Edge Network Routing Protocol Base on Target Tracking Scenario

Edge computing perfectly integrates cloud computing centers and edge-end devices together, but there are not many related researches on how the edge-end node devices work to form an edge network and what the protocols used to implement the communication among nodes in the edge network. Aiming at the problem of coordinated communication among edge nodes in the current edge computing network architecture, this paper proposes an edge network routing and forwarding protocol based on target tracking scenarios. This protocol can meet the dynamic changes of node locations, and the elastic expansion of node scale. Individual node failures will not affect the overall network, and the network ensures efficient real-time with less communication overhead. The experimental results display that the protocol can effectively reduce the communications volume of the edge network, improve the overall efficiency of the network, and set the optimal sampling period, so as to ensure that the network delay is minimized.

Proposed Smart Monitoring System for the Detection of Bee Swarming

This paper presents a bee-condition-monitoring system incorporated with a deep-learning process to detect bee swarming. This system includes easy-to-use image acquisition and various end node approaches for either on-site or cloud-based mechanisms. This system also incorporates a new smart CNN engine called Swarm-engine for detecting bees and the issue of notifications in cases of bee swarming conditions to the apiarists. First, this paper presents the authors’ proposed implementation system architecture and end node versions that put it to the test. Then, several pre-trained networks of the authors’ proposed CNN Swarm-engine were also validated to detect bee-clustering events that may lead to swarming. Finally, their accuracy and performance towards detection were evaluated using both cloud cores and embedded ARM devices on parts of the system’s different end-node implementations.

Time Switching Based Wireless Powered Relay Transmission with Uplink NOMA

Non-orthogonal multiple access (NOMA) utilizes power domain multiplexing to improve spectrum efficiency compared with orthogonal multiple access (OMA). In the Internet of Things (IoT) uplink NOMA networks, if the channel between the far-end node and the base station is in deep fading, allocating larger transmitting power for this node cannot achieve higher spectrum efficiency and overall system throughput. Relay cooperative communication reduces the transmitting power at the far-end node but leads to extra energy expenditure at the relay node. Fortunately, simultaneous wireless information and power transfer (SWIPT) is advocated in energy-constrained IoT networks to save energy consumption. However, early works all focus on energy harvesting (EH) from one source node or one dedicated power supply station. In this paper, we propose a time switching based wireless powered relay transmission model with uplink NOMA where our EH technique can harvest energy from two simultaneously transmitting nodes. More importantly, by optimizing relay position more energy is harvested from the near-end node at the relay and relay signal attenuation to the destination is reduced as well. Furthermore, the closed-form expressions of outage probability and overall system throughput are derived, and numerical results prove that NOMA in our EH scheme achieves better performance compared to the traditional EH scheme and OMA by optimizing the position of the relay node, time switching factor and so on.

Directed closure coefficient and its patterns

The triangle structure, being a fundamental and significant element, underlies many theories and techniques in studying complex networks. The formation of triangles is typically measured by the clustering coefficient, in which the focal node is the centre-node in an open triad. In contrast, the recently proposed closure coefficient measures triangle formation from an end-node perspective and has been proven to be a useful feature in network analysis. Here, we extend it by proposing the directed closure coefficient that measures the formation of directed triangles. By distinguishing the direction of the closing edge in building triangles, we further introduce the source closure coefficient and the target closure coefficient. Then, by categorising particular types of directed triangles (e.g., head-of-path), we propose four closure patterns. Through multiple experiments on 24 directed networks from six domains, we demonstrate that at network-level, the four closure patterns are distinctive features in classifying network types, while at node-level, adding the source and target closure coefficients leads to significant improvement in link prediction task in most types of directed networks.

Towards Dependable IoT via Interface Selection: Predicting Packet Delivery at the End Node in LoRaWAN Networks

Estimating channel conditions to predict packet delivery can be exploited as a powerful tool to ensure wireless networks dependability. In this article we explore the practical application of this idea from the end-device perspective, using the LoRaWAN protocol stack. We aim to understand if packet delivery can be estimated considering different levels of feedback at the end-device. For that, an extensive data collection campaign is carried out. Through an analysis of the obtained traces, we establish correlations between connectivity metrics at the end node and the fact that a packet is received at the gateway. The study is complemented considering different levels of feedback: (i) No feedback, (ii) enabling acknowledgements frames, and (iii) considering application/control plane data about the channel status at the gateway side. The results show that it is possible to estimate packet delivery in all the evaluated cases.

Implementation of Multiprocessing and Multithreading for End Node Middleware Control on Internet of Things Devices

Previously, an educational robot system was built by incorporating Internet of Things (IoT) elements. Over time, this educational robot has been implanted with a middleware. Middleware has a role in receiving command data from the real-time database, access sensors, actuators, and sending feedback. Middleware contains protocols that translate commands between high-level programming and Raspberry Pi hardware. The focus of this research is to improve the performance of the middleware to pursue processing time efficiency. For this reason, it is necessary to implement multiprocessing and multithreading in handling several tasks. The CPU division has been adjusted automatically to not work on just one core or block of memory. Several program functions can run in parallel and reduce program execution time efficiently. The tasks handled are sensor reading and actuator control in the form of a motor. Testing has been carried out to perform multiprocessing and multithreading tasks to process six sensors and five actuators. Multiprocessing requires an average of 1.00% to 15.00% CPU usage and 2.70% memory usage. Meanwhile, multithreading involves an average of 1.00% to 71.00% CPU usage and 3.30% memory usage.

CONSTRUCTION OF LORA DATA POWER SENSOR FROM GIOT AND ACSIP USING SQL TECHNIQUE

LoRa is one of developing data commuication infrastructures which can be enabled sensors on a large scale, wide area operations, and low energy consumption.the benefit of Low energy consumption in LoRa impacted on the length of data, the spread factor and the type of operation. by the challanges in smart building, LoRa can be best solution to cover wide area sensor network. and one of the critical points is how to ensure the data can be trusted. The purpose of this research is to observe the data taken from the power used in single phase electrical in residential consumers. the LoRa infrastructure used to deliver the data is using GioT and Acsip as the gateway and End Node, then involving SQL technique as a programming tools to refine the data.

Performance Improvement in Conventional AODV Using Energy Efficient, Manifold Route Discovery Scheme

The decentralized network formed without any assistance of the fixed infrastructure and just by the employing the volunteering mobile or the portable devices that work in a cooperative manner along with the other devices that are clubbed in the network are inbuilt with the capacity of providing a best data conveyance facility utilizing the unicast, multicast and the broadcast methods of the routing strategies. Despite the capabilities of these type of networks, it faces difficulties in devising a strategy of routing according to the dynamic nature of the distributed network. The reactive type or the on demand routing are highly used over the proactive way of routing in the decentralized network as the performance of the former is better compared to the latter. As the mobile device employed are capable are moving from its position irrespective of time, and they behave as the route and as well as the end node or the initiating node. The important factors to be considered while forming the route is the power required for transmission and the current position of the nodes, this is quiet tedious. The study in the paper provides the importance of the on demand routing distance vector routing for the distributed network that are linked in a adhoc manner and analysis all the existing on demand distance vector routing strategies and form a new manifold route discovery scheme to improve the conventional_AODV. The method devised to improve the conventional_AODV proves to be efficient when simulated using the NS-3 on the basis of the packet delivery rate, load balancing and the energy usage.