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System Engineering, Multi Actor Systems

System Engineering, Multi Actor Systems

A major research challenge in distributed systems is the design of services that incorporate robustness to events such as network changes and node faults. In this paper we describe an approach ï½ which we refer to as EmbryoWare ï½ that is inspired by cellular development and differentiation processes. The approach uses ï½artificial stem cellsï½ in the form of totipotent nodes that differentiate into the different types needed to obtain the desired systemï½level behaviour. Each node has a genome that contains the full service specification, as well as rules for the differentiation process. We describe the system architecture and present simulation results that assess the overall performance and fault tolerance properties of the system in a decentralized network monitoring scenario.

In previous work the authors have described an approach for building distributed self-healing systems - referred to as EmbryoWare - that, in analogy to Embryonics in hardware, is inspired by cellular development and differentiation processes. The approach uses "artificial stem cells" that autonomously differentiate into the node types needed to obtain the desired system-level behaviour. Each node has a genome that contains the full service specification, as well as rules for the differentiation process. This approach has inherent self-healing behaviours that naturally give rise to fault tolerance. Previous evaluations of this fault tolerance have however focused on individual node failures. A more systemic fault modality arises when the nodes become mobile, leading to regular changes in the network topology and hence the potential introduction of local node type faults. In this paper we evaluate the extent to which the existing fault tolerance copes with the class of faults arising from node mobility and associated network topology changes. We present simulation results that demonstrate a significant relationship between network stability, node speed, and node sensing rates. © 2010 Springer-Verlag Berlin Heidelberg.

In previous work the authors have described an approach for building distributed self-healing systems - referred to as EmbryoWare - that, in analogy to Embryonics in hardware, is inspired by cellular development and differentiation processes. The approach uses "artificial stem cells" that autonomously differentiate into the node types needed to obtain the desired system-level behaviour. Each node has a genome that contains the full service specification, as well as rules for the differentiation process. This approach has inherent self-healing behaviours that naturally give rise to fault tolerance. Previous evaluations of this fault tolerance have however focused on individual node failures. A more systemic fault modality arises when the nodes become mobile, leading to regular changes in the network topology and hence the potential introduction of local node type faults. In this paper we evaluate the extent to which the existing fault tolerance copes with the class of faults arising from node mobility and associated network topology changes. We present simulation results that demonstrate a significant relationship between network stability, node speed, and node sensing rates. © 2010 Springer-Verlag Berlin Heidelberg.

A major research challenge in distributed systems is the design of services that incorporate robustness to events such as network changes and node faults. In this paper we describe an approach ï½ which we refer to as EmbryoWare ï½ that is inspired by cellular development and differentiation processes. The approach uses ï½artificial stem cellsï½ in the form of totipotent nodes that differentiate into the different types needed to obtain the desired systemï½level behaviour. Each node has a genome that contains the full service specification, as well as rules for the differentiation process. We describe the system architecture and present simulation results that assess the overall performance and fault tolerance properties of the system in a decentralized network monitoring scenario.

In this work we report on a method, based on the use of activation-inhibition mechanisms, for building and maintaining high-rate routing paths (data highways) in dense wireless sensor networks. We describe the algorithms devised and report on the outcomes of a simulation study, aimed at assessing the scalability and the performance of the proposed approach.

In this work we report on a method, based on the use of activation-inhibition mechanisms, for building and maintaining high-rate routing paths (data highways) in dense wireless sensor networks. We describe the algorithms devised and report on the outcomes of a simulation study, aimed at assessing the scalability and the performance of the proposed approach.

Previous work has demonstrated the feasibility of distributed generation of data highways through a grid-based wireless sensor network. These highways carry packets across the network from source(s) to sink(s), and can be generated through a localised reaction diffusion process that does not require apriori knowledge of the global network topology. In this paper we consider the extension of this approach to a more realistic graph-based structure. We present the underlying algorithms, simulation results, and an analysis of the extent to which the algorithms can be fully distributed.

Previous work has demonstrated the feasibility of distributed generation of data highways through a grid-based wireless sensor network. These highways carry packets across the network from source(s) to sink(s), and can be generated through a localised reaction diffusion process that does not require apriori knowledge of the global network topology. In this paper we consider the extension of this approach to a more realistic graph-based structure. We present the underlying algorithms, simulation results, and an analysis of the extent to which the algorithms can be fully distributed.