ANALYSIS OF EPIDEMIC, PROPHET AND SPRAY AND WAIT ROUTING PROTOCOLS IN THE MOBILE OPPORTUNISTIC NETWORKS

Background: The opportunistic mobile networks (OMNs) are a type of mobile adhoc networks (MANETs) with delay-tolerant network (DTN) features, where the sender to receiver connectivity never exists most of the time, due to dynamic nature of the nodes and the network partition. The real use of OMNs is to provide connectivity in challenged environments. Methods: The paper presents the detailed analysis of three routing protocols, namely Epidemic, PROPHET and Spray and Wait, against variable size of the messages and the time to live (TTL) in the networks. The key contribution of the paper is to explore routing protocols with mobility models for the dissemination of data to the destination. Routing uses the store-carryforward mechanism for message transfer and network has to keep compromise between message delivery ratio and delivery delay. Results: The results are generated from the experiments with Opportunistic Network Environment (ONE) simulator. The performance is evaluated based on three metrics, the delivery ratio, overhead ratio and the average latency. The results show that the minimum message size (256 KB) offers better performance in the delivery than the larger message size (1 MB). It has also been observed that with the epidemic routing, since there are more message replicas, which in turn increase the cost of delivery, so with a smaller message, the protocol can reduce the overhead ratio with a high proportion. Conclusion: The average latency observed increases with the increase of the TTL of the message in three protocols with variation of the message size from 256KB to 1 MB.

Performance Improvement of DTN Routing Protocols with Enhanced Buffer Management Policy

Delay tolerant network (DTN) is one of the emerging technologies which is applied generally when there is no end-to-end path exists from source to destination all the time. The two major issues in DTN are routing and buffer management. Existing buffer management policies are based on one or more parameters such as message Time-to-Live, message age, message replication count, message size etc.,. There is no efficient approach is available for estimation of message replication count. In this work an efficient approach is proposed to estimate total number of copies of the message. The proposed buffer management approach prioritizes the messages and based on which the messages are forwarded/dropped from the buffer when there is a contact opportunity occurs/when the buffer is full. These priorities are based on message Time-to-Live, message age, message replication count and message size. This proposed buffer management policy is evaluated with two popular DTN routing protocols Spray-and-Wait and Prophet. The simulation results show that delivery probability of messages has increased with reduced buffer time average and minimized latency.

Comparative Study of Three Steganographic Methods Using a Chaotic System and Their Universal Steganalysis Based on Three Feature Vectors

In this paper, we firstly study the security enhancement of three steganographic methods by using a proposed chaotic system. The first method, namely the Enhanced Edge Adaptive Image Steganography Based on LSB Matching Revisited (EEALSBMR), is present in the spatial domain. The two other methods, the Enhanced Discrete Cosine Transform (EDCT) and Enhanced Discrete Wavelet transform (EDWT), are present in the frequency domain. The chaotic system is extremely robust and consists of a strong chaotic generator and a 2-D Cat map. Its main role is to secure the content of a message in case a message is detected. Secondly, three blind steganalysis methods, based on multi-resolution wavelet decomposition, are used to detect whether an embedded message is hidden in the tested image (stego image) or not (cover image). The steganalysis approach is based on the hypothesis that message-embedding schemes leave statistical evidence or structure in images that can be exploited for detection. The simulation results show that the Support Vector Machine (SVM) classifier and the Fisher Linear Discriminant (FLD) cannot distinguish between cover and stego images if the message size is smaller than 20% in the EEALSBMR steganographic method and if the message size is smaller than 15% in the EDCT steganographic method. However, SVM and FLD can distinguish between cover and stego images with reasonable accuracy in the EDWT steganographic method, irrespective of the message size.