Middleware platform for distributed applications incorporating robots, sensors and the cloud

Cyber-physical systems in the factory of the future will consist of cloud-hosted software governing an agile production process executed by autonomous mobile robots and controlled by analyzing the data from a vast number of sensors. CPSs thus operate on a distributed production floor infrastructure and the set-up continuously changes with each new manufacturing task. In this paper, we present our OSGibased middleware that abstracts the deployment of servicebased CPS software components on the underlying distributed platform comprising robots, actuators, sensors and the cloud. Moreover, our middleware provides specific support to develop components based on artificial neural networks, a technique that recently became very popular for sensor data analytics and robot actuation. We demonstrate a system where a robot takes actions based on the input from sensors in its vicinity

Extending Eventually Consistent Cloud Databases for Enforcing Numeric Invariants

Geo-replicated databases often operate under the principle of eventual consistency to offer high-availability with low latency on a simple key/value store abstraction. Recently, some have adopted commutative data types to provide seamless reconciliation for special purpose data types, such as counters. Despite this, the inability to enforce numeric invariants across all replicas still remains a key shortcoming of relying on the limited guarantees of eventual consistency storage. We present a new replicated data type, called bounded counter, which adds support for numeric invariants to eventually consistent geo-replicated databases. We describe how this can be implemented on top of existing cloud stores without modifying them, using Riak as an example. Our approach adapts ideas from escrow transactions to devise a solution that is decentralized, fault-tolerant and fast. Our evaluation shows much lower latency and better scalability than the traditional approach of using strong consistency to enforce numeric invariants, thus alleviating the tension between consistency and availability

Building Regular Registers with Rational Malicious Servers and Anonymous Clients

The paper addresses the problem of emulating a regular register in a synchronous distributed system where clients invoking $$\mathsf{read}()$$ and $$\mathsf{write}()$$ operations are anonymous while server processes maintaining the state of the register may be compromised by rational adversaries (i.e., a server might behave as rational malicious Byzantine process). We first model our problem as a Bayesian game between a client and a rational malicious server where the equilibrium depends on the decisions of the malicious server (behave correctly and not be detected by clients vs returning a wrong register value to clients with the risk of being detected and then excluded by the computation). We prove such equilibrium exists and finally we design a protocol implementing the regular register that forces the rational malicious server to behave correctly

File Tracking For Mobile Devices

Since 2010, the smart device has become an integral part of people’s daily lives. The popularity of smart devices has increased dramatically. However, as the number of devices owned by an individual user increases, so does the risk of data leakage and loss. This problem has started to draw attention because the data contained on smart devices tends to be personal or sensitive in nature. Many people have so much data on their devices that they have no idea as to what they are missing when a device is lost. Although there are already some solutions for data recovery, a data backup system on a remote server, these solutions are not accessible in the non-Internet environment. Development of a data recovery system that is accessible in the non-Internet environment is essential because of the constraints of mobile devices, such as unreliable network. This research proposes an architecture that allows the data recovery in both Internet (cloud) and Non-Internet (local) network by using different connection technologies. A data tracking mechanism has also been designed to monitor data flow among multiple devices, such as the cloud server, mobile devices, and tablets. Additionally, a synchronization system has been developed to ensure the consistency of tracking information. By designing and implementing this architecture, the two problems regarding to the data: "what is where" and "who has what" are resolved