Modular Energy-Efficient and Robust Paradigms for a Disaster-Recovery Process over Wireless Sensor Networks

Robust paradigms are a necessity, particularly for emerging wireless sensor network (WSN) applications. The lack of robust and efficient paradigms causes a reduction in the provision of quality of service (QoS) and additional energy consumption. In this paper, we introduce modular energy-efficient and robust paradigms that involve two archetypes: (1) the operational medium access control (O-MAC) hybrid protocol and (2) the pheromone termite (PT) model. The O-MAC protocol controls overhearing and congestion and increases the throughput, reduces the latency and extends the network lifetime. O-MAC uses an optimized data frame format that reduces the channel access time and provides faster data delivery over the medium. Furthermore, O-MAC uses a novel randomization function that avoids channel collisions. The PT model provides robust routing for single and multiple links and includes two new significant features: (1) determining the packet generation rate to avoid congestion and (2) pheromone sensitivity to determine the link capacity prior to sending the packets on each link. The state-of-the-art research in this work is based on improving both the QoS and energy efficiency. To determine the strength of O-MAC with the PT model; we have generated and simulated a disaster recovery scenario using a network simulator (ns-3.10) that monitors the activities of disaster recovery staff; hospital staff and disaster victims brought into the hospital. Moreover; the proposed paradigm can be used for general purpose applications. Finally; the QoS metrics of the O-MAC and PT paradigms are evaluated and compared with other known hybrid protocols involving the MAC and routing features. The simulation results indicate that O-MAC with PT produced better outcomes.https://doi.org/10.3390/s15071616

Data Collection and Capacity Analysis in Large-scale Wireless Sensor Networks

In this dissertation, we study data collection and its achievable network capacity in Wireless Sensor Networks (WSNs). Firstly, we investigate the data collection issue in dual-radio multi-channel WSNs under the protocol interference model. We propose a multi-path scheduling algorithm for snapshot data collection, which has a tighter capacity bound than the existing best result, and a novel continuous data collection algorithm with comprehensive capacity analysis. Secondly, considering most existing works for the capacity issue are based on the ideal deterministic network model, we study the data collection problem for practical probabilistic WSNs. We design a cell-based path scheduling algorithm and a zone-based pipeline scheduling algorithm for snapshot and continuous data collection in probabilistic WSNs, respectively. By analysis, we show that the proposed algorithms have competitive capacity performance compared with existing works. Thirdly, most of the existing works studying the data collection capacity issue are for centralized synchronous WSNs. However, wireless networks are more likely to be distributed asynchronous systems. Therefore, we investigate the achievable data collection capacity of realistic distributed asynchronous WSNs and propose a data collection algorithm with fairness consideration. Theoretical analysis of the proposed algorithm shows that its achievable network capacity is order-optimal as centralized and synchronized algorithms do and independent of network size. Finally, for completeness, we study the data aggregation issue for realistic probabilistic WSNs. We propose order-optimal scheduling algorithms for snapshot and continuous data aggregation under the physical interference model

Time-Driven Access and Forwarding for Industrial Wireless Multihop Networks

The deployment of wireless technologies in industrial networks is very promising mainly due to their inherent flexibility. However, current wireless solutions lack the capability to provide the deterministic, low delay service required by many industrial applications. Moreover, the high level of interference generated by industrial equipment limits the coverage that ensures acceptable performance. Multi-hop solutions, when combining frame forwarding with higher node density, have the potential to provide the needed coverage while keeping radio communication range short. However, in multi-hop solutions the medium access time at each of the nodes traversed additively contributes to the end-to-end delay and the forwarding delay (i.e., the time required for packets to be processed, switched, and queued) at each node is to be added as well. This paper describes Time-driven Access and Forwarding (TAF), a solution for guaranteeing deterministic delay, at both the access and forwarding level, in wireless multi-hop networks, analyzes its properties, and assesses its performance in industrial scenario

Drone’s node placement algorithm with routing protocols to enhance surveillance

Flying ad-hoc network (FANET) is characterized by key component features such as communication scheme, energy awareness, and task distribution. In this research, a surveillance space considering standard petroleum pipe was created with three drones viz: drone 1 (D1), master drone (DM), and drone 2 (D2) to survey as FANET. DM aggregate packets from D1, D2 and communicate with the static ground control station (SGCS). The starting point of the three drones and their trajectories during deployment were calculated and simulated. Selection of DM, D1, and D2 was done using battery level before take-off. Simulation results show take-off time difference which depends on the distance of each drone to the SGCS during deployment. D1 take-off first, while DM and D2 followed after 0.0704 and 0.1314 ms respectively. The position-oriented routing protocols results indicated variation of information flow within time notch due to variation in the density of the transmitted packets. Packets delivery periods are 0.00136×103 sec, 0.00110×103 sec, and 0.00246×103 sec for time notch 1, 2, and aggregating time notch respectively. From the results obtained, two algorithms were used successfully in deploying the drone

Long-Term Stable Communication in Centrally Scheduled Low-Power Wireless Networks

With the emergence of the Internet of Things (IoT), more devices are connected than ever before. Most of these communicate wirelessly, forming Wireless Sensor Networks. In recent years, there has been a shift from personal networks, like Smart Home, to industrial networks. Industrial networks monitor pipelines or handle the communication between robots in factories. These new applications form the Industrial Internet of Things (IIoT). Many industrial applications have high requirements for communication, higher than the requirements of common IoT networks. Communications must stick to hard deadlines to avoid harm, and they must be highly reliable as skipping information is not a viable option when communicating critical information. Moreover, communication has to remain reliable over longer periods of time. As many sensor locations do not offer a power source, the devices have to run on battery and thus have to be power efficient. Current systems offer solutions for some of these requirements. However, they especially lack long-term stable communication that can dynamically adapt to changes in the wireless medium.In this thesis, we study the problem of stable and reliable communication in centrally scheduled low-power wireless networks. This communication ought to be stable when it can dynamically adapt to changes in the wireless medium while keeping latency at a minimum. We design and investigate approaches to solve the problem of low to high degrees of interference in the wireless medium. We propose three solutions to overcome interference: MASTER with Sliding Windows brings dynamic numbers of retransmissions to centrally scheduled low-power wireless networks, OVERTAKE allows to skip nodes affected by interference along the path, and AUTOBAHN combines opportunistic routing and synchronous transmissions with the Time-Slotted Channel Hopping (TSCH) MAC protocol to overcome local wide-band interference with the lowest possible latency. We evaluate our approaches in detail on testbed deployments and provide open-source implementations of the protocols to enable others to build their work upon them

MobiBone:An energy-efficient and adaptive network protocol to support short rendezvous between static and mobile wireless sensor nodes

To ensure long network life-time, the duty-cycle of wireless sensor networks is often set to be low. This brings with itself the risk of either missing a sent packet or delaying the message delivery and dissemination depending on the duration of the duty-cycle and number of hops. This risk is increased in wireless sensor applications with hybrid architecture, in which a static ground wireless sensor network interacts with a network of mobile sensor nodes. Dynamicity and mobility of mobile nodes may lead to only a short rendezvous between them and the backbone network to exchange data. Additionally, such dynamicity generates complex and often random data traffic patterns. To support successful data delivery in case of short rendezvous between static and mobile wireless sensor nodes, we propose MobiBone, an energy-efficient and adaptive network protocol that utilizes data packet traffic to characterize the sleep schedule. Our simulation results show that compared with network protocols with fixed duty-cycles, MobiBone offers a good trade-off between energy consumption, latency, and detection rate of mobile nodes (which indicates awakens of the backbone network at crucial times of mobile node presence)