Intelligent Communication Planning for Constrained Environmental IoT Sensing with Reinforcement Learning

Internet of Things (IoT) technologies have enabled numerous data-driven mobile applications and have the potential to significantly improve environmental monitoring and hazard warnings through the deployment of a network of IoT sensors. However, these IoT devices are often power-constrained and utilize wireless communication schemes with limited bandwidth. Such power constraints limit the amount of information each device can share across the network, while bandwidth limitations hinder sensors' coordination of their transmissions. In this work, we formulate the communication planning problem of IoT sensors that track the state of the environment. We seek to optimize sensors' decisions in collecting environmental data under stringent resource constraints. We propose a multi-agent reinforcement learning (MARL) method to find the optimal communication policies for each sensor that maximize the tracking accuracy subject to the power and bandwidth limitations. MARL learns and exploits the spatial-temporal correlation of the environmental data at each sensor's location to reduce the redundant reports from the sensors. Experiments on wildfire spread with LoRA wireless network simulators show that our MARL method can learn to balance the need to collect enough data to predict wildfire spread with unknown bandwidth limitations.Comment: To be published in the 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON 2023

Mobile Computing: Challenges and Opportunities for Autonomy and Feedback

Mobile devices have evolved to become computing platforms more similar to desktops and workstations than the cell phones and handsets of yesteryear. Unfortunately, today’s mobile infrastructures are mirrors of the wired past. Devices, apps, and networks impact one another, but a systematic approach for allowing them to cooperate is currently missing. We propose an approach that seeks to open key interfaces and to apply feedback and autonomic computing to improve both user experience and mobile system dynamics

A Survivable Social Network

<p>The impact that widespread disasters have on communications systems has evolved over time – fueled by advancements in technology and cemented by societal adoption. As the use of IP-based communications systems, both wired and wireless, has become ubiquitous, we as a society have become dangerously dependent. We vest our banking and healthcare records in cloudbased services, and we have systematically shifted our preferred ways of staying in touch with friends and family away from voice communications toward online social networks. Outages of these systems that occur as a consequence of man-made or natural disasters leave us in communications darkness and without the local means to reconstruct our communications tools. In this paper, we propose a Survivable Social Network (SSN) that seeks to put the means of rebuilding familiar-feeling, modern communications tools into the hands of members of neighborhoods, schools, organizations and communities and demonstrate how such a system can be architected and replicated.</p

CROSSMobile: A Cross-Layer Architecture for Next-Generation Wireless Systems

<p>Commercial cellular networks emerged from the wired public switched telephone networks (PSTN) in an evolutionary manner. Market pressures fueled upgrades in bandwidth and functionality. Four decades later, these networks maintain historical artifacts from PSTN networks, and the artifacts work against the fundamental needs of today’s wireless systems. Noncellular wireless networks are used beneficially within geographically limited domains (enterprise, at home), but such networks lack the architecture to scale geographically.</p> <p>In this paper, we step back and re-evaluate existing wireless network architectures, identifying inherent limitations and offering a new set of architectural principles that, we contend, will lead to significantly improved overall system performance and scalability. Based on these principles, we propose the CROSSMobile^SM architecture that is enabled by controlled cross-layer information exchange between radio, network, and application layers (both on-device and in-cloud), coupled with information-owner-based privacy and security controls. We discuss how this architecture can provide increased value to equipment and device manufacturers, application and network service providers, and end users. We close by outlining a number of open research questions.</p> <p>CROSSMobile is a service mark of Carnegie Mellon University</p