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Distributed optimal dispatch strategies are attracting attention to exploit the fast and continuous control capabilities of converter-interfaced small-scale generators connected to power distribution systems. However, their impact on the supporting cyber structure and their scalability to ensure real-time performance need further study. In this paper, a proximal Jacobian distributed optimal power flow model for the dispatch of converter-based power distribution systems is proposed, which features a favorable convergence behavior. A suitable cyber architecture to realize such model is developed through this paper. The corresponding cyber costs are quantified and the proposed architecture's scalability is analyzed through numerical experiments.

We propose and evaluate a signaling and transmission algorithmic system for wireless digital networks, in conjunction with a Traffic Monitoring Algorithm (TMA) for dynamic capacity allocation in multimedia ATM environments. The deployed signaling protocol is stable, and two transmission techniques are compared: a Framed Time-Domain Based (FTDB) technique and a Framed CDMA (FCDMA) technique. The overall signaling/transmission/traffic monitoring proposed system has powerful performance characteristics, while the TMA-FTDB combination is superior to the TMA-FCDMA combination in environments where message lengths are relatively short and the speed of the transmission lines is relatively low. We also evaluate a system deploying the Ethernet protocol as a signaling protocol, instead. In the presence of relatively tight admission delay constraints in signaling, the latter is significantly inferior to our proposed signaling technique. As the above admission delay constraints diminish, the Ethernet protocol breaks down, while our proposed signaling technique maintains its high performance characteristics.

We address the accommodation of multimedia traffic by ATM broadband networks. We isolate a single network channel and we search for capacity allocation/transmission multiplexing policies which satisfy all traffic QOSs with simultaneous high utilization of channel capacity resources, in the presence of variable traffic rates. Towards that direction, we superimpose a high-level traffic-monitoring protocol which determines capacity allocations for each traffic category, dynamically. The latter protocol has sequential and implementation-efficient characteristics, and induces moving boundaries within prespecified and fixed channel frames. The channel frames are selected to satisfy the jittering constraints of all the traffics, such as voice, video and high versus low speed data. The high level protocol, in conjunction with the channel frame structure and the specifics of the transmission policy, may satisfy all traffic QOSs and may simultaneously attain high channel utilization, for certain variability conditions of the traffic rates and at relatively low implementation cost. Performance analysis as well as numerical evaluations are provided.

We consider digital wireless multimedia LANs and time‐varying traffic rates. To deal effectively with the dynamics of the time‐varying traffic rates, a Traffic Monitoring Algorithm (TMA) is deployed to dynamically allocate channel capacities to the heterogeneous traffics. The TMA is implemented as a higher level protocol that dictates the capacity boundaries within two distinct framed transmission techniques: a Framed Time Domain‐Based (FTDB) technique and a Framed CDMA (FCDMA) technique. The performance of the TMA in the presence of the FTDB technique is compared to its performance in the presence of the FCDMA technique for some traffic scenarios. The performance metrics used for the TMA‐FTDB and TMA‐FCDMA combinations are channel capacity utilization factors, traffic rejection rates, and traffic delays. It is found that the TMA‐FTDB is superior to the TMA‐FCDMA when the speed of the transmission links is relatively low and the lengths of the transmitted messages are relatively short. As the speed of the transmission links and the length of the transmitted messages increase, the TMA‐FCDMA eventually outperforms the TMA‐FTDB.

This paper describes and analyzes a medium access protocol for wireless personal communication networks serving integrated traffic. A multi‐priority mechanism, which is implemented and controlled explicitly by the users and without any involvement from the network is incorporated into the protocol. We examine the proposed protocol under reservation and non‐reservation policies and evaluate its performance when handling integrated voice and data traffic. The proposed protocol is suitable to be used in Personal Communication Systems aiming to provide integrated (voice/data) services.

The design of hybrid transmission algorithms for the multiplexing of voice and data over a common digital channel is of interest to various communication networks, including cellular radio and high-speed topologies. In environments where the characteristics of the voice and data traffics may vary dynamically, the issue is the deployment of hybrid multiplexing algorithms (HMAs) which satisfy the constraints imposed by the voice traffic, while they simultaneously attain high channel utilization and induce low implementation overhead. In this paper, we propose, evaluate, and compare two HMAs: a semidynamic and a dynamic. The former induces lower implementation overhead than the latter, but it is applicable only to environments where the rate of the voice traffic may vary relatively slowly and its statistics are parametrically known. The semidynamic HMA induces frame structures, where the capacity allocation per frame, for the voice versus data traffic, is dictated by a superimposed traffic monitoring algorithm. The dynamic HMA, on the other hand, assigns each channel slot to voice versus data packets dynamically; it requires no statistical knowledge about the voice traffic, at the expense of significantly increased implementation overhead.

We consider the Channel Multiple-Access problem for messages with strict delay constraints. The constraints are represented by an upper bound on the transmission delays. For this problem, and for binary collision-noncollision feedback per slot, we present a simple full sensing window Random-Access algorithm. We analyze the algorithm and we compute the fraction of maintained traffic and the expected delay for the successfully transmitted packet, for various input Poisson intensities and various values of the bound on the transmission delays.

In this paper, fundamental neural network structures in decentralized hypothesis testing are considered. For binary hypothesis testing, the basic neural operations are established, and the Neyman-Pearson criterion is utilized due to information theoretic arguments. Then, two fundamental neural structures are considered, and analyzed and compared in terms of asymptotic performance measures. In particular, the Asymptotic Relative Efficiency performance measure is used to establish performance characteristics and tradeoffs in the two structures, for both parametrically and nonparametrically defined hypotheses. In the latter case, robust neural network structures are considered, and their superiority to parametric network structures is argued.

Robust multivariate prediction and interpolation problems for statistically contaminated vector valued second order stationary processes are considered. The statistical contamination is modeled by requiring that the spectral density matrices of the processes lie within certain nonparametric classes. Both prediction and interpolation are then formalized as games whose saddle point solutions are sought. Finally, such solutions are found and analyzed, for two specific multivariate spectral classes.

We consider multimedia wireless networks in environments where traffic characterizations and traffic rates are generally time‐varying. For such networks we propose a CDMA transmission policy, in conjunction with a moving boundaries concept induced by a traffic monitoring high‐level protocol. The proposed transmission/traffic management technique is analyzed and numerically evaluated.

It is known that under certain restrictions on the posterior density and assigned cost function, the Bayes estimate of a random parameter is the conditional mean. The restrictions on the cost function are that it must be a symmetric convex upward function of the difference between the parameter and the estimate. In this correspondence, asymmetrical cost functions of the following form are examined: \begin{equation} C(a, \hat{a})= \begin{cases} f_1(a- \hat{a}),& a \geq \hat{a} \\ f_2(\hat{a}- a),& a < \hat{a} \end{cases} \end{equation} wheref_1(\cdot), f_2(\cdot)are both twice-differentiable convex upward positive functions on[0, \infty]that intersect the origin. It is shown that for posterior densities satisfying a certain symmetry condition, the biased Bayes estimate is a generalized median. Furthermore, for linear polynomial functionsf_1(\cdot), f_2(\cdot), the unbiased Bayes estimate is shown to be the conditional mean.