CoCONet: A collision-free container-based core optical network

  • Authors:
  • Amin R. Mazloom;Preetam Ghosh;Kalyan Basu;Sajal K. Das

  • Affiliations:
  • CReWMaN, The University of Texas at Arlington, Arlington, TX 76019-23015, USA;CReWMaN, The University of Texas at Arlington, Arlington, TX 76019-23015, USA;CReWMaN, The University of Texas at Arlington, Arlington, TX 76019-23015, USA;CReWMaN, The University of Texas at Arlington, Arlington, TX 76019-23015, USA

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2008

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Abstract

Electrical-to-optical domain conversions and vice versa (denoted by O/E/O conversions) for each hop in optical core transport networks impose considerable capital and financial overhead on the providers. In this paper, we propose a full-mesh topology driven core network with a central scheduler that handles the task of signaling and coordination among slot transmissions for every hop to eliminate such O/E/O conversions. We introduce the concept of a container as a macro data unit that forms a separate layer in the protocol stack above the optical layer. A FAST centralized scheduling algorithm is proposed based on a preemptive scheduling technique that can ensure that there are no collisions between the containers. We also analyze the complexity of this algorithm. Next we design the logical architecture for the core and edge switches following the de facto policy of moving the complexity to the edge. We also designed a hierarchical architecture for the edge switch and provide the respective block diagrams. To get a more concrete design prototype, we further proposed a generic (vendor independent) physical architecture for a single port of the switch considering SONET/SDH on the access side. Moreover, we develop a concise delay model for the containers to analyze the packet arrival process and derive the optimal container size, based on the link speed. Finally, we present some simulation results to study the performance of the algorithms and models proposed in our work.