Multiplepath source routing protocols allow a data source node to distribute the total traffic among available paths. In this article, we consider the problem of jammingaware 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 multisource 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 multisource 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.
As a result, there do exist various motivations for cloud server to behave unfaithfully and to return incorrect results, i.e., they may behave beyond the classical semi honest model.
Fully homomorphic encryption (FHE) scheme, a general result of secure computation outsourcing has been shown viable in theory, where the computation is represented by an encrypted combinational Boolean circuit that allows to be evaluated with encrypted private inputs.
Modules:
 Allocation of traffic across multiple routing paths
 Characterizing The Impact Of Jamming
 Effect of Jammer Mobility on Network
 Estimating EndtoEnd Packet Success Rates
 Optimal JammingAware Traffic Allocation
Tools Used:
Front End 
: 
ASP.Net with C# 
Back End 
: 
SQL Server 2005 
