Performance analysis of epidemic routing protocol for opportunistic networks in different mobility patterns

Author(s):  
V V Neena ◽  
V Mary Anita Rajam
2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Aarti Munjal ◽  
Tracy Camp ◽  
Nils Aschenbruck

A phenomenal increase in the number of wireless devices has led to the evolution of several interesting and challenging research problems in opportunistic networks. For example, the random waypoint mobility model, an early, popular effort to model mobility, involves generatingrandommovement patterns. Previous research efforts, however, validate that movement patterns are not random; instead, human mobility is predictable to some extent. Since the performance of a routing protocol in an opportunistic network is greatly improved if the movement patterns of mobile users can be somewhat predicted in advance, several research attempts have been made to understand human mobility. The solutions developed use our understanding of movement patterns to predict the future contact probability for mobile nodes. In this work, we summarize the changing trends in modeling human mobility asrandommovements to the current research efforts that model human walks in a more predictable manner. Mobility patterns significantly affect the performance of a routing protocol. Thus, the changing trend in modeling mobility has led to several changes in developing routing protocols for opportunistic networks. For example, the simplest opportunistic routing protocol forwards a received packet to a randomly selected neighbor. With predictable mobility, however, routing protocols can use the expected contact information between a pair of mobile nodes in making forwarding decisions. In this work, we also describe the previous and current research efforts in developing routing protocols for opportunistic networks.


Author(s):  
Salem Sati ◽  
Ahmed Sohoub ◽  
Adel Eltahar ◽  
Khairol Amali Bin Ahmad ◽  
Khaleel Ahmad ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Halikul Lenando ◽  
Mohamad Alrfaay

In opportunistic networks, the nature of intermittent and disruptive connections degrades the efficiency of routing. Epidemic routing protocol is used as a benchmark for most of routing protocols in opportunistic mobile social networks (OMSNs) due to its high message delivery and latency. However, Epidemic incurs high cost in terms of overhead and hop count. In this paper, we propose a hybrid routing protocol called EpSoc which utilizes the Epidemic routing forwarding strategy and exploits an important social feature, that is, degree centrality. Two techniques are used in EpSoc. Messages’ TTL is adjusted based on the degree centrality of nodes, and the message blocking mechanism is used to control replication. Simulation results show that EpSoc increases the delivery ratio and decreases the overhead ratio, the average latency, and the hop counts as compared to Epidemic and Bubble Rap.


Author(s):  
Halikul Lenando ◽  
Aref Hassan Kurd Ali ◽  
Mohamad Alrfaay

Background: In traditional networks, nodes drop messages in order to free up enough space for buffer optimization. However, keeping messages alive until it reaches its destination is crucial in Opportunistic Networks. Therefore, this paper proposes an Acumen Message Drop scheme (AMD) that consider the impact of the message drop decision on data dissemination performance. Methods: In order to achieve this goal, AMD drops the message based on the following considerations: the estimated time of message's arrival to its destination, message time to live, message transmission time, and the waiting time of the message in the queue. AMD scheme works as a plug-in in any routing protocol. Results: Performance evaluation shows that the integration of the proposed scheme with the PRoPHET routing protocol may increase efficiency by up to 80%, while if integrated with Epidemic routing protocol, efficiency increases by up to 35%. Moreover, the proposed system significantly increases performance in the case of networks with limited resources. Conclusion: To the best of our knowledge, most of the previous works did not address the issue of formulating the message drop decision in the non-social stateless opportunistic networks without affecting performance.


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