MinHop (MH) Transmission strategy to optimized performance of epidemic routing protocol

Delay tolerant network aims to provide the network architecture in environments where end-to-end path may never exist for long duration of time Furthermore dynamic topology changes limited buffer space and non stable connectivity make routing a challenging issue The research contribution regarding DTN routing protocols can be categorized in to single and multi copy strategies A single copy strategy makes less use of network resources but suffers from long delay and less delivery probability Multi copy schemes enjoy better delivery probability and minimum delivery delay at the cost of heavy use of network resource Moreover DTN nodes operate under short contact duration and limited transmission bandwidth Therefore it is not possible for a node to transmit all messages from its forwarding queue Hence the order at which the messages are forwarded becomes very vital In this paper we propose a forwarding queue mode named MinHop We prove through simulations that the proposed policy performs better then FIFO in terms of delivery probability overhead message drop and rela

A novel queue management policy for delay-tolerant networks

Delay-tolerant networks (DTNs) have attracted increasing attention from governments, academia and industries in recent years. They are designed to provide a communication channel that exploits the inherent mobility of trams, buses and cars. However, the resulting highly dynamic network suffers from frequent disconnections, thereby making node-to-node communications extremely challenging. Researchers have thus proposed many routing/forwarding strategies in order to achieve high delivery ratios and/or low latencies and/or low overheads. Their main idea is to have nodes store and carry information bundles until a forwarding opportunity arises. This, however, creates the following problems. Nodes may have short contacts and/or insufficient buffer space. Consequently, nodes need to determine (i) the delivery order of bundles at each forwarding opportunity and (ii) the bundles that should be dropped when their buffer is full. To this end, we propose an efficient scheduling and drop policy for use under quota-based protocols. In particular, we make use of the encounter rate of nodes and context information such as time to live, number of available replicas and maximum number of forwarded bundle replicas to derive a bundle\u27s priority. Simulation results, over a service quality metric comprising of delivery, delay and overhead, show that the proposed policy achieves up to 80 % improvement when nodes have an infinite buffer and up to 35 % when nodes have a finite buffer over six popular queuing policies: Drop Oldest (DO), Last Input First Output (LIFO), First Input First Output (FIFO), Most FOrwarded first (MOFO), LEast PRobable first (LEPR) and drop bundles with the greatest hop-count (HOP-COUNT)