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compromised sensor nodes, assuming that the sensor nodes can communicate with each other Second, this scheme is sensitive to node compromises Even if some nodes are compromised, there is still a high probability that a pairwise key can be reestablished between two noncompromised nodes Third, a sensor node can directly determine whether it can establish a direct key with another node, and if it can, which polynomial should be used As a result, there is no communication overhead during polynomial share discovery 534 Improving Random Key Predistribution with Expected Deployment Locations Despite the recent advances, key management in distributed sensor networks is still not an entirely solved problem This is especially because the performance of these schemes, particularly the probability of establishing a common key between communicating sensors and the ability to tolerate compromised sensors, are highly dependent on the memory available on sensor nodes.

of having to convert the output of the RBF DFE and the turbo decoderfrom the LLR values to BER values according to Equation 10.14, in order toobtain the short-term BER the data of burst.

0.6031 0.7302 0.8953 1.119 1.428

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Because of the resource constraints on sensor nodes and the need to lower the cost of sensor networks, it is always desirable to reduce the memory required by key management and allocate more resources for the sensor network applications In some applications, the sensors may have low mobility, and we may be able to predetermine the location of the sensors to a certain extent In this case, we can use the sensors location information to improve the performance of pairwise key predistribution In this subsection, we describe a simple location-aware deployment model as well as a pairwise key management scheme that can take advantage of the location information More details of random key predistribution using deployment knowledge can be found in refs [7] and [8] 534.

If you find yourself in a 3D environment in AutoCAD, you ll see a gray background and a perspective view. To work in 2D in AutoCAD, switch to a 2D environment, following these steps in AutoCAD:

IP routing table summary Maximum ECMP Paths = 1 Total routes = 11 Best routes = 11 Static routes = 6 Direct routes = 4 BGP routes = 0 RIP routes = 0 OSPF routes = 0 CLIP routes = 0 NAT routes = 0

1 A Location-Aware Deployment Model We assume that sensors are deployed in a two-dimensional area called the target eld, and two sensors can communicate with each other if they are within each other s signal range The location of a sensor can be represented by a coordinate in the target eld Each sensor has an expected location that can be predicted or predetermined After the deployment, a sensor is placed at an actual location that may be different from its expected location We call the difference between the expected location and the actual location of a sensor the deployment error for the sensor Thus, this model can be characterized by the following three parameters: 1 Signal Range dr A sensor can receive messages from another sensor if the former is located within the signal range of the latter.

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