Enhancement of an Error Minimizing Framework for Localizing Jammers in Wireless Networks: A Survey

Abstract-Jammers can sternly mess up the communication in wireless networks. The jamming attacks can be aggressively eradicate by the protector thus permits by the jammer location information. Our intensions to plan a framework that can be localize multiple jammers with high accuracy. Maximum of surviving jammer localization scheme exploit indirect measurement such as neighbor lists, PDR, hearing range that can be disturbed by jamming attacks which is tough to focus the jammers perfectly. In its place we utilize a direct measurements-JSS. It is difficult to estimate and it can be derive in order signals. So we formulate an estimation scheme that is relying on ambient noise floor. To measure the estimation errors, we can explain an evaluation feedback metric. In addition to decrease the estimation errors by explain an evaluation feedback metric. We utilize the jammer localization problem as nonlinear optimization issue then global optimal solution is nearby jammer location. Then we discover many experimental algorithms for this global optimal solution but the watchdog timer shows our error minimizing framework obtains enhanced performance than the current scheme