Macro-Star Networks: Efficient Low-Degree Alternatives to Star Graphs for Large-Scale Parallel Architectures

We propose a new class of interconnection networks called macro-star networks, which belong to the class of Cayley graphs and use the star graph as a basic building module. A macro-star network can have node degree that is considerably smaller than that of a star graph of the same size, and diameter that is asymptotically within a factor of 1.25 from a universal lower bound (given its node degree) . We show that algorithms developed for star graphs can be emulated on suitably constructed macro-stars with asymptotically optimal slowdown. In particular, we obtain asymptotically optimal algorithms to execute the multinode broadcast and total exchange communication tasks in a macro-star network, under both the single-port and the all-port communication models. 1 Introduction A large variety of topologies have been proposed and analyzed in the literature [1, 11, 12, 14, 15, 17, 18, 19, 20, 23, 26, 30, 31] for the interconnection of processors in parallel computer systems. Among them, the ..

Resource partitioning in the NEPHELE datacentre interconnect

We present heuristic algorithms for the efficient resource partitioning in the NEPHELE datacentre optical interconnect. The algorithms aim to segment the network into smaller and isolated virtual datacentres (VDCs), where all racks are able to communicate at full capacity irrespective of their placement. Since the NEPHELE architecture relies on shared optical rings, the isolation of VDC traffic is challenging. Observing its close resemblance to finding a bi-clique on a bipartite graph, which is NP-hard, we propose heuristic algorithms which find a solution by limiting either the spatial spread of racks that construct each VDC or their wavelength allocation. If a solution cannot be found, then the algorithms invoke a second de-fragmentation phase, where they re-allocate the racks of existing VDCs to concentrate them spatially and reduce traffic on the shared optical rings. It is demonstrated via simulation that the proposed heuristics can achieve very high utilization and also exhibit low VDC request blocking probability for typically expected VDC sizes

Network and Market-Aware Bidding to Maximize Local RES Usage and Minimize Cost in Energy Islands with Weak Grid Connections

The increasing renewable energy sources RES penetration in today’s energy islands and rural energy communities with weak grid connections is expected to incur severe distribution network stability problems (i.e., congestion, voltage issues). Tackling these problems is even more challenging since RES spillage minimization and energy cost minimization for the local energy community are set as major pre-requisites. In this paper, we consider a Microgrid Operator (MGO) that: (i) gradually decides the optimal mix of its RES and flexibility assets’ (FlexAsset) sizing, siting and operation, (ii) respects the physical distribution network constraints in high RES penetration contexts, and (iii) is able to bid strategically in the existing day-ahead energy market. We model this problem as a Stackelberg game, expressed as a Mathematical Problem with Equilibrium Constraints (MPEC), which is finally transformed into a tractable Mixed Integer Linear Program (MILP). The performance evaluation results show that the MGO can lower its costs when bidding strategically, while the coordinated planning and scheduling of its FlexAssets result in higher RES utilization, as well as distribution network aware and cost-effective RES and FlexAsset operation