Optimizing rule placement in software-defined networks for energy-aware routing

Abstract

Abstract:Software-defined Networks (SDN), in particular OpenFlow, is a new networking paradigm enabling innovation through network programmability. Over past few years, many applications have been built using SDN such as server load balancing, virtual-machine migration, traffic engineering and access control. In this paper, we focus on using SDN as an approach for energy-aware routing (EAR). Since traffic load has a small influence on power consumption of routers, EAR allows to put unused links into sleep mode to save energy. SDN can collect traffic matrix and then computes routing solutions satisfying QoS while being minimal in energy consumption. However, prior works on EAR have assumed that the table of OpenFlow switch can hold an infinite number of rules. In practice, this assumption does not hold since the flow table is implemented in Ternary Content Addressable Memory (TCAM) which is expensive and powerhungry. In this paper, we propose an optimization method to minimize energy consumption for a backbone network while respecting capacity constraints on links and rule space constraints on routers. In details, we present an exact formulation using Integer Linear Program (ILP) and introduce efficient greedy heuristic algorithm for large networks. Based on simulations, we show that using this smart rule space allocation, it is possible to save almost as much power consumption as in the classical EAR approach.

Evaluating the Impact of Energy-Aware Routing on Software-Defined Networking Performance

“…As expected, the number of installed rules is raised by the energy-aware routing in almost all the network devices (18 out of 22 nodes), being in some cases more than twice the value obtained by the TOB algorithm. However, the DESRA performance in this topology is still physically acceptable considering that a routing table can support from 750 to few thousands of rules [10].…”

“…They formulated an optimization problem for finding minimum power network subsets in these hybrid networks. Giroire et al [10] proposed an energy-aware routing approach that takes into account the limited rule space of TCAM in SDN devices. An ILP model is presented as well as an efficient heuristic.…”

Bringing Energy Aware Routing Closer to Reality with SDN Hybrid Networks

“…For instance, in [8], the authors propose algorithms to minimize the energy consumption of routing by shutting down links while taking into account constraints of SDN hardware such as the size of TCAM memory. Authors in [9] implemented and analyzed ElasticTree, an energy aware routing solution for data center networks.…”

Energy aware routing and traffic management for software defined networks

“…In [11], an integrated control scheme which combines smart sleeping and power scaling algorithms has been given by testing in data center with Fat-Tree topology under low and high traffic cases. In [12], an optimization method for rule placement considering link capacities and space constraints on routers has been suggested to reduce energy consumption for a backbone network. In [13], an energy efficient routing scheme with traffic aggregation for each flow to decrease the number of active network devices while maintaining acceptable performance has been presented.…”