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Abstract This paper considers the linear output regulation problem for uncertain over-actuated plants. The general form of input redundancy considered in this work implies the existence of multiple control inputs and state trajectories compatible with a prescribed reference for the output. On-line selection, according to certain performance criteria, of the most suitable of these inputs-state trajectories leads to a linear output regulation problem with dynamic redundancy allocation. We present a solution that augments the well known internal model control scheme with two additional dynamical systems. The first one, named annihilator , parametrizes the inputs and the corresponding state trajectories that are invisible from the output. The second one, named redundancy allocator , dynamically selects the best solution according to a predefined performance criterion. We derive explicit solutions for the performance criterion equal to relaxed 1, 2, and ∞ - norms of the plant input. This set-up is a particular case of the dynamic redundancy allocation problem named dynamic input allocation. The proposed solutions can be implemented in an error feedback form and are especially suitable for optimizing sparsity, power and amplitude of the control input. Finally, structural stability, robustness and existence of a unique steady-state are proven. [ABSTRACT FROM AUTHOR]

In this paper we focus on two scheduling problems in container terminal: (i) the Yard Truck Scheduling Problem (YTSP) which assigns a fleet of trucks to transport containers between the QCs and the storage yard to minimize the makespan, (ii) the integrated Yard Truck Scheduling Problem and Storage Allocation Problem (YTS–SAP) which extends the first problem to consider storage allocation strategy for discharging containers. Its object is to minimize the total delay for all jobs. The second model is improved to consider the truck ready time. Due to the computational intractability, two recently developed solution methods, based on swarm intelligence technique, are developed for problem solution, namely, particle swarm optimization (PSO) and bacterial colony optimization (BCO). As these two algorithms are originally designed for continuous optimization problems, we proposed a particular mapping method to implement them for YTSP and YTS–SAP, both of which are discrete optimization problems. Through comparing the PSO algorithms and BCO algorithm with GA by an experiment conducted on different scale instances, we can draw a conclusion that LPSO perform best in YTSP while BCO perform best in YTS–SAP. [ABSTRACT FROM AUTHOR]

This work presents a study of the effects of the leakage currents in the control transistors of a dynamic storage cell intended to be used with Bulk-BICS circuits. A means to introduce a controlled discharge current to the storage element is presented, making the dynamic storage cell stable in the reset-state at rest. This self-reset feature allows eliminating the recurrent reset pulse necessary in the previous version for stabilization of the memory cell. A reduction in the current consumption when the circuit is idle is also achieved with this technique. [ABSTRACT FROM AUTHOR]

A method is suggested that allows thermodynamic data to be dynamically stored and retrieved. The purpose of the method is to reduce computer simulation time when Calphad type databases are being used. Some test simulations are presented and these indicate that simulations can be made to run 5–40 times faster without any significant loss of accuracy. [ABSTRACT FROM AUTHOR]

Abstract: We study the single-device Dynamic Storage Allocation (DSA) problem and the multi-device Balancing DSA problem in this paper. The goal is to dynamically allocate the job into memory to minimize the usage of space without concurrency. The SRF problem is just a variant of the DSA problem. Our results are as follows. [•] The NP-completeness for the 2-SRF problem, 3-DSA problem, and DSA problem for jobs with agreeable deadlines. [•] An improved 3-competitive algorithm for jobs with agreeable deadlines on single-device DSA problems. A 4-competitive algorithm for jobs with agreeable deadlines on multi-device Balancing DSA problems. [•] Lower bounds for jobs with agreeable deadlines: any non-clairvoyant algorithm cannot be -competitive and any clairvoyant algorithm cannot be -competitive. [•] The first -competitive algorithm for general jobs on multi-device Balancing DSA problems without any assumption. [Copyright &y& Elsevier]

Abstract: We propose DMP-tree, a dynamic M-way prefix tree, data structure for the string matching problem in general and prefix matching in particular. DMP-tree has been initially devised for fast and efficiently handling prefix matching which constitutes the building block of some applications in the computer realm and related area. It is assumed there are strings of an alphabet which are ordered. The data strings can have different lengths and some of them can be prefixes of others. Two well known applications of prefix matching are layers 3 and 4 switching in TCP/IP protocols. In layer 3 switching, routers forward an IP packet by checking its destination address and finding the longest matching prefix from a database. In layer 4 switching, the source and destination addresses are used to classify packets for differentiated service and Quality of Services (QoS). DMP-tree is a superset of B-tree. When none of the data strings are a prefix of each other, DMP-tree is the same as B-tree. In DMP-tree, no data string can be in a higher level than another data string which is its prefix. This requires a special procedure for node splitting. Indeed, node splitting differentiates DMP-tree from B-tree. The proposed data structure is simple, well defined, easy to implement in hardware or software and efficient in terms of memory usages and search time compared to other data structures proposed for prefix matching. We have implemented DMP-tree and the experimental results for simulated IP prefixes from the {0,1} character set show an average search time of for a large number of N, number of data elements, when the internal node branching factor M is big enough (⩾5). [ABSTRACT FROM AUTHOR]

Most of currently deployed Grid systems employ hierarchical or centralized approaches to simplify system management. However, the approaches cannot satisfy the requirements of complex Grid applications which involve hundreds or thousands of geographically distributed nodes. This paper proposes a Dynamic and Scalable Storage Management (DSSM) architecture for Grid Oriented Storage (GOS) devices. Since large-scale data intensive applications frequently involve a high degree of data access locality, the DSSM divides GOS nodes into multiple geographically distributed domains to facilitate the locality and simplify the intra-domain storage management. Dynamic GOS agents selected from the domains are organized as a virtual agent domain in a Peer-to-Peer (P2P) manner to coordinate multiple domains. As only the domain agents participate in the inter-domain communication, system wide information dissemination can be done far more efficiently than flat flooding. Grid service based storage resources are adopted to stack simple modular service piece by piece as demand grows. The decentralized architecture of DSSM avoids the hierarchical or centralized approaches of traditional Grid architectures, eliminates large-scale flat flooding of unstructured P2P systems, and provides an interoperable, seamless, and infinite storage pool in a Grid environment. The DSSM architecture is validated by a proof-of-concept prototype system. [Copyright &y& Elsevier]

It is demonstrated how dynamic storage allocation algorithms can be analyzed in terms of finite-size scaling. The method is illustrated in the three simple cases of the first-fit, next-fit and best-fit algorithms, and the system works at full capacity. The analysis is done from two different points of view—running speed and employed memory. In both cases, and for all algorithms, it is shown that a simple scaling function exists and the relevant exponents are calculated. The method can be applied on similar problems as well. [Copyright &y& Elsevier]