DEVELOPMENT OF A MODIFIED TOKEN BASED CONGESTION CONTROL SCHEME WITH ADAPTIVE FORWARDING FOR OPPORTUNISTIC NETWORK
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- NGN 3000
ABSTRACT
This research presents the development of a modified token-based congestion control scheme with adaptive forwarding mechanism (mTBCC) algorithm for addressing congestion problems in opportunistic networks (OppNets). The algorithm addresses the limitations associated with the standard token –based congestion control (TBCC) in terms of its ability to redirect the traffic from more congested nodes of OppNet to congestion-free nodes without necessarily compromising computational time. This is because the TBCC has the tendency to drop significant number of messages when node is full (overflow) in order to control congestion. OppNet was modeled using ONE simulator with Eclipse, which is a java based programming language. The node density was controlled by varying the greatest connected component (GCC) expressed in percentage and the corresponding results were used to evaluate the performance of the proposed approach using (dropped messages and network transit time) as performance metrics. The results showed reduction in dropped messages and network transit time across all scenarios considered. At queue size of 10(QS-10), TBCC had 38592 messages, and mTBCC has 36037 messages, yielding an average improvement of 13.91%, at queue size of 20 (QS-20), TBCC had 30330 messages and mTBCC had 27845 messages resulting in average improvement of 10.78%, at queue size of 30(QS-30) TBCC produced 28356 messages and mTBCC yielded 26767 messages resulting to an average improvement of 5.68% and at queue size of 40(QS-40) , TBCC had 23150 messages while mTBCC had 22197 messages, providing an average improvement of 4.22% respectively for dropped messages. In addition, at 0.5GCC, TBCC had 29401.70 time and mTBCC had 27151.41 time, producing an average improvement of 8.34%, at 0.6GCC, TBCC produced 16319.29 time and mTBCC had 15966.42 time, resulting in average improvement of 2.19%, at 0.7GCC, TBCC yielded 13178.21 time and mTBCC produced 12581.01 time, resulting in an average improvement of 4.61%, and at 0.8GCC, TBCC had 12333.55 time and mTBCC had 11453.23 time, yielding an average improvement of 7.63% for network transit time.
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