Ongoing work funded by Public Safety Communications Research


The proposal uses commodity networks, including WiFi, Bluetooth, commercially available UHF radios and LTE networks to evaluate a proposed software environment respons, the Reliable Environment for Secure Police Operations and Networks. This portion of the proposed work seeks to develop a usable fog computing application environment for use in dispersed or situational computing for police systems. The respons system uses a combination of distributed consensus systems, distributed transactional memory and object systems, multi-path routing and container-based application isolation. Many of the technologies needed for resilient systems are commonly used in existing datacenter scale systems, but those systems require adaptation for the relatively poor network connectivity and disconnected operation that would occur in field systems. Reusing the existing software and design patterns simplifies the training needed to develop applications using the software framework. This system will use the plurality of networks which can be partitioned and perturbed to emulate network partitions and failures, and consumer-grade long-range but low-bandwidth networks used to emulate functions of the emerging device-to-device networking standard.

This proposal is funded by NIST Public Safety Communications Research.

Mobile Edge Computing over Elastic EPC cluster

Mobile Edge Computing (MEC) is an essential part of the 5G plan to support the numerous IoT devices that are projected to be in use over the coming decades. These IoT devices will have very limited computing power and will rely on services provided from the network to process and respond to the physical input they are receiving. We believe that there is utility in taking inspiration from MEC in 5G and applying it to public safety communications. Latency to edge services and resiliency to loss of network connection is the major contribution of this work.

Offline Map Sharing

Our goal is to develop a framework that simplifies the production of complex mobile applications. We develop a distributed spatial computing application that focuses on messaging, image dissemination and map retrieval, which is inspired by Serval project. We implement optimized distributed spatial data organized that can be used to rapidly identify shared and geo-spatially distributed representations of common map information.