Optimal placement of piezoelectric patches over a smart structure

Control of structural vibrations has significant applications in manufacturing, infrastructure engineering, aerospace engineering and various consumer products. In last two decades, considerable attention has been focused to suppress structural vibrations using active vibration control technique. Various researchers have proposed various optimization criteria for optimal placement of piezoelectric patches over a smart structure to suppress vibrations using various optimization techniques. This paper presents a review of various optimization criteria and techniques that have been used by various researchers in the field of smart structures. Mathematical expressions of objective functions of twelve optimization criteria have been presented and their justifications have been reasoned. Step by step procedures of commonly used optimization techniques have also been presented.     

Flower‐shaped ultra‐wideband fractal antenna

A flower‐shaped ultra‐wideband fractal antenna is presented. It comprises a fourth iterative flower‐shaped radiator, asymmetrical stub‐loaded feeding line, and coplanar quarter elliptical ground planes. A wide operating band of 12.12 GHz (4.58‐16.7 GHz) for S ₁₁ ≤ ? 10 dB is achieved along with an overall antenna footprint of 15.7 × 11.4 mm². In addition, other desirable characteristics, that is, omnidirectional radiation patterns, peak gain upto 5 dB, and fidelity factor more than 75% are achieved. A good agreement exists between the simulation and measured results. The obtained results illustrate that this antenna has wide operating range and compact dimensions than available structures.     

Low-cost checkpointing and failure recovery in mobile computingsystems

A mobile computing system consists of mobile and stationary nodes, connected to each other by a communication network. The presence of mobile nodes in the system places constraints on the permissible energy consumption and available communication bandwidth. To minimize the lost computation during recovery from node failures, periodic collection of a consistent snapshot of the system (checkpoint) is required. Locating mobile nodes contributes to the checkpointing and recovery costs. Synchronous snapshot collection algorithms, designed for static networks, either force every node in the system to take a new local snapshot, or block the underlying computation during snapshot collection. Hence, they are not suitable for mobile computing systems. If nodes take their local checkpoints independently in an uncoordinated manner, each node may have to store multiple local checkpoints in stable storage. This is not suitable for mobile nodes as they have small memory. This paper presents a synchronous snapshot collection algorithm for mobile systems that neither forces every node to take a local snapshot, nor blocks the underlying computation during snapshot collection. If a node initiates snapshot collection, local snapshots of only those nodes that have directly or transitively affected the initiator since their last snapshots need to be taken. We prove that the global snapshot collection terminates within a finite time of its invocation and the collected global snapshot is consistent. We also propose a minimal rollback/recovery algorithm in which the computation at a node is rolled back only if it depends on operations that have been undone due to the failure of node(s). Both the algorithms have low communication and storage overheads and meet the low energy consumption and low bandwidth constraints of mobile computing systems     

Quasi-synchronous checkpointing: Models, characterization, andclassification

Checkpointing algorithms are classified as synchronous and asynchronous in the literature. In synchronous checkpointing, processes synchronize their checkpointing activities so that a globally consistent set of checkpoints is always maintained in the system. Synchronizing checkpointing activity involves message overhead and process execution may have to be suspended during the checkpointing coordination, resulting in performance degradation. In asynchronous checkpointing, processes take checkpoints without any coordination with others. Asynchronous checkpointing provides maximum autonomy for processes to take checkpoints; however, some of the checkpoints taken may not lie on any consistent global checkpoint, thus making the checkpointing efforts useless. Asynchronous checkpointing algorithms in the literature can reduce the number of useless checkpoints by making processes take communication induced checkpoints besides asynchronous checkpoints. We call such algorithms quasi-synchronous. In this paper, we present a theoretical framework for characterizing and classifying such algorithms. The theory not only helps to classify and characterize the quasi-synchronous checkpointing algorithms, but also helps to analyze the properties and limitations of the algorithms belonging to each class. It also provides guidelines for designing and evaluating such algorithms     

