Thanh Dinh

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud.

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud.

A Novel Location-Centric IoT-Cloud Based On-Street Car Parking Violation Management System in Smart Cities

Nowadays, in big cities, parking management is a critical issue from both the driver’s side and the city government’s side. From the driver’s side, how to find an available parking lot in a city is a considerable concern. As a result, smart parking systems recently have received great interest, both in academia and industry. From the city government’s side, how to manage and distribute such a limited public parking resource efficiently to give every visitor a fair chance of finding an on-street parking lot is also a considerable concern. However, existing studies of smart parking management focus only on assisting the driver’s side to find available parking spaces. This study aims to raise a new perspective on such smart parking management and to propose a novel location-centric IoT-cloud-based parking violation management system. The system is designed to assist authoritative officers in finding parking violations easily and recommends the least cost path for officers so that officers can achieve their highest productivity in finding parking violations and issuing parking tickets. Experimental results show that the system not only improves the productivity of officers in finding parking violations and issuing tickets, but also helps reduce the traveling cost of officers and to reduce the average violation period of violating cars considerably.

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model.

Distributed cell selection for scheduling function in 6TiSCH networks

Recently, the new IETF 6TiSCH Working Group (WG) was created to enable the IPv6 over the deterministic Time Slotted Channel Hopping (TSCH) mode of the 802.15.4e standard for the Industrial Internet of Things (IIoT). Due to the dynamic nature of the target network environment, the 6TiSCH WG is now calling for an efficient distributed scheduling through a Scheduling Function in which the neighbor nodes negotiate with one another to add/delete cells to satisfy the bandwidth requirement. A Scheduling Function consists of the following two main points: when a node should add/delete one or more cells to its neighbor, and the cells that should be selected. Although several Scheduling Function studies have been conducted, the primary focus of the current works is the first point, while the optimal selection method regarding the cells remains an unresolved issue. In this paper, a reliable distributed cell-selection mechanism for the Scheduling Function in the 6TiSCH networks is proposed. The simulation and experiment results show that the proposed mechanism helps in the reductions of the negotiation-error ratio, the number of colliding cells and the signaling overhead compared with the state-of-the-art approaches.

A rapid joining scheme based on fuzzy logic for highly dynamic IEEE 802.15.4e time-slotted channel hopping networks

The IEEE 802.15.4e standard is an amendment of the IEEE 802.15.4-2011 protocol by introducing time-slotted channel hopping access behavior mode. However, the IEEE 802.15.4e only defines time-slotted channel hopping link-layer mechanisms without an investigation of network formation and communication scheduling which are still open issues to the research community. This article investigates the network formation issue of the IEEE 802.15.4e time-slotted channel hopping networks. In time-slotted channel hopping networks, a joining node normally takes a long time period to join the network because the node has to wait until there is at least one enhanced beacon message advertised by synchronized nodes (synchronizers) in the network on its own synchronization channel. This leads to a long joining delay and high energy consumption during the network formation phase, especially so in highly dynamic networks in which nodes join or rejoin frequently. To enable a rapid time-slotted channel hopping network formation, this article proposes a new design for slotframe structure and a novel adaptive joining scheme based on fuzzy logic. Our proposed scheme enables a synchronizer to be able to adaptively determine an appropriate number of enhanced beacons it should advertise, based on the number of available synchronizers in the network, so that joining nodes can achieve a short joining time while energy consumption of enhanced beacon advertisement at the synchronizers is optimized. Through extensive mathematical analysis and experimental results, we show that the proposed scheme achieves a significant improvement in terms of joining delay compared to state-of-the-art studies.

L-MAC

This paper analyzes the trade-off issue between energy efficiency and packet delivery latency among existing duty-cycling MAC protocols in wireless sensor networks for low data-rate periodic-reporting applications. We then propose a novel and practical wake-up time self-learning MAC (L-MAC) protocol in which the key idea is to reuse beacon messages of receiver-initiated MAC protocols to enable nodes to coordinate their wakeup time with their parent nodes without incurring extra communication overhead. Based on the self-learning mechanism we propose, L-MAC builds an on-demand staggered scheduler to allow any node to forward packets continuously to the sink node. We present an analytical model, and conduct extensive simulations and experiments on Telosb sensors to show that L-MAC achieves significant higher energy efficiency compared to state-of-the-art asynchronous MAC protocols and a similar result of latency compared to synchronous MAC protocols. In particular, under QoS requirements with an upper bound value for one-hop packet delivery latency within 1ź s and a lower bound value for packet delivery ratio within 95%, results show that the duty cycle of L-MAC is improved by more than 3.8 times and the end-to-end packet delivery latency of L-MAC is reduced by more than 7 times compared to those of AS-MAC and other state-of-the-art MAC protocols, respectively, in case of the packet generation interval of 1ź min. L-MAC hence achieves high performance in both energy efficiency and packet delivery latency.

