Distributed redundancy and robustness in complex systems

Abstract

The uptake and increasing prevalence of Web 2.0 applications, promoting new largescale and complex systems such as Cloud computing and the emerging Internet of Services/Things, requires tools and techniques to analyse and model methods to ensure the robustness of these new systems. This paper reports on assessing and improving complex system resilience using distributed redundancy, termed degeneracy in biological systems, to endow large-scale complicated computer systems with the same robustness that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an 'open-ended' manner where not all states of the system are prescribed at designtime. In particular an observer system is used to select robust topologies, within system components, based on a measurement of the first non-zero Eigen value in the Laplacian spectrum of the components' network graphs; also known as the algebraic connectivity. It is shown, through experimentation on a simulation, that increasing the average algebraic connectivity across the components, in a network, leads to an increase in the variety of individual components termed distributed redundancy; the capacity for structurally distinct components to perform an identical function in a particular context. The results are applied to a specific application where active clustering of like services is used to aid load balancing in a highly distributed network. Using the described procedure is shown to improve performance and distribute redundancy.

Optimal network topology for structural robustness based on natural connectivity

“…The R-optimized network has an ''onion-like'' topology consisting of a core of highly connected nodes 19 that are hierarchically surrounded by rings of nodes with decreasing degree [11]. 20 In reality, most networks are large-scale and complex, which indicates that the optimization has a request for the com-21 putational complexity of robustness measure. The measure R, however, does not pay enough attention to its computational 22 complexity or to f c .…”

“…Thus, a more ap- 26 propriate measure which can be computed fast and measure structural robustness accurately is of great importance for the 27 optimization. 28 Natural connectivity λ, a new measure of robustness in complex networks based on graph spectra, has been proposed and 29 received growing attention [14][15][16][17][18][19][20]. It is derived from the graph spectrum as an average eigenvalue, and can be interpreted as 30 the Helmholtz free energy of a network [21].…”

“…3). Finally, considering the 19 economic factors that limit the number of times for rewiring links in practical applications, we have improved the algorithm 20 presented in our research to reduce the required amount of rewiring by employing the assortative rewiring strategy. 21 Our results show that the optimal network has the maximum redundancy of alternative routes between each pair of 22 nodes, which is regarded as the maximum structural robustness of the network.…”

Virtual Machine Scheduling to Minimize Resource Wastage in Cloud Computing Environment

“…The adoption and deployment of cloud computing platforms have many attractive benefits, such as reliability, quality of service and robustness [2].There are some key technologies that make cloud computing possible. One of the most important is virtualization which has made the task no longer assigned to a physical machine, but made the user's requests to be mapped to a virtual machine, while the virtual machine can be mapped to different physical machines.…”

Raising Risk Awareness on the Adoption of Web 2.0 Technologies in Decision Making Processes

“…Other components could suddenly find it impossible to correctly communicate with the "updated" one, with effects ranging from visible crashes to subtle alterations of the displayed results. Literature exists [11,12] that addresses the issue of reliability, or robustness, of the kind of distributed systems powering Web 2.0 applications. The proposed solutions appear to be still at the academic level rather than widely deployed.…”