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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/userguides/explore-bristol-research/ebr-terms/ 1932-4537 (c)Abstract-Datacenter (DC) design has been moved towards the edge computing paradigm motivated by the need of bringing cloud resources closer to end users. However, the Software Defined Networking (SDN) architecture offers no clue to the design of Micro Datacenters (MDC) for meeting complex and stringent requirements from next generation 5G networks. This is because canonical SDN lacks a clear distinction between functional network parts, such as core and edge elements. Besides, there is no decoupling between the routing and the network policy. In this paper, we introduce Residue Defined Networking Architecture (RDNA) as a new approach for enabling key features like ultra-reliable and low-latency communication in MDC networks. RDNA explores the programmability of Residues Number System (RNS) as a fundamental concept to define a minimalist forwarding model for core nodes. Instead of forwarding packets based on classical table lookup operations, core nodes are tableless switches that forward packets using merely remainder of the division (modulo) operations. By solving a residue congruence system representing a network topology, we found out the algorithms and their mathematical properties to design RDNA's routing system that (i) supports unicast and multicast communication, (ii) provides resilient routes with protection for the entire route, and (iii) is scalable for 2-tier Clos topologies. Experimental implementations on Mininet and NetFPGA SUME show that RDNA achieves 600 ns switching latency per hop with virtually no jitter at core nodes and submillisecond failure recovery time.

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A hierarchical modeling framework for the dependability evaluation of Internet-based applications is presented and illustrated on a travel agency example. Modeling is carried out considering four levels, namely: user, function, service and resource levels. The first level describes how the users invoke the application and the three remaining levels detail how the user requests are handled by the application a t distinct abstraction layers. The user perceived availability measure considered in this paper takes into account the combined impact of performance-related failures and traditional software and hardware failures. For illustration purposes, several sensitivity analysis results are presented to show the impact on this measure of various assumptions concerning, e.g. the users operational profile, the travel agency architecture and the fault coverage.

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