Abstract:
The term delay-tolerant network (DTN) is coined to describe and include all types of discon nected,long delay, disrupted or intermittently-connected networks. So, in such network, commu nication is created with the help of encounter opportunities between nodes and those nodes follow
store-carry and forward approach to achieve data delivery. In this approach, each node stores the
messages in their buffers until they encounter another node and also to achieve a high delivery
ratio most of DTN routing transmits several copies of messages. But the combination of long
term storage and several copies of message transmission in this process impose greater transmis sion overhead and buffer occupancy. Most of the previous works on improving the performance
of routing do not consider the issue of resource limitations like buffer and bandwidth. However,
hand held devices which are having limited storage and bandwidth are used in many of DTN ap plications Therefore, buffer management policies have a direct impact on routing performance of
DTNs routing. Basing on this point, in this paper Message Drop control with priority(MDCP)
buffer management policy has been proposed in the situations where there is short contact duration,
limited bandwidth and buffer.
The proposed policy prioritize messages in parallel with controlling unnecessary message drops
by using three local information’s namely hop count, time to live and size of messages. The per formance of proposed policy is validated through simulation by using opportunistic Network Envi ronment (ONE) simulator. The proposed Message Drop Control with priority buffer management
policy (PMDCP) and existing buffer management policies namely Drop oldest (DO), Drop Largest
(DL), Drop Maximum Hop Count (DMaxHop), Efficient buffer management policy (EBMP) was
adapted on Epidemic Routing(ER) protocol for evaluation. They were analyzed on two different
metrics namely delivery probability and overhead ratio. The simulation results obtained in this
thesis shows that for the ER with the proposed policy, the message delivery probability is high and
overhead is low. Therefore, the proposed policy has better performances than existing policies by
increasing delivery probability and decreasing overhead ratio.
