A NEURAL NETWORK BASED TRAFFIC-AWARE FORWARDING STRATEGY IN NAMED DATA NETWORKING

Named Data Networking (NDN) is a new Internet architecture which has been proposed to eliminate TCP/IP Internet architecture restrictions. This architecture is abstracting away the notion of host and working based on naming datagrams. However, one of the major challenges of NDN is supporting QoS-aware forwarding strategy so as to forward Interest packets intelligently over multiple paths based on the current network condition. In this paper, Neural Network (NN) Based Traffic-aware Forwarding strategy (NNTF) is introduced in order to determine an optimal path for Interest forwarding. NN is embedded in NDN routers to select next hop dynamically based on the path overload probability achieved from the NN. This solution is characterized by load balancing and QoS-awareness via monitoring the available path and forwarding data on the traffic-aware shortest path. The performance of NNTF is evaluated using ndnSIM which shows the efficiency of this scheme in terms of network QoS improvementof17.5% and 72% reduction in network delay and packet drop respectively

A New Virtual Backbone forWireless Ad-Hoc Sensor Networks with Connected Dominating Set

http://citi.insa-lyon.fr/wons2006/index.htmlA wireless Ad-hoc sensor network consists of a number of sensors spread across a geographical area as a collection of sensors that form an ad-hoc wireless network. Sensors are very tiny devices that their primary function is to sense the target, convert the signal into a suitable data format, and pass on the data to a command node. These sensor nodes are very heavily constrained in processing power, and have a limited energy supply. Since energy is such a scarce resource, several algorithms have been developed at the routing and MAC layers to utilize energy efficiently and extend the lifetime of the network. First layer of the sensor networks is the infrastructure layer and there is no backbone for these networks. In this paper, we propose a virtual backbone for these networks and we measure the network lifetime and survivability as the performance evaluation metrics of the proposed model