6 research outputs found
Exchange of Services in Networks: Competition, Cooperation, and Fairness
Exchange of services and resources in, or over, networks is attracting
nowadays renewed interest. However, despite the broad applicability and the
extensive study of such models, e.g., in the context of P2P networks, many
fundamental questions regarding their properties and efficiency remain
unanswered. We consider such a service exchange model and analyze the users'
interactions under three different approaches. First, we study a centrally
designed service allocation policy that yields the fair total service each user
should receive based on the service it others to the others. Accordingly, we
consider a competitive market where each user determines selfishly its
allocation policy so as to maximize the service it receives in return, and a
coalitional game model where users are allowed to coordinate their policies. We
prove that there is a unique equilibrium exchange allocation for both game
theoretic formulations, which also coincides with the central fair service
allocation. Furthermore, we characterize its properties in terms of the
coalitions that emerge and the equilibrium allocations, and analyze its
dependency on the underlying network graph. That servicing policy is the
natural reference point to the various mechanisms that are currently proposed
to incentivize user participation and improve the efficiency of such networked
service (or, resource) exchange markets.Comment: to appear in ACM Sigmetrics 201
Loop-Free Backpressure Routing Using Link-Reversal Algorithms
The backpressure routing policy is known to be a throughput optimal policy that supports any feasible traffic demand in data networks, but may have poor delay performance when packets traverse loops in the network. In this paper, we study loop-free backpressure routing policies that forward packets along directed acyclic graphs (DAGs) to avoid the looping problem. These policies use link reversal algorithms to improve the DAGs in order to support any achievable traffic demand.
For a network with a single commodity, we show that a DAG that supports a given traffic demand can be found after a finite number of iterations of the link-reversal process. We use this to develop a joint link-reversal and backpressure routing policy, called the loop free backpressure (LFBP) algorithm. This algorithm forwards packets on the DAG, while the DAG is dynamically updated based on the growth of the queue backlogs. We show by simulations that such a DAG-based policy improves the delay over the classical backpressure routing policy. We also propose a multicommodity version of the LFBP algorithm, and via simulation we show that its delay performance is better than that of backpressure.National Science Foundation (U.S.) (Grant CNS-1116209)United States. Office of Naval Research (Grant N00014-12-1-0064