Actor-oriented directional anycast routing in wireless sensor and actor networks with smart antennas

Current routing protocols in wireless sensor and actor networks (WSANs) shows a lack of unification for different traffic patterns because the communication for sensor to actor and that for actor to actor are designed separately. Such a design poses a challenge for interoperability between sensors and actors. With the presence of rich-resource actor nodes, we argue that to improve network lifetime, the problem transforms from reducing overall network energy consumption to reducing energy consumption of constrained sensor nodes. To reduce energy consumption of sensor nodes, especially in challenging environments with coverage holes/obstacles, we propose that actor nodes should share forwarding tasks with sensor nodes. To enable such a feature, efficient interoperability between sensors and actors is required, and thus a unified routing protocol for both sensors and actors is needed. This paper explores capabilities of directional transmission with smart antennas and rich-resource actors to design a novel unified actor-oriented directional anycast routing protocol (ADA) which supports arbitrary traffic in WSANs. The proposed routing protocol exploits actors as main routing anchors as much as possible because they have better energy and computing power compared to constraint sensor nodes. In addition, a directional anycast routing approach is also proposed to further reduce total delay and energy consumption of overall network. Through extensive experiments, we show that ADA outperforms state-of-the-art protocols in terms of packet delivery latency, network lifetime, and packet reliability. In addition, by offer fault tolerant features, ADA also performs well in challenging environments where coverage holes and obstacles are of concerns.

A location-based interactive model for Internet of Things and cloud (IoT-cloud)

This paper presents a location-based interactive model for Internet of Things (IoT) and cloud integration (IoT-cloud). In the model, IoT-cloud provides sensing service on demand based on interest and location of mobile users. Cloud plays a role as a virtual sink which makes schedule for physical sensor networks on-demand based on locations of mobile users. Through extensive analysis results, we show that the model scheme achieve a significant improvement compared to traditional wireless sensor networks (WSNs).

An efficient sensor-cloud interactive model for on-demand latency requirement guarantee

This paper proposes an efficient interactive model for sensor-cloud integration to enable the sensor-cloud to provide on-demand sensing services for multiple applications with different latency requirements at the same time. In the model, we design an aggregation mechanism for the sensor-cloud to aggregate application requests so that workloads required for constrained sensor nodes are minimized to save energy. Sensing packet delivery latency from sensor-to-cloud is controlled by the sensor-cloud based feedback control theory. Based on feedbacks from the sensor-cloud, physical sensor nodes optimize their scheduling accordingly to save energy while satisfying latency requirements of all applications. Analysis and experimental results show that our proposed system effectively controls the latency of sensing flows with low signaling overhead and high energy efficiency compared to the state-of-the-art scheme.

Design and implementation of a container-based virtual client architecture for interactive digital signage systems:

Interactive digital signage is an important Internet of things application and has been becoming a common type of human–machine interface for multiple users. By integrating with wireless sensor networks, a digital signage system can provide smart features and on-demand contents to users. However, the performance of current interactive digital signage systems depends heavily on the server. An increasingly high number of digital signage clients and sensor devices attached to the system generating a huge amount of traffic flowed to the server may create bottleneck, management and scalability issues at the server, especially in large-scale digital signage systems. In addition, the current system requires application installation and configuration at the client side, thus leading to a high cost and complexity of deployment as well as management. This article proposes and implements a container-based distributed virtual client architecture for interactive digital signage to solve the above issues. In the proposed architecture, a number of digital signage clients and Internet of things devices are virtualized and managed by a container-based middleware. Each container-based middleware is responsible to manage and process data for a cluster of digital signage clients and corresponding Internet of things devices to (1) reduce load to server and improve the service performance and (2) enable lightweight clients to reduce cost and complexity in deployment as well as management. Implementation and obtained analysis results show the advantages of the proposed architecture.