Constraint programming for flexible Service Function Chaining deployment

2019 | HICSS | Citations: 0

Authors: Liu, Tong; Callegati, Franco; Cerroni, Walter; Contoli, Chiara; Gabbrielli, Maurizio; Giallorenzo, Saverio

Abstract: Network Function Virtualization (NFV) and Software Defined Networking (SDN) are t ... Expand

Abstract: Network Function Virtualization (NFV) and Software Defined Networking (SDN) are technologies that recently acquired a great momentum thanks to their promise of being a flexible and cost-effective solution for replacing hardware-based, vendor-dependent network middleboxes with software appliances running on general purpose hardware in the cloud. Delivering end-to-end networking services across multiple NFV/SDN network domains by implementing the so-called Service Function Chain (SFC) i.e., a sequence of Virtual Network Functions (VNF) that composes the service, is a challenging task. Collapse

Topics: Google+ user satisfaction artificial intelligence programming language lean manufacturing

Methods: experiment constraint programming modeling language minimum spanning tree problem mixed-integer programming

A Submodular Approach for Electricity Distribution Network Reconfiguration

2018 | HICSS | Citations: 0

Authors: Khodabakhsh, Ali; Yang, Ger; Basu, Soumya; Nikolova, Evdokia; Caramanis, Michael C; Lianeas, Thanasis; Pountourakis, Emmanouil

Abstract: Distribution network reconfiguration (DNR) is a tool used by operators to balance ... Expand

Abstract: Distribution network reconfiguration (DNR) is a tool used by operators to balance line load flows and mitigate losses. As distributed generation and flexible load adoption increases, the impact of DNR on the security, efficiency, and reliability of the grid will increase as well. Today, heuristic-based actions like branch exchange are routinely taken, with no theoretical guarantee of their optimality. This paper considers loss minimization via DNR, which changes the on/off status of switches in the network. The goal is to ensure a radial final configuration (called a spanning tree in the algorithms literature) that spans all network buses and connects them to the substation (called the root of the tree) through a single path. We prove that the associated combinatorial optimization problem is strongly NP-hard and thus likely cannot be solved efficiently. We formulate the loss minimization problem as a supermodular function minimization under a single matroid basis constraint, and use existing algorithms to propose a polynomial time local search algorithm for the DNR problem at hand and derive performance bounds. We show that our algorithm is equivalent to the extensively used branch exchange algorithm, for which, to the best of our knowledge, we pioneer in proposing a theoretical performance bound. Finally, we use a 33-bus network to compare our algorithm’s performance to several algorithms published in the literature. Collapse

Methods: computational algorithm optimization model simulation experiment minimum spanning tree problem