Results 1 -
3 of
3
Hallucination Helps: Energy Efficient Virtual Circuit Routing
, 2013
"... We consider virtual circuit routing protocols, with an objective of minimizing energy, in a network of components that are speed scalable, and that may be shutdown when idle. We assume that the speed s of the router is proportional to its load, and assume the standard model for component power, name ..."
Abstract
-
Cited by 1 (1 self)
- Add to MetaCart
(Show Context)
We consider virtual circuit routing protocols, with an objective of minimizing energy, in a network of components that are speed scalable, and that may be shutdown when idle. We assume that the speed s of the router is proportional to its load, and assume the standard model for component power, namely that the power is some constant static power plus sα, where typically α ∈ [1.1, 3]. We give a polynomial-time offline algorithm that is the combination of three natural combinatorial algorithms, and show that for any fixed α the algorithm has approximation ratio O(logα k), where k is the number of demand pairs. The algorithm extends rather naturally to a randomized online algorithm, which we show has competitive ratio Õ(log3α+1 k). This is the first online result for the problem. We also show that this online algorithm has competitive ratio Õ(logα+1 k) for the case that all connections have a common source. 1
Cluster Before You Hallucinate: Approximating Node-Capacitated Network Design and Energy Efficient Routing
, 2013
"... We consider circuit routing with an objective of minimizing energy, in a network of routers that are speed scal-able and that may be shutdown when idle. We consider both multicast routing and unicast routing. It is known that this energy minimization problem can be reduced to a capacitated flow netw ..."
Abstract
- Add to MetaCart
(Show Context)
We consider circuit routing with an objective of minimizing energy, in a network of routers that are speed scal-able and that may be shutdown when idle. We consider both multicast routing and unicast routing. It is known that this energy minimization problem can be reduced to a capacitated flow network design problem, where ver-tices have a common capacity but arbitrary costs, and the goal is to choose a minimum cost collection of vertices whose induced subgraph will support the specified flow requirements. For the multicast (single-sink) capacitated design problem we give a polynomial-time algorithm that is O(log3 n)-approximate with O(log4 n) congestion. This translates back to a O(log4α+3 n)-approximation for the multicast energy-minimization routing problem, where α is the polynomial exponent in the dynamic power used by a router. For the unicast (multicommodity) capacitated design problem we give a polynomial-time algorithm that is O(log5 n)-approximate with O(log12 n) congestion, which translates back to a O(log12α+5 n)-approximation for the unicast energy-minimization routing problem.
