J. Sens. Actuator Netw., Volume 5, Issue 4 (December 2016) – 6 articles

Cloud robotics in smart cities is an emerging paradigm that enables autonomous robotic agents to communicate and collaborate with a cloud computing infrastructure. It complements the Internet of Things (IoT) by creating an expanded network where robots offload data-intensive computation to the ubiquitous cloud to ensure quality of service (QoS). However, offloading for robots is significantly complex due to their unique characteristics of mobility, skill-learning, data collection, and decision-making capabilities. In this paper, a generic cloud robotics framework is proposed to realize smart city vision while taking into consideration its various complexities. Specifically, we present an integrated framework for a crowd control system where cloud-enhanced robots are deployed to perform necessary tasks. The task offloading is formulated as a constrained optimization problem capable of handling any task flow that can be characterized by a Direct Acyclic Graph (DAG). We consider two scenarios of minimizing energy and time, respectively, and develop a genetic algorithm (GA)-based approach to identify the optimal task offloading decisions. The performance comparison with two benchmarks shows that our GA scheme achieves desired energy and time performance. We also show the adaptability of our algorithm by varying the values for bandwidth and movement. The results suggest their impact on offloading. Finally, we present a multi-task flow optimal path sequence problem that highlights how the robot can plan its task completion via movements that expend the minimum energy. This integrates path planning with offloading for robotics. To the best of our knowledge, this is the first attempt to evaluate cloud-based task offloading for a smart city crowd control system. Full article

Side-sweep accidents are one of the major causes of loss of life and property damage on highways. This type of accident is caused by a driver initiating a lane change while another vehicle is blocking the road in the target lane. In this article, we are trying to quantify the degree to which different implementations of vehicle-to-vehicle (V2V) communication could reduce the occurrence of such accidents. We present the design of a simulator that takes into account common sources of lack of driver awareness such as blind-spots and lack of attention. Then, we study the impact of both traditional, non-technological communication means such as turning signals as well as unidirectional and bidirectional V2V communications. Full article

Delay Tolerant Networking (DTN) is well suited to challenging environments, defined by the lack of reliable end-to-end communication paths to the destination. However, the available energy is not considered in the majority of existing DTN routing protocols when they make forwarding decisions. This limits both delivery probabilities and the network lifetimes in energy-constrained applications. This paper investigates energy-aware routing protocols for wildlife tracking application to transmit data from attached sensors on the animal’s back to data collection base stations. We propose three new network protocol strategies to extend common DTN routing protocols, and consider the available energy to achieve efficient utilization of the node’s energy in transmission and sensing. These strategies enhance packet delivery rates up to 13% by carefully using the limited energy resources. We simulate two different animal tracking scenarios and show that the new strategies provide significant performance improvement under different scenarios. Full article

Named Data Networking (NDN) has been recently proposed as a prominent solution for content delivery in the Internet of Vehicles (IoV), where cars equipped with a variety of wireless communication technologies exchange information aimed to support safety, traffic efficiency, monitoring and infotainment applications. The main NDN tenets, i.e., name-based communication and in-network caching, perfectly fit the demands of time- and spatially-relevant content requested by vehicles regardless of their provenance. However, existing vehicular NDN solutions have not been targeted to wisely ensure prioritized traffic treatment based on the specific needs of heterogeneous IoV content types. In this work, we propose a holistic NDN solution that, according to the demands of data traffic codified in NDN content names, dynamically shapes the NDN forwarding decisions to ensure the appropriate prioritization. Specifically, our proposal first selects the outgoing interface(s) (i.e., 802.11, LTE) for NDN packets and then properly tunes the timing of the actual transmissions. Simulation results show that the proposed enhancements succeed in achieving differentiated traffic treatment, while keeping traffic load under control. Full article

Recent technological advancements allowed widening the applicability scope of the RFID (Radio Frequency Identification) technology from item identification to sensor-enabled computation platforms. This feature, added to the native radio energy-harvesting capability and the extremely low power consumption, has attracted the interest of research and industrial communities and pushed them to include the RFID technology into a global network of interconnected objects, as envisaged by the Internet of Things paradigm. In the last few years, standardization bodies have made significant efforts to design lightweight approaches, such as CoAP (Constrained Application Protocol), to efficiently manage resource-constrained nodes by using traditional web interfaces; nevertheless, RFID integration is not addressed yet. In this paper, we propose a CoAP-compliant solution where RFID tags, behaving as virtual CoAP servers, are directly accessible by remote CoAP clients via a reader, which acts as a CoAP proxy. A real testbed, addressing key aspects, such as tag addressing, discovery and management of CoAP requests via RFID operations, is deployed to validate the feasibility of the proposal. Experimental results show rapid response times: less than 60 ms are requested for resource retrieval, while from 80 to 360 ms for sending data to the RFID device, depending on the tag memory dimension. Full article

The development of the Internet of Things infrastructure requires the deployment of millions of heterogeneous sensors embedded in the environment. The powering of these sensors cannot be done with wired connections, and the use of batteries is often impracticable. Energy harvesting is the common proposed solution, and many devices have been developed for this purpose, using light, mechanical vibrations, and temperature differences as energetic sources. In this paper we present a novel energy-harvester device able to capture the kinetic energy from a fluid in motion and transform it in electrical energy. This device, named FLEHAP (FLuttering Energy Harvester for Autonomous Powering), is based on an aeroelastic effect, named fluttering, in which a totally passive airfoil shows large and regular self-sustained motions (limit cycle oscillations) even in extreme conditions (low Reynolds numbers), thanks to its peculiar mechanical configuration. This system shows, in some centimeter-sized configurations, an electrical conversion efficiency that exceeds 8% at low wind speed (3.5 m/s). By using a specialized electronic circuit, it is possible to store the electrical energy in a super capacitor, and so guarantee self-powering in such environmental conditions. Full article