Jamming-Aware Traffic Allocation for Multiple-Path Routing Using Portfolio Selection

Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. In this article, we consider the problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics.

We show that in multi-source networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network’s ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios.

Existing System:

To distribute the total traffic among available paths the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. If any path to be disturbed/jammed a routing path is requested an existing routing path is not be updated, the responding nodes along the path will disconnect the routing path.

Proposed System:

We propose techniques for the network nodes to estimate and characterize the impact of jamming and for a source node to incorporate these estimates into its traffic allocation. We show that in multi-source networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization.

We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics which allow individual network nodes to locally characterize the jamming impact and aggregate this information for the source nodes. We demonstrate that the use of portfolio selection theory allows the data sources to balance the expected data throughput with the uncertainty in achievable traffic rates.

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Modules:

  • Allocation of traffic across multiple routing paths
  • Characterizing The Impact Of Jamming
  • Effect of Jammer Mobility on Network
  • Estimating End-to-End Packet Success Rates
  • Optimal Jamming-Aware Traffic Allocation

Tools Used:

Front End : ASP.Net with C#
Back End : SQL Server 2005