network coding

This paper presents an optimization model to increase the amount of data collected and balance the bandwidth consumption of the edges and uses network coding. To solve this model, the dual method is used and to calculate a lower bound and find the optimal answer and point in the optimization model, the Karush-KunTucker condition is used, which requires calculating the derivative of the Lagrangian function with respect to its variables. Solving this problem and equations in polynomial time is very difficult, time consuming and almost impractical due to the involvement of different parameters and limited resources of wireless sensor networks with a large number of nodes, so to solve this problem, a distributed and iterative algorithm is proposed. It uses the sub gradient method and the network flow separation method. The effectiveness of the proposed model and algorithm has been investigated by simulation in terms of number of source sensor nodes, Lagrangian coefficient and step size. Up to 23% of bandwidth consumed, average network life and energy consumed.

Recently, a new technique called network coding has been introduced where it has numerous advantages on the computer networks. Network coding changes the traditional view of data transfer in store and forward paradigm and allows the nodes to store packets in their memory to combine with other packets, then, send to next nodes. In this paper, an optimization problem is proposed which balance memory utilization in network-coding-based-multicast routing of Wireless Sensor Networks (WSNs). In the large WSNs, solving this optimization problem in a centralized manner is impractical and almost impossible, therefore, by using sub-gradient and decomposition techniques, a distributed algorithm is presented in which the nodes make a decision based on local information. The performance evaluation of proposed mechanisms are carried by OMNETT++ simulator and the results show that the proposed model averagely decreases the end to end delay and buffer overflow by 17% and 95%, respectively. However, it increases the energy consumption and consequently decreases lifetime by 14%. The decentralized algorithm decreases buffer overflow 69% and has more delay by 11% than the optimization model, however, it can be utilized in large WSNs due to its distributed computations.

Energy constraint in wireless sensor networks, have been made the packets routing with essential issues. In event based applications, the inherent constraint of these networks and large packet traffics affects the networks lifetime. Hence, the energy of sensor nodes near the sink node will be exhusted and the duty of WSNs will be affected with this problem. Network coding scheme with encoding and decoding of data packets, have improved the throughput, reduces the average end-to-end delays and resilient the networks against the fails. In this paper, we proposes a routing algorithm using network coding scheme. For selecting appropriate routing paths, the proposed scheme considers the link quality and residual energy of neighbor nodes. Simulation results show that the proposed scheme increases the network reliability and decreases the energy consumption in comparing with other relate scheme.

Routing is a critical issue in telecommunication networks. In routing algorithms, the changes in data packets by intermediate nodes are not allowed. Network coding is a new method for data transmission in telecommunication networks which has advantages such as the improvement in network performance and throughput. In this method, intermediate nodes send a combining code of incoming packets to the destination node. Opportunistic routing has the potential to substantially increase wireless network throughput. In this approach, no node is selected as the intermediate node, and each node which receives the data can transfer them to the destination. In this paper, a method is proposed based on opportunistic routing in network coding to increase the throughput of wireless networks. In the proposed method, the random linear coding of forwarding packets from a source is used; and decoding of the packets is not required in all intermediate nodes. In addition, a fixed path is not considered for data transmission and opportunistic routing is used. The performance of proposed methods is simulated using simulator NS-2 and compared with COPE and EXOR. The simulation results show that the proposed method improves the network throughput.