A one-phase algorithm to detect distributed deadlocks in replicateddatabases

Replicated databases that use quorum-consensus algorithms to perform majority voting are prone to deadlocks. Due to the P-out-of-Q nature of quorum requests, deadlocks that arise are generalized deadlocks and are hard to detect. We present an efficient distributed algorithm to detect generalized deadlocks in replicated databases. The algorithm performs reduction of a distributed wait-for-graph (WFG) to determine the existence of a deadlock. If sufficient information to decide the reducibility of a node is not available at that node, the algorithm attempts reduction later in a lazy manner. We prove the correctness of the algorithm. The algorithm has a message complexity of 2e messages and a worst-case time complexity of 2d+2 hops, where e is the number of edges and d is the diameter of the WFG. The algorithm is shown to perform significantly better in both time and message complexity than the best known existing algorithms. We conjecture that this is an optimal algorithm, in time and message complexity, to detect generalized deadlocks if no transaction has complete knowledge of the topology of the WFG or the system and the deadlock detection is to be carried out in a distributed manner     

On supporting high-throughput routing metrics in on-demand routing protocols for multi-hop wireless networks

Researchers have proposed routing metrics other than hop count, such as ETX (expected transmission count) and ETT (expected transmission time), to find routes with high throughput. These metrics are inherently suitable to be used in source routing protocols such as DSR, because link state information needs to be collected for the calculation of the shortest path. In this paper, we propose an efficient and generalized approach called accumulated path metric (APM) for supporting high-throughput metrics (HTMs) in on-demand routing protocols. One advantage of APM is that it is able to find the shortest path, in terms of a particular metric, without collecting topology information and without running a shortest-path algorithm. This will significantly simplify the existing design of supporting HTMs in DSR. We present a proof of the correctness of APM. Moreover, we address the problem of duplicate RREQ (route request) transmissions with existing HTM schemes and present a broadcast ordering (BO) technique to suppress unnecessary RREQ transmissions. We study the performance of APM and BO in both AODV and DSR, and the results verify the effectiveness of the proposed approaches.     

Majorization Minimization Technique for Optimally Solving Deep Dictionary Learning

The concept of deep dictionary learning (DDL) has been recently proposed. Unlike shallow dictionary learning which learns single level of dictionary to represent the data, it uses multiple layers of dictionaries. So far, the problem could only be solved in a greedy fashion; this was achieved by learning a single layer of dictionary in each stage where the coefficients from the previous layer acted as inputs to the subsequent layer (only the first layer used the training samples as inputs). This was not optimal; there was feedback from shallower to deeper layers but not the other way. This work proposes an optimal solution to DDL whereby all the layers of dictionaries are solved simultaneously. We employ the Majorization Minimization approach. Experiments have been carried out on benchmark datasets; it shows that optimal learning indeed improves over greedy piecemeal learning. Comparison with other unsupervised deep learning tools (stacked denoising autoencoder, deep belief network, contractive autoencoder and K-sparse autoencoder) show that our method supersedes their performance both in accuracy and speed.     

Efficient distributed detection of conjunctions of local predicates

Global predicate detection is a fundamental problem in distributed systems and finds applications in many domains such as testing and debugging distributed programs. This paper presents an efficient distributed algorithm to detect conjunctive-form global predicates in distributed systems. The algorithm detects the first consistent global state that satisfies the predicate even if the predicate is unstable. Unlike previously proposed run-time predicate detection algorithms, our algorithm does not require the exchange of control messages during the normal computation. All the necessary information to detect predicates is piggybacked on computation messages of application programs. The algorithm is distributed because the predicate detection efforts as well as the necessary information are equally distributed among the processes. We prove the correctness of the algorithm and compare its performance with respect to message, storage and computational complexities with that of the previously proposed run-time predicate detection algorithms     

不同无线技术能否共存?

新建工厂的无线技术应用已逐步获得认可,然而,还有一些过程工业对采用这项新技术或其它新的解决方案存有疑虑,主要担心多种无线技术互相之间可能存在射频干扰而影响主要通讯的可靠性,例如使用IEEE 802.11b/g和IEEE 802.15.4协议的无线电。因为两种无线电通讯采用的也是用于工业、科技和医疗的2.4GHz波段,业内人士曾