Recent advancements in graph-based analysis and solutions of instantly decodable network coding (IDNC) trigger the interest to extend them to more complicated opportunistic network coding (ONC) scenarios, with limited increase in complexity. In this paper, we design a simple IDNC-like graph model for a specific subclass of ONC, by introducing a more generalized definition of its vertices and the notion of vertex aggregation in order to represent the storage of non-instantly-decodable packets in ONC. Based on this representation, we determine the set of pairwise vertex adjacency conditions that can populate this graph with edges so as to guarantee decodability or aggregation for the vertices of each clique in this graph. We then develop the algorithmic procedures that can be applied on the designed graph model to optimize any performance metric for this ONC subclass. A case study on reducing the completion time shows that the proposed framework improves on the performance of IDNC and gets very close to the optimal performance. Opportunistic network coding (ONC) was recently shown to provide fast and tailored packet delivery according to real-time demands of receivers and their side information [1]- [4] . The philosophy behind ONC is to exploit the previously stored source packets and undecoded packet combinations at the receivers in selecting subsequent combinations to maximize the network gains. By an undecoded packet combination for a given receiver, we mean a coded combination of source packets including more than one missing source packet at that receiver, thus preventing it from decoding a new source packet when received. Despite the benefits in storing such combinations for future decoding instances, exploring these benefits makes the proposed ONC algorithms in the literature highly complex and unscalable, as they need to examine an exploding number of sets and virtual queues to find suitable network codes. Moreover, there does not exist a general ONC framework to optimize any desired metric in a network. On the other hand, many advancements have been achieved in analyzing, optimizing, and designing simple algorithms for a special subclass of ONC, namely instantly decodable network coding (IDNC), which does not allow any receiver to store undecoded packet combinations. These advancement were made possible thanks to the IDNC's simple graph model [5]- [9] . Despite the promising performance and easy scalability of the proposed IDNC algorithms, the fact of not storing and exploiting undecoded packet combinations in future decoding instances remains a clear limitation against exploring further performance improvements.
Opportunistic network coding (ONC) is a network coding approach that exploits previously downloaded files at the receivers to optimize the subsequent file combinations at the transmitters REF .
A graph model for opportunistic network coding
2015 International Symposium on Network Coding (NetCod)
2015 International Symposium on Network Coding (NetCod)
Mathematics Computer Science