Implementation and evaluation of the sensornet protocol for Contiki

Sensornet Protocol (SP) is a link abstraction layer between the network layer and the link layer for sensor networks. SP was proposed as the core of a future-oriented sensor node architecture that allows flexible and optimized combination between multiple coexisting protocols. This thesis implements the SP sensornet protocol on the Contiki operating system in order to: evaluate the effectiveness of the original SP services; explore further requirements and implementation trade-offs uncovered by the original proposal. We analyze the original SP design and the TinyOS implementation of SP to design the Contiki port. We implement the data sending and receiving part of SP using Contiki processes, and the neighbor management part as a group of global routines. The evaluation consists of a single-hop traffic throughput test and a multihop convergecast test. Both tests are conducted using both simulation and experimentation. We conclude from the evaluation results that SP's link-level abstraction effectively improves modularity in protocol construction without sacrificing performance, and our SP implementation on Contiki lays a good foundation for future protocol innovations in wireless sensor networks

Enhancing Energy Efficiency of Wireless Sensor Network through the Design of Energy Efficient Routing Protocol

Wireless Sensor Network (WSN) is known to be a highly resource constrained class of network where energy consumption is one of the prime concerns. In this research, a cross layer design methodology was adopted to design an energy efficient routing protocol entitled “Position Responsive Routing Protocol” (PRRP). PRRP is designed to minimize energy consumed in each node by (1) reducing the amount of time in which a sensor node is in an idle listening state and (2) reducing the average communication distance over the network. The performance of the proposed PRRP was critically evaluated in the context of network lifetime, throughput, and energy consumption of the network per individual basis and per data packet basis. The research results were analyzed and benchmarked against the well-known LEACH and CELRP protocols. The outcomes show a significant improvement in the WSN in terms of energy efficiency and the overall performance of WSN

Wired and Wireless Reliable Real-Time Communication in Industrial Systems

In modern factory automation systems, data communication plays a vital role. Different nodes like control systems, sensors and actuators can communicate over a wireless or wired industrial network. The data traffic generated is often scheduled for periodic transmission, where each single message or packet must arrive in time. For this real-time communication, methods have been developed to support communication services with a guaranteed throughput and delay bound for such periodic traffic, but merely under the assumption of error-free communication. However, the possibility for errors in the transmission still exists due to, e.g. noise or interference. A node receiving sensor values from a sensor in the system might then be forced to rely upon an older sensor value from the latest period, possibly leading to inaccuracies in control loops which can compromise the functioning of the system. In safety-critical systems, redundant networks or communication channels are frequently added to cope with errors, leading to more expensive systems. In this chapter, we will describe an alternative approach where erroneous data packets are retransmitted in a way that does not jeopardise any earlier stated real-time guarantees for ordinary transmissions. Using our framework, the reliability of real-time communication can be increased in a more cost-efficient way. We describe in this chapter an overview of our framework for reliable real-time communication, while details of our approach can be found in our earlier publications. In the light of the emerging use of wireless communication, the framework proves to be especially useful due to the high bit error rate inherent to the wireless medium. However, the framework is naturally also attractive for wired communication systems

Implementing Efficient and Multi-Hop Image Acquisition In Remote Monitoring IoT systems using LoRa Technology

Remote sensing or monitoring through the deployment of wireless sensor networks (WSNs) is considered an economical and convenient manner in which to collect information without cumbersome human intervention. Unfortunately, due to challenging deployment conditions, such as large geographic area, and lack of electricity and network infrastructure, designing such wireless sensor networks for large-scale farms or forests is difficult and expensive. Many WSN-appropriate wireless technologies, such as Wi-Fi, Bluetooth, Zigbee and 6LoWPAN, have been widely adopted in remote sensing. The performance of these technologies, however, is not sufficient for use across large areas. Generally, as the geographical scope expands, more devices need to be employed to expand network coverage, so the number and cost of devices in wireless sensor networks will increase dramatically. Besides, this type of deployment usually not only has a high probability of failure and high transmission costs, but also imposes additional overhead on system management and maintenance. LoRa is an emerging physical layer standard for long range wireless communication. By utilizing chirp spread spectrum modulation, LoRa features a long communication range and broad signal coverage. At the same time, LoRa also has low power consumption. Thus, LoRa outperforms similar technologies in terms of hardware cost, power consumption and radio coverage. It is also considered to be one of the promising solutions for the future of the Internet of Things (IoT). As the research and development of LoRa are still in its early stages, it lacks sufficient support for multi-packet transport and complex deployment topologies. Therefore, LoRa is not able to further expand its network coverage and efficiently support big data transfers like other conventional technologies. Besides, due to the smaller payload and data rate in LoRa physical design, it is more challenging to implement these features in LoRa. These shortcomings limit the potential for LoRa to be used in more productive application scenarios. This thesis addresses the problem of multi-packet and multi-hop transmission using LoRa by proposing two novel protocols, namely Multi-Packet LoRa (MPLR) and Multi-Hop LoRa (MHLR). LoRa's ability to transmit large messages is first evaluated in this thesis, and then the protocols are well designed and implemented to enrich LoRa's possibilities in image transmission applications and multi-hop topologies. MPLR introduces a reliable transport mechanism for multi-packet sensory data, making its network not limited to the transmission of small sensor data only. In collaboration with a data channel reservation technique, MPLR is able to greatly mitigate data collisions caused by the increased transmission time in laboratory experiments. MHLR realizes efficient routing in LoRa multi-hop transmission by utilizing the power of machine learning. The results of both indoor and outdoor experiments show that the machine learning based routing is effective in wireless sensor networks

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs