一种能量高效的无线传感器网络拓扑控制算法

通过对现有拓扑控制算法的研究,针对无线传感器网络中节点能耗分布不均匀的问题,提出了一种能量高效的拓扑控制算法(EETCA)。该算法以均衡全局能耗为目标,综合考虑了节点的剩余能量、簇的规模、数据最优传输跳数等因素,避免了部分节点能量消耗过快,从而有效地均衡网络负载。仿真结果表明:EETCA在能耗均衡方面均优于原来的算法,延长了无线传感器网络的生命周期。     

Rotator graphs: an efficient topology for point-to-pointmultiprocessor networks

Rotator graphs, a set of directed permutation graphs, are proposed as an alternative to star and pancake graphs. Rotator graphs are defined in a way similar to the recently proposed Faber-Moore graphs. They have smaller diameter, n-1 in a graph with n factorial vertices, than either the star or pancake graphs or the k-ary n-cubes. A simple optimal routing algorithm is presented for rotator graphs. The n-rotator graphs are defined as a subset of all rotator graphs. The distribution of distances of vertices in the n-rotator graphs is presented, and the average distance between vertices is found. The n-rotator graphs are shown to be optimally fault tolerant and maximally one-step fault diagnosable. The n-rotator graphs are shown to be Hamiltonian, and an algorithm for finding a Hamiltonian circuit in the graphs is given     

An efficient anonymous authentication mechanism for delay tolerant networks

Security and privacy are crucial to the wide deployments of delay tolerant networks. Without security and privacy guarantees, people are reluctant to accept such a new network paradigm. To address the security and privacy issues in delay tolerant networks, in this paper, based on ID-based ring signatures and Merkle hash tree techniques, we present a new efficient anonymous authentication mechanism. The newly proposed mechanism not only achieves good security properties, including authentication, anonymity and confidentiality, but also has strong robustness and high efficiency.     

一种无线传感器网络可靠拓扑的生成算法

在无线传感器网络（ WSNs）的应用中,网络中的节点需要将采集到的数据信息传送到汇聚节点,其信息传输的可靠性是十分重要的。然而,由于无线通信信道容易受到干扰和噪音的影响,极限情况时甚至可能造成数据传输失败,这对无线传感器网络的正常工作提出了极大挑战。针对上述问题,提出一种可靠拓扑的生成算法,通过该算法设计了一组可靠的路由拓扑,并通过仿真验证了其可靠性。     

An efficient mechanism for processing similarity search queries in sensor networks

The similarity search problem has received considerable attention in database research community. In sensor network applications, this problem is even more important due to the imprecision of the sensor hardware, and variation of environmental parameters. Traditional similarity search mechanisms are both improper and inefficient for these highly energy-constrained sensors. A difficulty is that it is hard to predict which sensor has the most similar (or closest) data item such that many or even all sensors need to send their data to the query node for further comparison. In this paper, we propose a similarity search algorithm (SSA), which is a novel framework based on the concept of Hilbert curve over a data-centric storage structure, for efficiently processing similarity search queries in sensor networks. SSA successfully avoids the need of collecting data from all sensors in the network in searching for the most similar data item. The performance study reveals that this mechanism is highly efficient and significantly outperforms previous approaches in processing similarity search queries.     

Poly: A reliable and energy efficient topology control protocol for wireless sensor networks

Energy efficiency and reliability are the two important requirements for mission-critical wireless sensor networks. In the context of sensor topology control for routing and dissemination, Connected Dominating Set (CDS) based techniques proposed in prior literature provide the most promising efficiency and reliability. In a CDS-based topology control technique, a backbone - comprising a set of highly connected nodes - is formed which allows communication between any arbitrary pair of nodes in the network. In this paper, we show that formation of a polygon in the network provides a reliable and energy-efficient topology. Based on this observation, we propose Poly, a novel topology construction protocol based on the idea of polygons. We compare the performance of Poly with three prominent CDS-based topology construction protocols namely CDS-Rule K, Energy-efficient CDS (EECDS) and A3. Our simulation results demonstrate that Poly performs consistently better in terms of message overhead and other selected metrics. We also model the reliability of Poly and compare it with other CDS-based techniques to show that it achieves better connectivity under highly dynamic network topologies.     

