Opportunistic named data networking improvements via load balancing - Lorenzo, John Bennedict T.
There is growing interest in both opportunistic networking and data-centric networking, with uses ranging from disaster, to urban, and vehicular communications. In order to support larger scale networks, various works have been made to address congestion in opportunistic and data centric networks. Few have tried addressing the problem of traffic unevenly handled by just a few nodes, leading to some nodes to be underutilized affecting performance. Our approach tries to distribute the amount of traffic across nodes by using epidemic routing together with a dropping strategy that optimizes the forwarding efficiency (ratio between successfully delivered data vs the total number of forwards). We show that our approach achieves a higher performance than SimBet and epidemic routing under random walk scenarios.