Coordination and Self-Adaptive Communication Primitives for Low-Power Wireless Networks

The Internet of Things (IoT) is a recent trend where objects are augmented with computing and communication capabilities, often via low-power wireless radios. The Internet of Things is an enabler for a connected and more sustainable modern society: smart grids are deployed to improve energy production and consumption, wireless monitoring systems allow smart factories to detect faults early and reduce waste, while connected vehicles coordinate on the road to ensure our safety and save fuel. Many recent IoT applications have stringent requirements for their wireless communication substrate: devices must cooperate and coordinate, must perform efficiently under varying and sometimes extreme environments, while strict deadlines must be met. Current distributed coordination algorithms have high overheads and are unfit to meet the requirements of today\u27s wireless applications, while current wireless protocols are often best-effort and lack the guarantees provided by well-studied coordination solutions. Further, many communication primitives available today lack the ability to adapt to dynamic environments, and are often tuned during their design phase to reach a target performance, rather than be continuously updated at runtime to adapt to reality.In this thesis, we study the problem of efficient and low-latency consensus in the context of low-power wireless networks, where communication is unreliable and nodes can fail, and we investigate the design of a self-adaptive wireless stack, where the communication substrate is able to adapt to changes to its environment. We propose three new communication primitives: Wireless Paxos brings fault-tolerant consensus to low-power wireless networking, STARC is a middleware for safe vehicular coordination at intersections, while Dimmer builds on reinforcement learning to provide adaptivity to low-power wireless networks. We evaluate in-depth each primitive on testbed deployments and we provide an open-source implementation to enable their use and improvement by the community

INTERMITTENTLY CONNECTED DELAY-TOLERANT WIRELESS SENSOR NETWORKS

Intermittently Connected Delay-Tolerant Wireless Sensor Networks (ICDT-WSNs), a branch of Wireless Sensor Networks (WSNs), have features of WSNs and the intermittent connectivity of Opportunistic Networks. The applications of ICDT-WSNs are increasing in recent years; however, the communication protocols suitable for this category of networks often fall short. Most of the existing communication protocols are designed for either WSNs or Opportunistic Networks with sufficient resources and tend to be inadequate for direct use in ICDT-WSNs. In this dissertation, we study ICDT-WSNs from the perspective of the characteristics, chal- lenges and possible solutions. A high-level overview of ICDT-WSNs is given, followed by a study of existing work and our solutions to address the problems of routing, flow control, error control, and storage management. The proposed solutions utilize the utility level of nodes and the connectedness of a network. In addition to the protocols for information transmissions to specific destinations, we also propose efficient mechanisms for information dissemination to arbitrary destinations. The study shows that our proposed solutions can achieve better performance than other state of the art communication protocols without sacrificing energy efficiency

Towards video streaming in IoT environments: vehicular communication perspective

Multimedia oriented Internet of Things (IoT) enables pervasive and real-time communication of video, audio and image data among devices in an immediate surroundings. Today's vehicles have the capability of supporting real time multimedia acquisition. Vehicles with high illuminating infrared cameras and customized sensors can communicate with other on-road devices using dedicated short-range communication (DSRC) and 5G enabled communication technologies. Real time incidence of both urban and highway vehicular traffic environment can be captured and transmitted using vehicle-to-vehicle and vehicle-to-infrastructure communication modes. Video streaming in vehicular IoT (VSV-IoT) environments is in growing stage with several challenges that need to be addressed ranging from limited resources in IoT devices, intermittent connection in vehicular networks, heterogeneous devices, dynamism and scalability in video encoding, bandwidth underutilization in video delivery, and attaining application-precise quality of service in video streaming. In this context, this paper presents a comprehensive review on video streaming in IoT environments focusing on vehicular communication perspective. Specifically, significance of video streaming in vehicular IoT environments is highlighted focusing on integration of vehicular communication with 5G enabled IoT technologies, and smart city oriented application areas for VSV-IoT. A taxonomy is presented for the classification of related literature on video streaming in vehicular network environments. Following the taxonomy, critical review of literature is performed focusing on major functional model, strengths and weaknesses. Metrics for video streaming in vehicular IoT environments are derived and comparatively analyzed in terms of their usage and evaluation capabilities. Open research challenges in VSV-IoT are identified as future directions of research in the area. The survey would benefit both IoT and vehicle industry practitioners and researchers, in terms of augmenting understanding of vehicular video streaming and its IoT related trends and issues

Bandwidth and Energy-Efficient Route Discovery for Noisy Mobile Ad-Hoc Networks

Broadcasting is used in on-demand routing protocols to discover routes in Mobile Ad-hoc Networks (MANETs). On-demand routing protocols, such as Ad-hoc On-demand Distance Vector (AODV) commonly employ pure flooding based broadcasting to discover new routes. In pure flooding, a route request (RREQ) packet is broadcast by the source node and each receiving node rebroadcasts it. This continues until the RREQ packet arrives at the destination node. Pure flooding generates excessive redundant routing traffic that may lead to the broadcast storm problem (BSP) and deteriorate the performance of MANETs significantly. A number of probabilistic broadcasting schemes have been proposed in the literature to address BSP. However, these schemes do not consider thermal noise and interference which exist in real life MANETs, and therefore, do not perform well in real life MANETs. Real life MANETs are noisy and the communication is not error free. This research argues that a broadcast scheme that considers the effects of thermal noise, co-channel interference, and node density in the neighbourhood simultaneously can reduce the broadcast storm problem and enhance the MANET performance. To achieve this, three investigations have been carried out: First, the effect of carrier sensing ranges on on-demand routing protocol such as AODV and their impact on interference; second, effects of thermal noise on on-demand routing protocols and third, evaluation of pure flooding and probabilistic broadcasting schemes under noisy and noiseless conditions. The findings of these investigations are exploited to propose a Channel Adaptive Probabilistic Broadcast (CAPB) scheme to disseminate RREQ packets efficiently. The proposed CAPB scheme determines the probability of rebroadcasting RREQ packets on the fly according to the current Signal to Interference plus Noise Ratio (SINR) and node density in the neighbourhood. The proposed scheme and two related state of the art (SoA) schemes from the literature are implemented in the standard AODV to replace the pure flooding based broadcast scheme. Ns-2 simulation results show that the proposed CAPB scheme outperforms the other schemes in terms of routing overhead, average end-to-end delay, throughput and energy consumption

XLP: A Cross-Layer Protocol for Efficient Communication in Wireless Sensor Networks

Severe energy constraints of battery-powered sensor nodes necessitate energy-efficient communication in Wireless Sensor Networks (WSNs). However, the vast majority of the existing solutions is based on classical layered protocols approach, which leads to significant overhead. It is much more efficient to have a unified scheme which blends common protocol layer functionalities into a cross-layer module. In this paper, a cross layer protocol (XLP) is introduced, which achieves congestion control, routing, and medium access control in a cross-layer fashion. The design principle of XLP is based on the cross-layer concept of initiative determination, which enables receiver-based contention, initiative-based forwarding, local congestion control, and distributed duty cycle operation to realize efficient and reliable communication in WSNs. The initiative determination requires simple comparisons against thresholds, and thus is very simple to implement, even on computationally impaired devices. To the best of our knowledge, XLP is the first protocol that integrates functionalities of all layers from PHY to transport into a cross-layer protocol. A cross-layer analytical framework is developed to investigate the performance of the XLP. Moreover, in a cross-layer simulation platform, the state-of-the- art layered and cross-layer protocols have been implemented along with XLP for performance evaluations. XLP significantly improves the communication performance and outperforms the traditional layered protocol architectures in terms of both network performance and implementation complexity