Time efficient k-shot broadcasting in known topology radio networks

The paper considers broadcasting protocols in radio networks with known topology that are efficient in both time and energy. The radio network is modelled as an undirected graph G = (V, E) where |V| = n. It is assumed that during execution of the communication task every node in V is allowed to transmit at most once. Under this assumption it is shown that any radio broadcast protocol requires transmission rounds, where D is the diameter of G. This lower bound is complemented with an efficient construction of a deterministic protocol that accomplishes broadcasting in rounds. Moreover, if we allow each node to transmit at most k times, the lower bound on the number of transmission rounds holds. We also provide a randomised protocol that accomplishes broadcasting in rounds. The paper concludes with a number of open problems in the area. The research of L. Gąsieniec, D.R. Kowalski and C. Su supported in part by the Royal Society grant Algorithmic and Combinatorial Aspects of Radio Communication, IJP - 2006/R2. The research of E. Kantor and D. Peleg supported in part by grants from the Minerva Foundation and the Israel Ministry of Science.     

An efficient playout smoothing mechanism for layered streaming in P2P networks

Layered video streaming in peer-to-peer (P2P) networks has drawn great interest, since it can not only accommodate large numbers of users, but also handle peer heterogeneity. However, there’s still a lack of comprehensive studies on chunk scheduling for the smooth playout of layered streams in P2P networks. In these situations, a playout smoothing mechanism can be used to ensure the uniform delivery of the layered stream. This can be achieved by reducing the quality changes that the stream undergoes when adapting to changing network conditions. This paper complements previous efforts in throughput maximization and delay minimization for P2P streaming by considering the consequences of playout smoothing on the scheduling mechanisms for stream layer acquisition. The two main problems to be considered when designing a playout smoothing mechanism for P2P streaming are the fluctuation in available bandwidth between peers and the unreliability of user-contributed resources—particularly peer churn. Since the consideration of these two factors in the selection and scheduling of stream layers is crucial to maintain smooth stream playout, the main objective of our smoothing mechanism becomes the determination of how many layers to request from which peers, and in which order. In this work, we propose a playout smoothing mechanism for layered P2P streaming. The proposed mechanism relies on a novel scheduling algorithm that enables each peer to select appropriate stream layers, along with appropriate peers to provide them. In addition to playout smoothing, the presented mechanism also makes efficient use of network resources and provides high system throughput. An evaluation of the performance of the mechanism demonstrates that the proposed mechanism provides a significant improvement in the received video quality in terms of lowering the number of layer changes and useless chunks while improving bandwidth utilization.     

Scale-free topology evolution for wireless sensor networks with reconstruction mechanism

How to improve survivability of wireless sensor networks (WSNs) is an important issue which has attracted much attention over recent years. In this paper, by resorting to complex network theories, we propose two models, namely, a linear growth evolution model (LGEM) and an accelerated growth evolution model (AGEM). In the model evolution processes, the following factors: node addition, node deletion, and link reconstruction that naturally arise from practical WSNs applications are considered. In addition, accelerated growth is introduced into the evolving processes of AGEM. Theoretical analysis shows that AGEM is an extension of the LGEM model, and AGEM is generally more flexible and accommodating in practice. Simulation results show that the degree distributions of two models have scale-free characteristics and the topologies generated by the two models show a good survivability under random and deliberate attacks.     

An efficient second-order SQP method for structural topology optimization

This article presents a Sequential Quadratic Programming (SQP) solver for structural topology optimization problems named TopSQP. The implementation is based on the general SQP method proposed in Morales et al. J Numer Anal 32(2):553–579 (2010) called SQP+. The topology optimization problem is modelled using a density approach and thus, is classified as a nonconvex problem. More specifically, the SQP method is designed for the classical minimum compliance problem with a constraint on the volume of the structure. The sub-problems are defined using second-order information. They are reformulated using the specific mathematical properties of the problem to significantly improve the efficiency of the solver. The performance of the TopSQP solver is compared to the special-purpose structural optimization method, the Globally Convergent Method of Moving Asymptotes (GCMMA) and the two general nonlinear solvers IPOPT and SNOPT. Numerical experiments on a large set of benchmark problems show good performance of TopSQP in terms of number of function evaluations. In addition, the use of second-order information helps to decrease the objective function value.     

