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Krishnaiyan Thulasiraman

Publications and source records attributed to Krishnaiyan Thulasiraman.

2 recordsLinked to original sources

Survivable Cloud Network Design Against Multiple Failures Through Protecting Spanning Trees

Survivable design of cross-layer networks, such as the cloud computing infrastructure, lies in its resource deployment and allocation and mapping of the logical (virtual datacenter/IP) network into the physical infrastructure (cloud backbone/WDM) such that link or node failure(s) in the physical infrastructure would not result in cascading failures in the logical network. Most of the prior approaches for survivable cross-layer network design aim at single-link failure scenario, which are not applicable to the more challenging multi-failure scenarios. Also, as many of these approaches use the cross-layer cut concept, enumeration of all cuts in the network is required and thus introducing exponential number of constraints. To overcome these difficulties, we investigate in this paper survivable mapping approaches against multiple physical link failures and its special case, Shared Risk Link Group (SRLG) failure. We present the necessary and sufficient conditions based on both cross-layer spanning trees and cutsets to guarantee a survivable mapping when multiple physical link failures occur. Based on the necessary and sufficient conditions, we propose to solve the problem through (1) mixed-integer linear programs which avoid enumerating all combinations of link failures, and (2) an algorithm which generates/adds logical spanning trees sequentially. Our simulation results show that the proposed approaches can produce survivable mappings effectively against both $k$- and SRLG-failures.

cs.NI

Topology Abstraction Service for IP VPNs: Core Network Partitioning for Resource Sharing

VPN service providers (VSP) and IP-VPN customers have traditionally maintained service demarcation boundaries between their routing and signaling entities. This has resulted in the VPNs viewing the VSP network as an opaque entity and therefore limiting any meaningful interaction between the VSP and the VPNs. A key challenge is to expose each VPN to information about available network resources through an abstraction (TA) [1] which is both accurate and fair. In [2] we proposed three decentralized schemes assuming that all the border nodes performing the abstraction have access to the entire core network topology. This assumption likely leads to over- or under-subscription. In this paper we develop centralized schemes to partition the core network capacities, and assign each partition to a specific VPN for applying the decentralized abstraction schemes presented in [2]. First, we present two schemes based on the maximum concurrent flow and the maximum multicommodity flow (MMCF) formulations. We then propose approaches to address the fairness concerns that arise when MMCF formulation is used. We present results based on extensive simulations on several topologies, and provide a comparative evaluation of the different schemes in terms of abstraction efficiency, fairness to VPNs and call performance characteristics achieved.

cs.NI