An Efficient Buffer Management Policy for DTN

AbstractDelay or Disruption Tolerant Networks (DTNs) are challenged networks where an end-to-end path may not always exist, due to which it is necessary to use a store-carry-forward paradigm for routing messages from source to destination. DTNs have emerged from MANETs, inheriting their typical properties like mobility, network partitioning, sparse network structure, etc., differing in the inability to use IP. Due to the high mobility of nodes, and limited radio transmission range, two nodes may not always be able to communicate with each other. Thus, communication is established with the help of encounter opportunities between nodes. So intelligent relay selection plays an important role in routing performance. But apart from relay selection, effective buffer management policies also have an impact on routing performance. In this paper we have discussed existing buffer management methods in literature and proposed a novel buffer management scheme based on hop-count and TTL, which uses partial network knowledge. Experimental results show that the proposed buffer management scheme outperforms existing buffer management policies in terms of higher delivery rate and lower overhead ratio

Opportunistic Networks: Present Scenario- A Mirror Review

Opportunistic Network is form of Delay Tolerant Network (DTN) and regarded as extension to Mobile Ad Hoc Network. OPPNETS are designed to operate especially in those environments which are surrounded by various issues like- High Error Rate, Intermittent Connectivity, High Delay and no defined route between source to destination node. OPPNETS works on the principle of “Store-and-Forward” mechanism as intermediate nodes perform the task of routing from node to node. The intermediate nodes store the messages in their memory until the suitable node is not located in communication range to transfer the message to the destination. OPPNETs suffer from various issues like High Delay, Energy Efficiency of Nodes, Security, High Error Rate and High Latency. The aim of this research paper is to overview various routing protocols available till date for OPPNETs and classify the protocols in terms of their performance. The paper also gives quick review of various Mobility Models and Simulation tools available for OPPNETs simulation

Designing Smart Adaptive Flooding in MANET using Evolutionary Algorithm

International audienceThis paper deals with broadcasting warning / emergency messages in mobile ad hoc networks. Traditional broadcasting schemes tend to focus on usually high and homogeneous neighborhood densities environments. This paper presents a broadcasting protocol that locally and dynamically adapts its strategy to the neighborhood densities. The behavior of the protocol is tuned using various internal parameters. Multiple combinations of those parameters have been pre-computed as optimal solutions for a range of neighborhood densities, and the most relevant one is dynamically chosen depending on the locally perceived environment. The combinations were determined by coupling an evolutionary algorithm and a network simulator, using a statistically realistic radio-propagation model (Shadowing Pattern). This approach is compared with other probabilistic methods while broadcasting an emergency message in vehicular ad hoc networks with variable and heterogeneous vehicle densities. In such a context, it is expected from the network to enable each node to receive the warning message. The results show that our protocol covers the whole network, whereas other methods only have a probability of 0.57 to 0.9 to cover the entire network

Using a Multiobjective Approach to Balance Mission and Network Goals within a Delay Tolerant Network Topology

This thesis investigates how to incorporate aspects of an Air Tasking Order (ATO), a Communications Tasking Order (CTO), and a Network Tasking Order (NTO) within a cognitive network framework. This was done in an effort to aid the commander and or network operator by providing automation for battlespace management to improve response time and potential inconsistent problem resolution. In particular, autonomous weapon systems such as unmanned aerial vehicles (UAVs) were the focus of this research This work implemented a simple cognitive process by incorporating aspects of behavior based robotic control principles to solve the multi-objective optimization problem of balancing both network and mission goals. The cognitive process consisted of both a multi-move look ahead component, in which the future outcomes of decisions were estimated, and a subsumption decision making architecture in which these decision-outcome pairs were selected so they co-optimized the dual goals. This was tested within a novel Air force mission scenario consisting of a UAV surveillance mission within a delay tolerant network (DTN) topology. This scenario used a team of small scale UAVs (operating as a team but each running the cognitive process independently) to balance the mission goal of maintaining maximum overall UAV time-on-target and the network goal of minimizing the packet end-to-end delays experienced within the DTN. The testing was accomplished within a MATLAB discrete event simulation. The results indicated that this proposed approach could successfully simultaneously improve both goals as the network goal improved 52% and the mission goal improved by approximately 6%

The Impact of Rogue Nodes on the Dependability of Opportunistic Networks

Opportunistic Networks (OppNets) are an extension to the classical Mobile Ad hoc Networks (MANETs) where the network is not dependent on any infrastructure (e.g. Access Points or centralized administrative nodes). OppNets can be more flexible than MANETs because an end to end path does not exist and much longer delays can be expected. Whereas a Rogue Access Point is typically immobile in the legacy infrastructure based networks and can have considerable impact on the overall connectivity, the research question in this project evaluates how the pattern and mobility of a rogue nodes impact the dependability and overall "Average Latency" in an Opportunistic Network Environment. We have simulated a subset of the mathematical modeling performed in a previous publication in this regard. Ad hoc networks are very challenging to model due to their mobility and intricate routing schemes. We strategically started our research by exploring the evolution of Opportunistic networks, and then implemented the rogue behavior by utilizing The ONE (Opportunistic Network Environment, by Nokia Research Centre) simulator to carry out our research over rogue behavior. The ONE simulator is an open source simulator developed in Java, simulating the layer 3 of the OSI model. The Rogue behavior is implemented in the simulator to observe the effect of rogue nodes. Finally we extracted the desired dataset to measure the latency by carefully simulating the intended behavior, keeping rest of the parameters (e.g. Node Movement Models, Signal Range and Strength, Point of Interest (POI) etc) unchanged. Our results are encouraging, and coincide with the average latency deterioration patterns as modeled by the previous researchers, with a few exceptions. The practical implementation of plug-in in ONE simulator has shown that only a very high degree of rogue nodes impact the latency, making OppNets more resilient and less vulnerable to malicious attacks