A Protocol for the Atomic Capture of Multiple Molecules at Large Scale

With the rise of service-oriented computing, applications are more and more based on coordination of autonomous services. Envisioned over largely distributed and highly dynamic platforms, expressing this coordination calls for alternative programming models. The chemical programming paradigm, which models applications as chemical solutions where molecules representing digital entities involved in the computation, react together to produce a result, has been recently shown to provide the needed abstractions for autonomic coordination of services. However, the execution of such programs over large scale platforms raises several problems hindering this paradigm to be actually leveraged. Among them, the atomic capture of molecules participating in concur- rent reactions is one of the most significant. In this paper, we propose a protocol for the atomic capture of these molecules distributed and evolving over a large scale platform. As the density of possible reactions is crucial for the liveness and efficiency of such a capture, the protocol proposed is made up of two sub-protocols, each of them aimed at addressing different levels of densities of potential reactions in the solution. While the decision to choose one or the other is local to each node participating in a program's execution, a global coherent behaviour is obtained. Proof of liveness, as well as intensive simulation results showing the efficiency and limited overhead of the protocol are given.Comment: 13th International Conference on Distributed Computing and Networking (2012

Big Data Model Simulation on a Graph Database for Surveillance in Wireless Multimedia Sensor Networks

Sensors are present in various forms all around the world such as mobile phones, surveillance cameras, smart televisions, intelligent refrigerators and blood pressure monitors. Usually, most of the sensors are a part of some other system with similar sensors that compose a network. One of such networks is composed of millions of sensors connect to the Internet which is called Internet of things (IoT). With the advances in wireless communication technologies, multimedia sensors and their networks are expected to be major components in IoT. Many studies have already been done on wireless multimedia sensor networks in diverse domains like fire detection, city surveillance, early warning systems, etc. All those applications position sensor nodes and collect their data for a long time period with real-time data flow, which is considered as big data. Big data may be structured or unstructured and needs to be stored for further processing and analyzing. Analyzing multimedia big data is a challenging task requiring a high-level modeling to efficiently extract valuable information/knowledge from data. In this study, we propose a big database model based on graph database model for handling data generated by wireless multimedia sensor networks. We introduce a simulator to generate synthetic data and store and query big data using graph model as a big database. For this purpose, we evaluate the well-known graph-based NoSQL databases, Neo4j and OrientDB, and a relational database, MySQL.We have run a number of query experiments on our implemented simulator to show that which database system(s) for surveillance in wireless multimedia sensor networks is efficient and scalable