algorithm with provable performance is designed. Extensive experiments validate that our method can effectively ensure the trustworthiness of sensor nodes and decrease the energy consumption.

MTES: An Intelligent Trust Evaluation Scheme in Sensor-Cloud-Enabled Industrial Internet of Things

As an extension of wireless sensor network in underwater environment, underwater acoustic sensor networks (UASNs) have caused widespread concern of academia. In UASNs, the efficiency and reliability of data transmission are very challenging due to the complex underwater environment in variety of ocean applications, such as monitoring abnormal submarine oil pipelines. Motivated by the importance of energy consumption in many deployments of UASNs, we therefore propose an energy-efficient data transmission scheme in this paper, called energy-efficiency grid routing based on 3D cubes (EGRCs) in UASNs, considering the complex properties of underwater medium, such as 3D changing topology, high propagation delay, node mobility and density, as well as rotation mechanism of cluster-head nodes. First, the whole network model is regarded as a 3D cube from the grid point of view, and this 3D cube is divided into many small cubes, where a cube is seen as a cluster. In the 3D cube, all the sensor nodes are duty-cycled in the media access control layer. Second, in order to make energy efficient and extend network lifetime, the EGRC shapes an energy consumption model considering residual energy and location of sensor nodes to select the optimal cluster-heads. Moreover, the EGRC utilizes residual energy, locations, and end-to-end delay for searching for the next-hop node to maintain the reliability of data transmission. Simulation validations of the proposed algorithm are carried out to show the effectiveness of EGRC, which performs better than the representative algorithms in terms of energy efficiency, reliability, and end-to-end delay.

An Energy-Efficient Reliable Data Transmission Scheme for Complex Environmental Monitoring in Underwater Acoustic Sensor Networks

With the advance of the Internet of Underwater Things, smart things are deployed under the water and form the underwater wireless sensor networks (UWSNs), to facilitate the discovery of vast unexplored ocean volume. A routing protocol, which is not expensive in packets forwarding and energy consumption, is fundamental for sensory data gathering and transmitting in UWSNs. To address this challenge, this paper proposes Enhanced CARP (E-CARP), which is an enhanced version of the channel-aware routing protocol (CARP) developed by S. Basagni et al. , to achieve the location-free and greedy hop-by-hop packet forwarding strategy. In general, CARP does not consider the reusability of previously collected sensory data to support certain domain applications afterward, which induces data packets forwarding which may not be beneficial to applications. Besides, the PING - PONG strategy in CARP can be simplified for selecting the most appropriate relay node at each time point, when the network topology is relatively steady. These two research problems have been addressed by our E-CARP. Simulation results validate that our technique can decrease the communication cost significantly and increase the network capability to a certain extent.

E-CARP: An Energy Efficient Routing Protocol for UWSNs in the Internet of Underwater Things

Smartphones have become the most pervasive devices in people’s lives and are clearly transforming the way we live and perceive technology. Today’s smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as an accelerometer, a gyroscope, a microphone, and a camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this article, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing and analyze in depth the current state of the art on the topic. We also outline novel research challenges, along with possible directions of future work.

https://dl.acm.org/doi/pdf/10.1145/3139256

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Trust models have been recently suggested as an effective security mechanism for Wireless Sensor Networks (WSNs). Considerable research has been done on modeling trust. However, most current research work only takes communication behavior into account to calculate sensor nodes’ trust value, which is not enough for trust evaluation due to the widespread malicious attacks. In this paper, we propose an Efficient Distributed Trust Model (EDTM) for WSNs. First, according to the number of packets received by sensor nodes, direct trust and recommendation trust are selectively calculated. Then, communication trust, energy trust and data trust are considered during the calculation of direct trust. Furthermore, trust reliability and familiarity are defined to improve the accuracy of recommendation trust. The proposed EDTM can evaluate trustworthiness of sensor nodes more precisely and prevent the security breaches more effectively. Simulation results show that EDTM outperforms other similar models, e.g., NBBTE trust model.

An Efficient Distributed Trust Model for Wireless Sensor Networks

In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs.

Localization Algorithms of Underwater Wireless Sensor Networks: A Survey

Balancing energy consumption and prolonging network
lifetime have been hot topics in energy limited wireless sensor networks (WSNs). It is generally known that multiple
sensor nodes collaborating with each other to perform tasks
are an important means of energy balancing. In addition, a
reasonable task allocation strategy is also an efficient method
for task performing and energy saving. Furthermore, in order
to save energy consumption, many WSNs are organized into
clusters. Therefore, in this paper, we propose a distributed task allocation strategy for collaborative applications (DTAC)
in cluster-based WSNs. In DTAC, the service abilities of sensor
nodes are first evaluated and then the sensor nodes are classified
into different ranking domains. Based on the service abilities of
cluster members, the service ability of each cluster is calculated. 
A complex task can be first allocated to several clusters, and then
scheduled on collaborative cluster members. Simulation results
demonstrate that, compared with current related works, DTAC
is much more efficient for complex task processing in terms
of reducing energy consumption, shortening execution time, and
balancing network loads.

A Distributed Task Allocation Strategy for Collaborative Applications in Cluster-Based Wireless Sensor Networks

A wireless sensor network (WSN) consists of many resource constraint sensor nodes, which are always deployed in unattended environment. Therefore, the sensor nodes are vulnerable to failure and malicious attacks. The failed nodes have a heavily negative impact on WSNs' real-time services. Therefore, we propose a task allocation algorithm based on score incentive mechanism (TASIM) for WSNs. In TASIM, the score is proposed to reward or punish sensor nodes' task execution in cluster-based WSNs, where cluster heads are responsible for task allocation and scores' calculation. Based on the task scores, cluster members can collaborate with each other to complete complex tasks. In addition, the uncompleted tasks on failed nodes can be timely migrated to other cluster members for further execution. Furthermore, the uncompleted tasks on death nodes can be reallocated by cluster heads. Simulation results demonstrate that TASIM is quite suitable for real-time task allocation. In addition, the performance of the TASIM is clearly better than that of conventional task allocation algorithms in terms of both network load balance and energy consumption.

A task allocation algorithm based on score incentive mechanism for wireless sensor networks

The invention relates to a method for building a multi-dimension trust model in an underwater sensor network. The method includes the steps that firstly, link trust, data trust and node trust are independently calculated in time windows, communication link trust is built according to an underwater acoustic channel model, a signal modulation mode and an error control strategy, the data trust is calculated based on the similarity characteristic of perception data of neighbor nodes, and the node trust is built according to the node honesty and the node capacity; secondly, based on a logical relationship among the link trust, the data trust and the node trust, link middle trust, data middle trust and node middle trust are calculated according to a fuzzy logic method, a time decay function is built on the basis of middle trust values, and the link trust, the data trust and the node trust are updated in real time in cooperation with the dynamic water flow environment. By means of the method, the trust values of the nodes can be effectively evaluated in the complex underwater environment, and the safety performance of the network can be improved in real time.

Wang Feng

Papers

An Efficient Distributed Trust Model for Wireless Sensor Networks

Localization Algorithms of Underwater Wireless Sensor Networks: A Survey

A Distributed Task Allocation Strategy for Collaborative Applications in Cluster-Based Wireless Sensor Networks

A task allocation algorithm based on score incentive mechanism for wireless sensor networks

Method for building multi-dimension trust model in underwater sensor network