An energy-efficient topology construction algorithm for wireless sensor networks

Topology management schemes have emerged as promising approaches for prolonging the lifetime of the wireless sensor networks (WSNs). The connected dominating set (CDS) concept has also emerged as the most popular method for energy-efficient topology control in WSNs. A sparse CDS-based network topology is highly susceptible to partitioning, while a dense CDS leads to excessive energy consumption due to overlapped sensing areas. Therefore, finding an optimal-size CDS with which a good trade-off between the network lifetime and network coverage can be made is a crucial problem in CDS-based topology control. In this paper, a degree-constrained minimum-weight version of the CDS problem, seeking for the load-balanced network topology with the maximum energy, is presented to model the energy-efficient topology control problem in WSNs. A learning automata-based heuristic is proposed for finding a near optimal solution to the proxy equivalent degree-constrained minimum-weight CDS problem in WSN. A strong theorem in presented to show the convergence of the proposed algorithm. Superiority of the proposed topology control algorithm over the prominent existing methods is shown through the simulation experiments in terms of the number of active nodes (network topology size), control message overhead, residual energy level, and network lifetime.     

HORSIC: An efficient one-time signature scheme for wireless sensor networks

One-time signature schemes are promising candidates for broadcast authentication, which is an essential security primitive in wireless sensor networks. This paper proposes HORSIC, an efficient one-time signature scheme for broadcast authentication in wireless sensor networks. Different from previous one-time signature schemes, HORSIC can reduce the public key size and signature size simultaneously at the cost of increased overhead in key generation and signature verification.     

IRPL: An energy efficient routing protocol for wireless sensor networks

This study aims to overcome the disadvantages of the original RPL (IPv6 Routing Protocol for Low power and Lossy networks) routing protocol (RPL including problems with energy consumption and energy load balance). We developed a relatively balanced RPL – the improved protocol (IRPL). This protocol is based on an efficient clustering algorithm and an effective topology control model of the loop domain communication route. The clustering algorithm can be used to calculate the optimal number of cluster heads by assumption of the network model. Combined with the clustering probability model and the node competition mechanism, the cluster head node in the wireless sensor network was used to complete the clustering process. In the topology control model, the wireless sensor network was divided into concentric rings with equal areas. Nodes determined the best network route, depending on different levels of ring domain and the optimal forwarding communication area defined in this study. Simulation results indicate that the IRPL routing protocol can reduce overall network energy consumption, balance network energy consumption, and prolong network lifetime.     

A complete and efficient CUDA-sharing solution for HPC clusters

In this paper we detail the key features, architectural design, and implementation of rCUDA, an advanced framework to enable remote and transparent GPGPU acceleration in HPC clusters. rCUDA allows decoupling GPUs from nodes, forming pools of shared accelerators, which brings enhanced flexibility to cluster configurations. This opens the door to configurations with fewer accelerators than nodes, as well as permits a single node to exploit the whole set of GPUs installed in the cluster. In our proposal, CUDA applications can seamlessly interact with any GPU in the cluster, independently of its physical location. Thus, GPUs can be either distributed among compute nodes or concentrated in dedicated GPGPU servers, depending on the cluster administrator’s policy. This proposal leads to savings not only in space but also in energy, acquisition, and maintenance costs. The performance evaluation in this paper with a series of benchmarks and a production application clearly demonstrates the viability of this proposal. Concretely, experiments with the matrix–matrix product reveal excellent performance compared with regular executions on the local GPU; on a much more complex application, the GPU-accelerated LAMMPS, we attain up to 11x speedup employing 8 remote accelerators from a single node with respect to a 12-core CPU-only execution. GPGPU service interaction in compute nodes, remote acceleration in dedicated GPGPU servers, and data transfer performance of similar GPU virtualization frameworks are also evaluated.     

