The Kalman filter is a recursive Best Linear Unbiased Estimator (BLUE) for a linear dynamic system with uncorrelated white process and measurement noises. It has been extended to the case where the noises are Markov and/or crosscorrelated for the same time instant. This paper presents optimal batch and semi-recursive filters and a suboptimal recursive filter for a linear discrete-time system wi...

With the growth of bandwidth, real-time video streaming service becomes popular. Such application is also considered a future killer application on Internet. Recent research efforts have demonstrated the promising potential of building cost-effective video streaming systems on top of peer-to-peer (P2P) networks. Since the peers have limited capacity, such as upstream bandwidth, each streaming s...

Fairness is an inherent and fundamental factor of queue service disciplines in a large variety of queueing applications, ranging from computer systems, communications systems and call centers to airport and supermarket waiting lines. Service time variability across jobs is a major factor affecting both system performance and scheduling rules (for example, computer systems prioritize short jobs ...

This paper describes the implementation and use of a prototype mul-ticast late-binding RPC (LbRPC) system. The system provides a mechanism for exporting arbitrary code and data across a network to multiple hosts for evaluation. This provides a near optimum total execution time for the application without requiring continual monitoring and estimation of the state of the hosts and the intervening...

The traditional Karatsuba algorithm for the multiplication of polynomials and multi-precision integers has a time complexity of O(n) and a space complexity of O(n). Roche proposed an improved algorithm with the same O(n) time complexity but with a much reduced O(log n) space complexity. In Roche’s paper details were provided for multiplication of polynomials, but not for multi-precision integer...

Novel method of reconstructing dynamical networks from empirically measured time series is proposed. By examining the variable–derivative correlation of network node pairs, we derive a simple equation that directly yields the adjacency matrix, assuming the intra-network interaction functions to be known. We illustrate the method on a simple example, and discuss the dependence of the reconstruct...

We present an efficient algorithm for the confluent hypergeometric functions when the imaginary part of b and z is large. The algorithm is based on the steepest descent method, applied to a suitable representation of the confluent hypergeometric functions as a highly oscillatory integral, which is then integrated by using various quadrature methods. The performance of the algorithm is compared ...

We describe two techniques for fast multiple-precision evaluation of linearly convergent series, including power series and Ramanujan series. The computation time for N bits is O((logN)M(N)), whereM(N) is the time needed to multiply twoN -bit numbers. Applications include fast algorithms for elementary functions, π, hypergeometric functions at rational points, ζ(3), Euler’s, Catalan’s and Apéry...

We show how results known for discrete time GI/GI/1 systems with service time distributions of finite support can be generalized to include arbitrary, especially long-tailed distributions of the service time. Therefore we prove and exploit the property, that the tail of the service time distribution beyond a certain bound has negligible effect on the idle times. This enables to compute the idle...

Abstract. Time-varying network optimization problems have tradition-ally been solved by specialized algorithms. These algorithms have NP-complement time complexity. This paper considers the time-varying short-est path problem, in which can be optimally solved in O(T(m + n)) time,where T is a given integer. For this problem with arbitrary waiting times,we propose an approximation algorithm, whic...