Mobility management protocols allow wireless devices to move between networks. These protocols have traditionally supported the mobility of individual nodes and are therefore not optimized to support the migration of groups. Accordingly, the time required to re-establish connectivity, frequency of dropped packets and contention for the air interface increase significantly for mobile groups. We propose a protocol for mobile groups that reduces all of the above by allowing a single node to perform handoffs on behalf of all group members. This "gateway" node eliminates the need for multiple handoff messages by obscuring group membership to external parties. Through extensive simulation and implementation, we show significant reduction in handoff times, message complexity and packet loss for groups of heterogeneous, mobile sensors running AODV and DSDV. By leveraging the naturally occurring hierarchy, we demonstrate that it is possible for groups to efficiently use traditional mobility protocols to support their collective movements.

In this paper, we describe three different state space models for analyzing the security of a software system. In the first part of this paper, we utilize a semi-Markov process (SMP) to model the transitions between the security states of an abstract software system. The SMP model can be solved to obtain the probability of reaching security failed states along with the meantime to security failure (MTTSF). In the second part of the paper, we use a discrete event dynamic system model of security dynamics. We show how to derive events and transitions from existing security taxonomies. We then apply theory of discrete event control to define safety properties of the computer system in terms of the basic concepts of controllability used in discrete event control for two special sublanguages K/sub s/ and K/sub v/. These languages correspond to maximally robust controllable sub-languages. In the third approach, we show that by associating cost with the state transitions, the security quantification problem can be casted as Markov decision problem (MDP). This MOP can be solved to obtain an optimal controllable language K/sub s//spl sube/K/sub v/ the gives the minimal cost safe security policy.

Quite often failures in network based services and server systems may not be accidental, but rather caused by deliberate security intrusions. We would like such systems to either completely preclude the possibility of a security intrusion or design them to be robust enough to continue functioning despite security attacks. Not only is it important to prevent or tolerate security intrusions, it is equally important to treat security as a QoS attribute at par with, if not more important than other QoS attributes such as availability and performability. This paper deals with various issues related to quantifying the security attribute of an intrusion tolerant system, such as the SITAR system. A security intrusion and the response of an intrusion tolerant system to the attack is modeled as a random process. This facilitates the use of stochastic modeling techniques to capture the attacker behavior as well as the system's response to a security intrusion. This model is used to analyze and quantify the security attributes of the system. The security quantification analysis is first carried out for steady-state behavior leading to measures like steady-state availability. By transforming this model to a model with absorbing states, we compute a security measure called the "mean time (or effort) to security failure" and also compute probabilities of security failure due to violations of different security attributes.

Systolic implementation of neural networks is suggested. These arrays do not suffer from long feedback connections. Various learning rules are incorporated in the suggested systolic implementation of neural networks. It is shown that these arrays can be easily generalized for multilayered feedforward networks.>

In the presence of signal correlated interference, a conventional adaptive beamformer fails to perform satisfactorily due to the signal cancellation effects. This paper suggests a new technique based signal interpolation followed by spatial correlation smoothing to de-correlate the signal from the interference for avoiding signal cancellation.

The standard LMS algorithms for adaptive beamforming though straightforward, suffer from the main draw back of having slow, convergence rate. This is normally attributed to the wide range of spread of eigenvalues of the input signal vector correlation matrix. By properly pre-whitening the input signal vector these eigenvalues can be equalized thereby improving the convergence rate. An Escalator structure recently proposed for linear prediction problems is used to pre-whiten the input signal vector. This whitened signal vector is now fed to a beam former with desired main beam shape. The overall adaptive array is computationally efficient and exhibits faster convergence rate than the conventional LMS algorithms.

A new formulation of the adaptive beam forming processor is provided that facilitates the application of Kalman filtering algorithm. The problem formulation is such that it does not require apriori knowledge about the signal or the interference. Only the signal look direction needs to be specified. The resulting algorithm is capable of faster convergence then some other algorithms reported.

In this paper the problem of impulsive noise suppression in analog communication systems is considered. The problem of demodulation of amplitude and phase modulated signals in the presence of impulsive noise is formulated by introducing a binary random process to indicate the presence of impulsive noise. It is shown that sub-optimal receiver structures can be derived using this model and these are similar to some experimental receivers reported earlier in the literature. The receivers derived are non-linear in nature and their working is demonstrated through digital computer simulations.