On multigrid-CG for efficient topology optimization

This article presents a computational approach that facilitates the efficient solution of 3-D structural topology optimization problems on a standard PC. Computing time associated with solving the nested analysis problem is reduced significantly in comparison to other existing approaches. The cost reduction is obtained by exploiting specific characteristics of a multigrid preconditioned conjugate gradients (MGCG) solver. In particular, the number of MGCG iterations is reduced by relating it to the geometric parameters of the problem. At the same time, accurate outcome of the optimization process is ensured by linking the required accuracy of the design sensitivities to the progress of optimization. The applicability of the proposed procedure is demonstrated on several 2-D and 3-D examples involving up to hundreds of thousands of degrees of freedom. Implemented in MATLAB, the MGCG-based program solves 3-D topology optimization problems in a matter of minutes. This paves the way for efficient implementations in computational environments that do not enjoy the benefits of high performance computing, such as applications on mobile devices and plug-ins for modeling software.     

An efficient code generation technique for tiled iteration spaces

This paper presents a novel approach for the problem of generating tiled code for nested for-loops, transformed by a tiling transformation. Tiling or supernode transformation has been widely used to improve locality in multilevel memory hierarchies, as well as to efficiently execute loops onto parallel architectures. However, automatic code generation for tiled loops can be a very complex compiler work, especially when nonrectangular tile shapes and iteration space bounds are concerned. Our method considerably enhances previous work on rewriting tiled loops, by considering parallelepiped tiles and arbitrary iteration space shapes. In order to generate tiled code, we first enumerate all tiles containing points within the iteration space and, second, sweep all points within each tile. For the first subproblem, we refine upon previous results concerning the computation of new loop bounds of an iteration space that has been transformed by a nonunimodular transformation. For the second subproblem, we transform the initial parallelepiped tile into a rectangular one, in order to generate efficient code with the aid of a nonunimodular transformation matrix and its Hermite Normal Form (HNF). Experimental results show that the proposed method significantly accelerates the compilation process and generates much more efficient code.     

Compact yet efficient hardware implementation of artificial neural networks with customized topology

There are several neural network implementations using either software, hardware-based or a hardware/software co-design. This work proposes a hardware architecture to implement an artificial neural network (ANN), whose topology is the multilayer perceptron (MLP). In this paper, we explore the parallelism of neural networks and allow on-the-fly changes of the number of inputs, number of layers and number of neurons per layer of the net. This reconfigurability characteristic permits that any application of ANNs may be implemented using the proposed hardware. In order to reduce the processing time that is spent in arithmetic computation, a real number is represented using a fraction of integers. In this way, the arithmetic is limited to integer operations, performed by fast combinational circuits. A simple state machine is required to control sums and products of fractions. Sigmoid is used as the activation function in the proposed implementation. It is approximated by polynomials, whose underlying computation requires only sums and products. A theorem is introduced and proven so as to cover the arithmetic strategy of the computation of the activation function. Thus, the arithmetic circuitry used to implement the neuron weighted sum is reused for computing the sigmoid. This resource sharing decreased drastically the total area of the system. After modeling and simulation for functionality validation, the proposed architecture synthesized using reconfigurable hardware. The results are promising.     

An efficient model of neural networks for dynamic programming

Systems based on artificial neural networks have high computational rates owing to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. Neural networks with feedback connections provide a computing model capable of solving a large class of optimization problems. This paper presents a novel approach for solving dynamic programming problems using artificial neural networks. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. Simulated examples are presented and compared with other neural networks. The results demonstrate that the proposed method gives a significant improvement.     

An efficient range-free localization algorithm for wireless sensor networks

Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to...     

An efficient approach to reliability-based topology optimization for continua under material uncertainty

This contribution presents a computationally efficient method for reliability-based topology optimization for continuum domains under material properties uncertainty. Material Young’s modulus is assumed to be lognormally distributed and correlated within the domain. The computational efficiency is achieved through estimating the response statistics with stochastic perturbation of second order, using these statistics to fit an appropriate distribution that follows the empirical distribution of the response, and employing an efficient gradient-based optimizer. Two widely-studied topology optimization problems are examined and the changes in the optimized topology is discussed for various levels of target reliability and correlation strength. Accuracy of the proposed algorithm is verified using Monte Carlo simulation.