Combining Blockchain and Swarm Robotics to Deploy Surveillance Missions

Current swarm robotics systems are not utilized as frequently in surveillance missions due to the limitations of the existing distributed systems\u27 designs. The main limitation of swarm robotics is the absence of a framework for robots to be self-governing, secure, and scalable. As of today, a swarm of robots is not able to communicate and perform tasks in transparent and autonomous ways. Many believe blockchain is the imminent future of distributed autonomous systems. A blockchain is a system of computers that stores and distributes data among all participants. Every single participant is a validator and protector of the data in the blockchain system. The data cannot be modified since all participants are storing and watching the same records. In this thesis, we will focus on blockchain applications in swarm robotics using Ethereum smart contracts because blockchain can make a swarm globally connected and secure. A decentralized application (DApp) is used to deploy surveillance missions. After mission deployment, the swarm uses blockchain to communicate and make decisions on appropriate tasks within Ethereum private networks. We set a test swarm robotics system and evaluate the blockchain for its performance, scalability, recoverability, and responsiveness. We conclude that, although blockchain enables a swarm to be globally connected and secure, there are performance limitations that can become a critical issue

Design and evaluation of a genomics variant analysis pipeline using GATK Spark tools

Scalable and efficient processing of genome sequence data, i.e. for variant discovery, is key to the mainstream adoption of High Throughput technology for disease prevention and for clinical use. Achieving scalability, however, requires a significant effort to enable the parallel execution of the analysis tools that make up the pipelines. This is facilitated by the new Spark versions of the well-known GATK toolkit, which offer a black-box approach by transparently exploiting the underlying Map Reduce architecture. In this paper we report on our experience implementing a standard variant discovery pipeline using GATK 4.0 with Docker-based deployment over a cluster. We provide a preliminary performance analysis, comparing the processing times and cost to those of the new Microsoft Genomics Services

Mixed Initiative Systems for Human-Swarm Interaction: Opportunities and Challenges

Human-swarm interaction (HSI) involves a number of human factors impacting human behaviour throughout the interaction. As the technologies used within HSI advance, it is more tempting to increase the level of swarm autonomy within the interaction to reduce the workload on humans. Yet, the prospective negative effects of high levels of autonomy on human situational awareness can hinder this process. Flexible autonomy aims at trading-off these effects by changing the level of autonomy within the interaction when required; with mixed-initiatives combining human preferences and automation's recommendations to select an appropriate level of autonomy at a certain point of time. However, the effective implementation of mixed-initiative systems raises fundamental questions on how to combine human preferences and automation recommendations, how to realise the selected level of autonomy, and what the future impacts on the cognitive states of a human are. We explore open challenges that hamper the process of developing effective flexible autonomy. We then highlight the potential benefits of using system modelling techniques in HSI by illustrating how they provide HSI designers with an opportunity to evaluate different strategies for assessing the state of the mission and for adapting the level of autonomy within the interaction to maximise mission success metrics.Comment: Author version, accepted at the 2018 IEEE Annual Systems Modelling Conference, Canberra, Australi

Through a router darkly: how new American copyright enforcement initiatives may hinder economic development, net neutrality and creativity

On November 1, 2012, Russia enacted a law putatively aiming to protect Russian children from pedophiles. This law authorizes deep packet inspection (DPI), a method used for monitoring, filtering and shaping internet traffic, which has heightened concerns among many leading privacy groups. These groups are concerned with how the government will use such an intrusive method in prosecuting child predators. Central to this concern is DPI’s capability to allow the Russian government to peer into any citizens’ unencrypted internet traffic and monitor, copy, or even alter the traffic as it moves to its destination. The unresolved question is whether the government’s use of DPI will be restrained and utilized primarily to thwart child predators, or whether it will be expanded to lay the groundwork for a new era of national censorship. Although the United States has not yet adopted similar tactics in regulating its citizens’ internet use, Russia’s implementation of the new DPI monitoring and filtering system will provide an educational opportunity for both privacy advocates and policymakers

The water clock of Proteus mirabilis paces colony periodic and synchronous swarming

For decades, the origin of the concentric ring pattern of bacterial swarming colonies has puzzled microbiologists. Thanks to _in situ_ and real time infrared microspectroscopy and the brilliance of the infrared beam at SOLEIL synchrotron, we demonstrate here that _Proteus mirabilis_ swarming is paced by a periodic variation of the water activity at colony's edge. This periodic variation originates a phase transition within the extracellular matrix water H bond network which switches on and off the exopolysaccharides viscoelasticity and, consequently, the ability of bacterial cells to swarm. A dynamic behaviour emerges from the global properties of the multicellular entity which here relies on the ability of the bacterial cells to tune exoproducts synthesis in order to undergo sharp transitions above/below a given water activity threshold

IDMoB: IoT Data Marketplace on Blockchain

Today, Internet of Things (IoT) devices are the powerhouse of data generation with their ever-increasing numbers and widespread penetration. Similarly, artificial intelligence (AI) and machine learning (ML) solutions are getting integrated to all kinds of services, making products significantly more "smarter". The centerpiece of these technologies is "data". IoT device vendors should be able keep up with the increased throughput and come up with new business models. On the other hand, AI/ML solutions will produce better results if training data is diverse and plentiful. In this paper, we propose a blockchain-based, decentralized and trustless data marketplace where IoT device vendors and AI/ML solution providers may interact and collaborate. By facilitating a transparent data exchange platform, access to consented data will be democratized and the variety of services targeting end-users will increase. Proposed data marketplace is implemented as a smart contract on Ethereum blockchain and Swarm is used as the distributed storage platform.Comment: Presented at Crypto Valley Conference on Blockchain Technology (CVCBT 2018), 20-22 June 2018 - published version may diffe